{ "name": "AI Unite report library", "description": "Every major business AI report in one place: short, sourced summaries of research from consultancies, universities, companies and government, with what each one means for mid-market companies.", "url": "https://aiunite.org", "license": "https://creativecommons.org/licenses/by/4.0/", "attribution": "AI Unite (aiunite.org). Reports belong to their publishers; cite the originals.", "generated": "2026-10-05", "count": 85, "reports": [ { "id": "challenger-job-cuts-ai-2026-08", "url": "https://aiunite.org/reports/challenger-job-cuts-ai-2026-08/", "kind": "report", "title": "Challenger Report: September Layoff Plans Fall to 43,281; Seasonal Hiring Muted", "publisher": "Challenger, Gray & Christmas", "publisher_type": "Industry research & software", "published": "2026-10-01", "updated": "2026-10-05", "topics": [ "Workforce" ], "method": "Labor data", "sample_n": "573,195 announced job cuts (Jan–Sep 2026)", "respondents": "Job cut announcements by U.S.-based employers, categorized by stated reason", "company_size": null, "geography": "US", "fieldwork": "January–September 2026", "headline_stat": "21%", "headline_label": "of announced U.S. job cuts in Jan–Sep 2026 were attributed to AI", "adoption_stage": "n/a", "summary": "Challenger, Gray & Christmas's September 2026 Challenger Report (October 2026; 573,195 announced U.S. job cuts, labor data) found that AI was cited in 120,136 announced cuts so far in 2026, about 21% of all cuts and still the leading reason year-to-date.", "findings": [ "Through September 2026, employers cited AI in 120,136 announced job cuts, approximately 21% of all cuts, still the leading reason year-to-date.", "AI was the fifth-most cited reason in September, with 3,961 cuts, about 9% of the month's total.", "Employers announced 43,281 job cuts in September, down 18% from August and 20% from September 2025, the lowest September total since 2022.", "Technology announced 165,925 cuts through September, 29% of all cuts and more than any other industry, up 54% from a year earlier.", "Announced hiring plans were 210,612 through September, up 3% from a year earlier, as seasonal hiring plans were the lowest for a September since 2011." ], "trust": "medium", "source_url": "https://www.challengergray.com/wp-content/uploads/2026/10/Challenger-Report-September-2026.pdf", "access": "free" }, { "id": "bain-technology-report-2026", "url": "https://aiunite.org/reports/bain-technology-report-2026/", "kind": "report", "title": "Technology Report 2026", "publisher": "Bain & Company", "publisher_type": "Consultancy", "published": "2026-09-29", "updated": "2026-09-30", "topics": [ "Strategy", "Productivity", "Agents" ], "method": "Executive survey", "sample_n": "293", "respondents": "Senior technology leaders (Bain Tech and Engineering Survey)", "company_size": "Not disclosed", "geography": "Not disclosed", "fieldwork": "Not disclosed", "headline_stat": "20–27%", "headline_label": "productivity gains most companies are capturing today, against an expected 95% uplift for developers within one to two years", "adoption_stage": "n/a", "summary": "Bain & Company's Technology Report 2026 (September 2026; n=293, executive survey) found that senior technology leaders expect a 95% uplift in software developer productivity within one to two years, while the gains most are capturing today are 20% to 27%.", "findings": [ "Senior technology leaders anticipate a 95% uplift in software developer productivity within the next one to two years.", "They also anticipate a 148% improvement in release-cycle speed over the same period.", "Productivity gains most companies capture today are 20% to 27% across key metrics.", "Bain estimates the AI industry needs $6 trillion in annual revenue by 2031 to justify data center spending." ], "trust": "low", "source_url": "https://www.bain.com/insights/topics/technology-report/", "access": "free" }, { "id": "kpmg-global-ai-pulse-q3-2026", "url": "https://aiunite.org/reports/kpmg-global-ai-pulse-q3-2026/", "kind": "report", "title": "Global AI Pulse Q3 2026: AI at scale: Accountability, resilience and economics", "publisher": "KPMG", "publisher_type": "Accounting & advisory", "published": "2026-09-24", "updated": "2026-09-29", "topics": [ "Agents", "ROI & value", "Governance & risk" ], "method": "Executive survey", "sample_n": "2,131", "respondents": "Senior leaders (CEO, C-suite, SVP/VP, directors reporting to C-suite)", "company_size": "$50M+ revenue ($100M+ in US and 9 other countries); US tracking sample $1B+", "geography": "20 countries (Americas 670, APAC 540, EMEA 921)", "fieldwork": "Jul 23–Aug 26, 2026", "headline_stat": "12%", "headline_label": "consistently assess the value AI generates against what it costs", "adoption_stage": "pnl", "summary": "KPMG's Global AI Pulse Q3 2026: AI at scale: Accountability, resilience and economics (September 2026; n=2,131, fielded Jul 23–Aug 26, 2026) found that 12% consistently assess the value AI generates against what it costs.", "findings": [ "34% report significant employee adoption of AI agents, up from 25% in Q1 2026.", "55% operate a formal AI 'harness' control layer, rising to 86% among those reporting established returns.", "Average planned AI investment rose to US$210 million for the next year, from US$186 million in Q1." ], "trust": "medium", "source_url": "https://kpmg.com/xx/en/our-insights/ai-and-technology/ai-pulse.html", "access": "free" }, { "id": "ey-ai-risk-governance-2026", "url": "https://aiunite.org/reports/ey-ai-risk-governance-2026/", "kind": "report", "title": "EY AI Risk and Governance Survey 2026", "publisher": "EY-Parthenon", "publisher_type": "Accounting & advisory", "published": "2026-09-15", "updated": "2026-09-30", "topics": [ "Governance & risk", "Agents" ], "method": "Executive survey", "sample_n": "202", "respondents": "US senior AI decision-makers (board members, C-suite, VP+)", "company_size": "Publicly traded, $1B+ annual revenue", "geography": "United States", "fieldwork": "May 28–Jun 15, 2026", "headline_stat": "47%", "headline_label": "say their organization has previously not applied its AI governance process for urgent deployments", "adoption_stage": "n/a", "summary": "EY's AI Risk and Governance Survey 2026 (September 2026; n=202, executive survey) found that 98% have formal AI governance policies, yet 47% say their organization has previously not applied its AI governance process for urgent deployments.", "findings": [ "98% have formal AI governance policies in place, but 47% say their organization has previously not applied its governance process for urgent deployments.", "91% say their organization uses agentic AI, and 85% of those admit at least a handful of these systems execute actions without real-time human involvement.", "26% of respondents whose organization uses agentic AI say it cannot detect unauthorized AI agents.", "About a third (36%) have experienced an AI incident or failure with a materially negative impact, such as data loss, financial damage or operational disruption." ], "trust": "medium", "source_url": "https://www.ey.com/en_us/newsroom/2026/09/ey-survey-finds-that-autonomous-ai-implementation-outpaces-oversight-yielding-an-ai-governance-gap", "access": "free" }, { "id": "ramp-ai-index-2026-09", "url": "https://aiunite.org/reports/ramp-ai-index-2026-09/", "kind": "report", "title": "Ramp AI Index, September 2026: Cracks in the AI Thesis, Part 2", "publisher": "Ramp", "publisher_type": "Industry research & software", "published": "2026-09-09", "updated": "2026-09-29", "topics": [ "Spending & investment", "Adoption" ], "method": "Usage data", "sample_n": "70,000+ businesses", "respondents": "U.S. businesses on Ramp's corporate card and bill-pay platform (August 2026 transactions)", "company_size": "Mixed; skews toward startups and tech-forward firms", "geography": "US", "fieldwork": "August 2026 transactions", "headline_stat": "$7,205", "headline_label": "median monthly AI spend per employee at the top 1% of firms in August, down 9.7%", "adoption_stage": "n/a", "summary": "Ramp's AI Index for September 2026 (September 2026; transactions from 70,000+ U.S. businesses on its platform, usage data) found that 43.8% of businesses paid for Anthropic and 39.8% for OpenAI in August, while median AI spend per employee at the top 1% of spenders fell 9.7% to $7,205 a month.", "findings": [ "43.8% of U.S. businesses on Ramp paid for Anthropic subscriptions or tokens in August, up 0.34 percentage points.", "Median per-employee monthly AI spend among the top 1% of spenders fell 9.7%, from $7,976 to $7,205.", "Ramp's effective price per million tokens fell 41% to $0.68, from a 2026 peak of $1.15 in March.", "Frontier models drove 45% of token share, down from a 53% peak in August.", "Only 3.6% of all businesses (6.4% of AI-spending businesses) use open-source models." ], "trust": "medium", "source_url": "https://ramp.com/data/ai-index-sept-2026", "access": "free" }, { "id": "gartner-scaled-ai-survey-2026", "url": "https://aiunite.org/reports/gartner-scaled-ai-survey-2026/", "kind": "report", "title": "Gartner Survey Finds Only 22% of Organizations Have Successfully Scaled AI Across Multiple Business Units (press release)", "publisher": "Gartner", "publisher_type": "Industry research & software", "published": "2026-09-01", "updated": "2026-09-29", "topics": [ "Adoption", "Strategy" ], "method": "Executive survey", "sample_n": "1,303", "respondents": "Functional leaders", "company_size": "$50M+ annual revenue (FY2025)", "geography": "Not specified in release", "fieldwork": "Jan–Apr 2026", "headline_stat": "22%", "headline_label": "of organizations have scaled AI across multiple business units or adopted an AI-first approach", "adoption_stage": "core", "summary": "Gartner's Gartner Survey Finds Only 22% of Organizations Have Successfully Scaled AI Across Multiple Business Units (press release) (September 2026; n=1,303, fielded Jan–Apr 2026) found that 22% of organizations have scaled AI across multiple business units or adopted an AI-first approach.", "findings": [ "85% of functional leaders plan to increase AI spending in 2026 after allocating an average 12% of functional budgets to AI in 2025.", "Roughly 11% of organizations were entirely unaware of what their function spent on AI in 2025.", "High performers that track ROI and cut underperforming projects reported positive returns on 81% of AI initiatives." ], "trust": "medium", "source_url": "https://www.gartner.com/en/newsroom/press-releases/gartner-survey-finds-only-22-percent-of-organizations-have-successfully-scaled-ai-across-multiple-business-units", "access": "free" }, { "id": "ny-fed-ai-hiring-2026", "url": "https://aiunite.org/reports/ny-fed-ai-hiring-2026/", "kind": "report", "title": "Businesses Are Using AI to Transform Work, Not Cut Jobs", "publisher": "Federal Reserve Bank of New York", "publisher_type": "Government & central bank", "published": "2026-09-01", "updated": "2026-09-29", "topics": [ "Workforce", "Adoption" ], "method": "Executive survey", "sample_n": null, "respondents": "Firms in the Empire State Manufacturing Survey and Business Leaders Survey (services)", "company_size": null, "geography": "New York and Northern New Jersey", "fieldwork": "August 2026 (with August 2024 and 2025 comparisons)", "headline_stat": "4%", "headline_label": "of AI-using service firms laid off workers due to AI in the past six months", "adoption_stage": "n/a", "summary": "The New York Fed's Businesses Are Using AI to Transform Work, Not Cut Jobs (September 2026; regional business surveys, executive survey) found that 61% of service firms now use AI, but only 4% laid off workers because of it in the past six months, while about 15% hired fewer and about 13% hired more.", "findings": [ "61% of service firms and 51% of manufacturers used AI in 2026, up from 40% and 26% in 2025 and 25% and 16% in 2024.", "Only 4% of service firms laid off workers in response to AI in the past six months, up from 1% last year; no manufacturers did.", "About 13% of service firms hired more workers because of AI, roughly offsetting those that hired fewer.", "Among AI adopters, the median share of workers using AI was 17% in service firms and 7% in manufacturers.", "Just over a third of AI-using service firms and more than 20% of manufacturers retrained workers in response to AI." ], "trust": "medium", "source_url": "https://libertystreeteconomics.newyorkfed.org/2026/09/businesses-are-using-ai-to-transform-work-not-cut-jobs/", "access": "free" }, { "id": "mckinsey-state-of-ai-2026", "url": "https://aiunite.org/reports/mckinsey-state-of-ai-2026/", "kind": "report", "title": "The state of AI in 2026: On the road to ROI", "publisher": "McKinsey & Company", "publisher_type": "Consultancy", "published": "2026-08-25", "updated": "2026-09-29", "topics": [ "ROI & value", "Adoption", "Agents" ], "method": "Mixed survey", "sample_n": "1,719", "respondents": "Online survey respondents at all levels, functions and tenures", "company_size": "Full range; 36% at organizations with >$1B revenue", "geography": "97 nations (weighted by GDP)", "fieldwork": "May 4–Jun 8, 2026", "headline_stat": "37%", "headline_label": "attribute any EBIT impact to AI, essentially unchanged from last year", "adoption_stage": "pnl", "summary": "McKinsey & Company's The state of AI in 2026: On the road to ROI (August 2026; n=1,719, fielded May 4–Jun 8, 2026) found that 37% attribute any EBIT impact to AI, essentially unchanged from last year.", "findings": [ "80% say AI improved their individual productivity, yet only about 6% are AI high performers, flat since 2025.", "32% decided against buying at least one software product or feature because they could build it with agentic coding tools.", "Smaller organizations (under $1B) scaling agents stayed flat at 22%; large ones rose from 27% to 40%." ], "trust": "medium", "source_url": "https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai", "access": "free" }, { "id": "openai-enterprise-signals-2026-08", "url": "https://aiunite.org/reports/openai-enterprise-signals-2026-08/", "kind": "report", "title": "Enterprise Signals: What Frontier Firms Are Doing Differently", "publisher": "OpenAI", "publisher_type": "Technology company", "published": "2026-08-12", "updated": "2026-09-29", "topics": [ "Agents", "Adoption", "Strategy" ], "method": "Usage data", "sample_n": null, "respondents": "Aggregated, de-identified usage data from OpenAI's enterprise customers (ChatGPT, Codex, API); function analysis based on more than 10 million messages", "company_size": "OpenAI enterprise customers (not broken out by size)", "geography": "Global", "fieldwork": "January–June 2026 (some measures since February 2026)", "headline_stat": "64%", "headline_label": "of enterprise output tokens (Codex plus ChatGPT) came from the Codex agent in June 2026", "adoption_stage": "n/a", "summary": "OpenAI's Enterprise Signals: What Frontier Firms Are Doing Differently (August 2026; enterprise usage data) found that as of June 2026 its Codex agent generated 64% of combined Codex and ChatGPT output tokens among enterprise customers.", "findings": [ "As of June 2026, Codex generated 64% of combined Codex and ChatGPT output tokens among OpenAI's enterprise customers.", "Frontier firms, the top 10% by usage each month, generated 8.3x as many output tokens per active user as typical firms in June, up from 2.6x in January.", "Among weekly active users, 21% at frontier firms use plugins and 19% use skills, compared with 9% and 3% at typical firms.", "Since February 2026, weekly active enterprise Codex users grew 108x in legal, 41x in sales, 41x in recruiting and 26x in marketing, compared with 5x among engineers.", "Coding and system or agent operations together account for nearly 75% of agentic messages, while writing remains the most common use of ChatGPT." ], "trust": "medium", "source_url": "https://openai.com/signals/enterprise-data/", "access": "free" }, { "id": "cbiz-mid-market-pulse-q3-2026", "url": "https://aiunite.org/reports/cbiz-mid-market-pulse-q3-2026/", "kind": "report", "title": "Mid-Market Pulse No. 3, 2026: AI Adoption Surges as Healthcare Costs Rise", "publisher": "CBIZ", "publisher_type": "Accounting & advisory", "published": "2026-08-10", "updated": "2026-09-29", "topics": [ "Mid-market", "ROI & value" ], "method": "Executive survey", "sample_n": null, "respondents": "Middle-market business leaders and CBIZ clients", "company_size": null, "geography": "US", "fieldwork": null, "headline_stat": "2%", "headline_label": "of respondents report achieving measurable business impact from AI", "adoption_stage": "pnl", "summary": "CBIZ's Mid-Market Pulse No. 3, 2026: AI Adoption Surges as Healthcare Costs Rise (August 2026) found that 2% of respondents report achieving measurable business impact from AI.", "findings": [ "63% of organizations are actively exploring, piloting or implementing AI.", "Only 2% claim to have achieved measurable business impact from AI.", "Barriers: risk and governance (52%), lack of internal expertise (43%), integration and infrastructure (38%)." ], "trust": "low", "source_url": "https://www.cbiz.com/insights/mid-market-pulse/mid-market-pulse-no3-2026", "access": "free" }, { "id": "stanford-del-canaries-2025", "url": "https://aiunite.org/reports/stanford-del-canaries-2025/", "kind": "report", "title": "Canaries in the Coal Mine? Six Facts about the Recent Employment Effects of Artificial Intelligence", "publisher": "Stanford Digital Economy Lab", "publisher_type": "University & nonprofit", "published": "2026-08", "updated": "2026-09-29", "topics": [ "Workforce" ], "method": "Labor data", "sample_n": "3.5–5 million employees per month", "respondents": "Balanced panel of firms using ADP payroll services", "company_size": null, "geography": "US", "fieldwork": "Jan 2021–Jun 2026 monthly payroll records", "headline_stat": "19%", "headline_label": "shortfall in employment of 22–25-year-olds in AI-exposed jobs vs. less-exposed peers", "adoption_stage": "n/a", "summary": "Stanford Digital Economy Lab's Canaries in the Coal Mine? (August 2026 update; ADP payroll data on 3.5–5 million workers a month, labor data) found that employment of 22–25-year-olds in the most AI-exposed occupations stands 19% below where it would be had it kept pace with less-exposed peers, while overall employment shows no widespread displacement.", "findings": [ "Employment of workers aged 22–25 in AI-exposed occupations is 19% below where it would be had it kept pace with less-exposed peers.", "The gap has widened from 15% at the July 2025 data vintage to 19% as of June 2026.", "In levels, employment of 22–25-year-olds in the two most exposed quintiles fell about 11% from November 2022 to June 2026, while the same age group in the three least-exposed quintiles grew about 10%.", "Across the whole ADP sample, employment rose about 6% from November 2022 to June 2026, and about 4% in the most exposed quintile.", "Declines concentrate in occupations where AI usage mainly substitutes for human tasks; where it mainly complements workers, employment is flat or rising." ], "trust": "high", "source_url": "https://digitaleconomy.stanford.edu/publication/canaries-in-the-coal-mine-six-facts-about-the-recent-employment-effects-of-artificial-intelligence/", "access": "free" }, { "id": "ibm-cost-data-breach-2026", "url": "https://aiunite.org/reports/ibm-cost-data-breach-2026/", "kind": "report", "title": "Cost of a Data Breach Report 2026", "publisher": "IBM Institute for Business Value", "publisher_type": "Technology company", "published": "2026-07-29", "updated": "2026-09-29", "topics": [ "Governance & risk", "ROI & value" ], "method": "Field study", "sample_n": "602 organizations", "respondents": "Organizations that experienced a data breach, interviewed by Ponemon Institute; follow-on study of 456 organizations in May 2026", "company_size": "Mixed", "geography": "Global", "fieldwork": "Breaches from Mar 2025 – Feb 2026", "headline_stat": "1 in 4", "headline_label": "malicious breaches were AI-enabled", "adoption_stage": "n/a", "summary": "IBM's Cost of a Data Breach Report 2026 (July 2026; 602 breached organizations studied by Ponemon Institute) found that one in four malicious breaches were AI-enabled, costing about $6 million on average versus a $4.99 million global average.", "findings": [ "The global average cost of a data breach rose 12% to a record $4.99 million.", "One in four malicious breaches were AI-enabled, and AI-driven attacks rose 56%, adding about $1 million per breach.", "Roughly one in five organizations reported an attack on AI models or applications, and 92% of those lacked proper AI access controls.", "Model inversion and prompt injection attacks cost an average $6.07 million and $5.89 million per breach.", "Organizations with extensive use of AI and automation in security saved an average $1.93 million per breach." ], "trust": "medium", "source_url": "https://www.ibm.com/reports/data-breach", "access": "gated" }, { "id": "ncmm-mmi-midyear-2026", "url": "https://aiunite.org/reports/ncmm-mmi-midyear-2026/", "kind": "report", "title": "Mid-Year 2026 Middle Market Indicator", "publisher": "National Center for the Middle Market", "publisher_type": "University & nonprofit", "published": "2026-07-29", "updated": "2026-09-29", "topics": [ "Mid-market", "Adoption" ], "method": "Executive survey", "sample_n": "1,000", "respondents": "CEOs, CFOs and other C-suite executives", "company_size": "$10M–$1B revenue", "geography": "US", "fieldwork": "June 2026", "headline_stat": "9 in 10", "headline_label": "middle market companies report using AI", "adoption_stage": "tried", "summary": "National Center for the Middle Market's Mid-Year 2026 Middle Market Indicator (July 2026; n=1,000, fielded June 2026) found that 9 in 10 middle market companies report using AI.", "findings": [ "Year-over-year revenue growth held at 11% while employment growth slowed to 7.2%, its lowest post-pandemic level.", "Nine in ten middle market companies report using AI, and AI remains the leading investment priority.", "More than four in five report AI concerns, including data privacy and security, implementation costs, data quality and workforce capabilities." ], "trust": "high", "source_url": "https://www.middlemarketcenter.org/u-s-middle-market-sustains-double-digit-growth-while-ai-fuels-a-shift-toward-productivity/", "access": "free" }, { "id": "veracode-genai-code-security-2026", "url": "https://aiunite.org/reports/veracode-genai-code-security-2026/", "kind": "report", "title": "2026 GenAI Code Security Report", "publisher": "Veracode", "publisher_type": "Technology company", "published": "2026-07-28", "updated": "2026-09-29", "topics": [ "Governance & risk", "Productivity" ], "method": "Benchmark", "sample_n": "11 new models, 80 tasks (100+ models tracked since 2025)", "respondents": "Large language models generating code without security-specific prompting", "company_size": null, "geography": null, "fieldwork": "Summer 2026 snapshot; four snapshots since 2025", "headline_stat": "56%", "headline_label": "average security pass rate for AI-generated code, flat since 2025", "adoption_stage": "n/a", "summary": "Veracode's 2026 GenAI Code Security Report (July 2026; 11 new models tested on 80 coding tasks, benchmark) found that AI-generated code passed security tests 56% of the time on average, barely changed from 55% in its first report.", "findings": [ "The average security pass rate across models was 56%, barely changed from 55% in the first report.", "The best model in the Summer 2026 snapshot, GPT-5.5, passed 68% of security tasks; six of eleven models scored 50–53%.", "Coding-specialized models averaged 51% and general-purpose models 52%.", "Pass rates ranged from 87% on cryptographic algorithms and 83% on SQL injection to 15% on cross-site scripting and 12% on log injection.", "Java had the lowest mean security pass rate at 30%." ], "trust": "medium", "source_url": "https://www.veracode.com/resources/analyst-reports/2026-genai-code-security-report/", "access": "gated" }, { "id": "accenture-pulse-of-change-2026-jul", "url": "https://aiunite.org/reports/accenture-pulse-of-change-2026-jul/", "kind": "report", "title": "Pulse of Change (July 2026)", "publisher": "Accenture", "publisher_type": "Consultancy", "published": "2026-07-26", "updated": "2026-09-29", "topics": [ "ROI & value", "Workforce" ], "method": "Mixed survey", "sample_n": "6,000 (3,000 C-suite + 3,000 employees)", "respondents": "C-suite leaders and non-C-suite employees", "company_size": "$500M+ revenue", "geography": "20 countries, 19 industries", "fieldwork": "Apr–Jun 2026", "headline_stat": "23%", "headline_label": "of C-suite report widespread, sustained business value from AI, down from 32% earlier in 2026", "adoption_stage": "pnl", "summary": "Accenture's Pulse of Change (July 2026) (July 2026; n=6,000 (3,000 C-suite + 3,000 employees), fielded Apr–Jun 2026) found that 23% of C-suite report widespread, sustained business value from AI, down from 32% earlier in 2026.", "findings": [ "82% of C-suite leaders are increasing AI investment; 49% of companies are piloting or deploying AI agents.", "81% of employees say AI tools increased their productivity; 71% say job satisfaction rose since AI tools arrived.", "78% of leaders expect roles to change within 12 months; 57% of employees say their roles already changed." ], "trust": "medium", "source_url": "https://www.accenture.com/en/insights/pulse-of-change", "access": "free" }, { "id": "deloitte-cfo-signals-q2-2026", "url": "https://aiunite.org/reports/deloitte-cfo-signals-q2-2026/", "kind": "report", "title": "CFO Signals Q2 2026: AI governance and risk management", "publisher": "Deloitte", "publisher_type": "Accounting & advisory", "published": "2026-07-23", "updated": "2026-09-29", "topics": [ "Strategy", "Governance & risk" ], "method": "Executive survey", "sample_n": "200", "respondents": "CFOs", "company_size": "$1B+ revenue", "geography": "North America", "fieldwork": "May 22–Jun 7, 2026", "headline_stat": "93%", "headline_label": "of CFOs say their organizations use AI across key operations", "adoption_stage": "core", "summary": "Deloitte's CFO Signals Q2 2026: AI governance and risk management (July 2026; n=200, fielded May 22–Jun 7, 2026) found that 93% of CFOs say their organizations use AI across key operations.", "findings": [ "59% say balancing pressure to deploy AI quickly with managing risk is their top AI-governance challenge.", "46% cite cost uncertainty or transparency as their biggest internal concern about their organization's AI use.", "43% name litigation over protected or private content as a leading external AI risk." ], "trust": "medium", "source_url": "https://www.deloitte.com/us/en/insights/topics/business-strategy-growth/2q-2026-cfo-signals-survey.html", "access": "free" }, { "id": "dx-state-of-ai-impact-engineering-q2-2026", "url": "https://aiunite.org/reports/dx-state-of-ai-impact-engineering-q2-2026/", "kind": "report", "title": "State of AI Impact in Engineering: Q2 2026 Report", "publisher": "DX", "publisher_type": "Industry research & software", "published": "2026-07-22", "updated": "2026-09-29", "topics": [ "Productivity", "Spending & investment", "ROI & value" ], "method": "Usage data", "sample_n": "500+ engineering organizations", "respondents": "DX customer engineering organizations (system telemetry plus developer surveys)", "company_size": "Includes organizations with 15–99 engineers through 750+ engineers", "geography": null, "fieldwork": "Apr–Jun 2026, with trend data back to Q3 2025", "headline_stat": "52.7%", "headline_label": "of all code is AI-generated, up from 24% two quarters earlier", "adoption_stage": "n/a", "summary": "DX's State of AI Impact in Engineering: Q2 2026 Report (July 2026; n=500+ engineering organizations, telemetry plus surveys) found that AI-generated code reached 52.7% of all code while median quarterly AI spend grew nearly 28x in a year in the tech sector and the share of time on new feature work stayed at roughly 57–58%.", "findings": [ "AI-generated code accounted for 52.7% of all code, up from 24% two quarters earlier.", "Median quarterly AI spend grew from roughly $1.5K to $44K in a year in the tech sector, a nearly 28x increase.", "Median weekly throughput rose 37%, from 1.42 to 1.94 pull requests per engineer per week.", "Organizations with 15–99 engineers hit about 2.2 PRs per engineer per week, versus 1.2 for those with 750+ engineers.", "Change confidence fell 6.1% while code maintainability improved 3.8%; the Developer Experience Index fell from 67 to 65." ], "trust": "medium", "source_url": "https://getdx.com/report/state-of-ai-impact-in-engineering-q2-report/", "access": "gated" }, { "id": "domino-enterprise-ai-report-2026", "url": "https://aiunite.org/reports/domino-enterprise-ai-report-2026/", "kind": "report", "title": "The Fifth Annual Domino Enterprise AI Report", "publisher": "Domino Data Lab", "publisher_type": "Technology company", "published": "2026-07-21", "updated": "2026-09-29", "topics": [ "ROI & value", "Agents", "Governance & risk" ], "method": "Executive survey", "sample_n": "639", "respondents": "Senior enterprise AI leaders, director level and above, in financial services and insurance, life sciences and public sector (fielded by BARC Research)", "company_size": "$100M+ annual revenue (56% at $1B+)", "geography": "North America (397), UK (148), continental Europe (94)", "fieldwork": "April 2026", "headline_stat": "57%", "headline_label": "say AI returns are not keeping pace with investment, unchanged since 2025", "adoption_stage": "n/a", "summary": "Domino Data Lab's Fifth Annual Domino Enterprise AI Report (July 2026; n=639 senior AI leaders, executive survey) found that 57% of enterprises say AI returns are not keeping pace with investment, unchanged since 2025, even as 93% report improved ability to move AI into production.", "findings": [ "57% of enterprises say AI ROI fails to outpace their investment, the same share as in 2025.", "The share reporting ROI at or below investment was 51.1% in North America, 66.9% in the UK and 67.0% in continental Europe.", "43% have agentic AI running in governed production, while 41% are piloting (12%) or scaling (29%) agents without governance.", "40% still rely entirely on at least one mediated access method, such as scheduled reports or analyst requests, to get AI insights to business users.", "75% of organizations with fully integrated AI governance report significantly improved AI delivery speed, versus 23% where governance is falling behind." ], "trust": "medium", "source_url": "https://domino.ai/enterprise-ai-report", "access": "gated" }, { "id": "rsm-mm-ai-2026", "url": "https://aiunite.org/reports/rsm-mm-ai-2026/", "kind": "report", "title": "RSM Middle Market AI Survey 2026: U.S. and Canada", "publisher": "RSM US", "publisher_type": "Accounting & advisory", "published": "2026-07-21", "updated": "2026-09-29", "topics": [ "Mid-market", "Adoption", "ROI & value" ], "method": "Executive survey", "sample_n": "1,030", "respondents": "Mid-level managers or higher with influence over technology investment decisions (827 U.S., 203 Canada)", "company_size": "$30M–$10B revenue (U.S.); $30M–$1B (Canada)", "geography": "US + Canada", "fieldwork": "Mar 5–16, 2026", "headline_stat": "36%", "headline_label": "have AI fully embedded across core processes", "adoption_stage": "core", "summary": "RSM US's RSM Middle Market AI Survey 2026: U.S. and Canada (July 2026; n=1,030, fielded Mar 5–16, 2026) found that 36% have AI fully embedded across core processes.", "findings": [ "86% have partially or fully integrated AI into operations, and 97% say they are satisfied with the business value AI delivers.", "Only 36% have AI fully embedded across core processes; about half of recent pilots produced moderate or limited results.", "Data quality (34%), security or privacy (30%) and legacy integration (28%) are the most-cited barriers to deploying AI; 58% plan to invest $1M or more this fiscal year." ], "trust": "medium", "source_url": "https://rsmus.com/insights/services/digital-transformation/rsm-middle-market-ai-survey.html", "access": "free" }, { "id": "yale-budget-lab-ai-labor-market-2026-09", "url": "https://aiunite.org/reports/yale-budget-lab-ai-labor-market-2026-09/", "kind": "report", "title": "Tracking the Impact of AI on the Labor Market", "publisher": "The Budget Lab at Yale", "publisher_type": "University & nonprofit", "published": "2026-07-16", "updated": "2026-09-29", "topics": [ "Workforce" ], "method": "Government statistics", "sample_n": null, "respondents": "Current Population Survey (CPS) microdata, plus Anthropic Economic Index usage data", "company_size": null, "geography": "US", "fieldwork": "CPS data through August 2026 (tracker updated Sept 15, 2026)", "headline_stat": "~1 pt", "headline_label": "how much faster the job mix has shifted since ChatGPT than during the early internet era (Oct 2025 baseline)", "adoption_stage": "n/a", "summary": "The Budget Lab at Yale's Tracking the Impact of AI on the Labor Market (July 2026, updated September 2026; CPS microdata through August 2026, government statistics) found no clear evidence of labor market disruption associated with AI, with occupational churn, AI exposure among the unemployed, and usage measures flat, within historical ranges, or on pre-AI trends.", "findings": [ "As of the September 15, 2026 update using August 2026 CPS data, the tracker finds no clear evidence of labor market disruption associated with AI.", "Measures of AI usage show no connection to changes in employment or unemployment.", "In the October 2025 baseline analysis, the occupational mix since November 2022 was on a path only about 1 percentage point above the pace seen with the internet from 1996.", "Unemployed workers came from occupations where about 25 to 35 percent of tasks could be performed by generative AI, with no clear upward trend." ], "trust": "high", "source_url": "https://budgetlab.yale.edu/research/tracking-impact-ai-labor-market", "access": "free" }, { "id": "indeed-hiring-lab-ai-job-postings-2026", "url": "https://aiunite.org/reports/indeed-hiring-lab-ai-job-postings-2026/", "kind": "report", "title": "AI and Job Postings: From Destruction to Creation?", "publisher": "Indeed Hiring Lab", "publisher_type": "Industry research & software", "published": "2026-07-08", "updated": "2026-09-29", "topics": [ "Workforce" ], "method": "Labor data", "sample_n": null, "respondents": "Job postings on Indeed", "company_size": null, "geography": "US (with comparisons to other large economies)", "fieldwork": "Postings from Feb 2020 through June 2026", "headline_stat": "71%", "headline_label": "of the rise in US software development postings (May 2025–May 2026) came from senior roles", "adoption_stage": "n/a", "summary": "Indeed Hiring Lab's AI and Job Postings: From Destruction to Creation? (July 2026; Indeed US job postings, labor data) found that software development postings rose almost 15% since late February 2025 while all postings fell 7%, with 71% of the past year's increase coming from senior roles.", "findings": [ "US software development postings have grown almost 15% since late February 2025, while overall postings fell 7%.", "Software development postings remain about 27.5% below their pre-pandemic level.", "71% of the increase in software development postings between May 2025 and May 2026 came from senior roles.", "From May 2022 to May 2026, more AI-exposed occupations saw larger declines in postings; from May 2025 to May 2026 the relationship reversed." ], "trust": "medium", "source_url": "https://hiringlab.indeed.com/2026/07/08/ai-and-job-postings-from-destruction-to-creation/", "access": "free" }, { "id": "schwab-ria-benchmarking-2026", "url": "https://aiunite.org/reports/schwab-ria-benchmarking-2026/", "kind": "report", "title": "2026 RIA Benchmarking Study", "publisher": "Charles Schwab", "publisher_type": "Financial institution", "published": "2026-07", "updated": "2026-09-29", "topics": [ "Professional services", "Adoption" ], "method": "Benchmark", "sample_n": "1,236", "respondents": "Independent RIA firms that custody assets with Schwab", "company_size": "Firms representing $2.5T+ AUM in aggregate", "geography": "US", "fieldwork": "Jan–Mar 2026", "headline_stat": "31% vs 19%", "headline_label": "Top Performing Firms vs. all others using AI to automate time-consuming, manual workflows", "adoption_stage": "core", "summary": "Charles Schwab's 2026 RIA Benchmarking Study (July 2026; n=1,236, fielded Jan–Mar 2026) found that 31% vs 19% Top Performing Firms vs. all others using AI to automate time-consuming, manual workflows.", "findings": [ "Top Performing Firms use AI to automate time-consuming, manual workflows 31% of the time versus 19% for other firms.", "Among firms with $250 million or more in assets under management, AI usage reached 83%, led by administrative tasks (65%) and client correspondence (49%).", "47% of firms use AI to draft job descriptions; 35% use it to formulate interview questions." ], "trust": "medium", "source_url": "https://advisorservices.schwab.com/insights-hub/perspectives/ria-benchmarking-study-2026", "access": "free" }, { "id": "ramp-heavy-ai-adopters-hire-more-2026", "url": "https://aiunite.org/reports/ramp-heavy-ai-adopters-hire-more-2026/", "kind": "report", "title": "A New Look at AI's Impact on Jobs: Firm-Level AI Spending and Workforce Adjustment", "publisher": "Ramp", "publisher_type": "Industry research & software", "published": "2026-06-30", "updated": "2026-09-29", "topics": [ "Workforce", "Spending & investment" ], "method": "Usage data", "sample_n": "More than 21,000 firms", "respondents": "Ramp corporate card and bill-pay customers, linked to Revelio Labs workforce data", "company_size": null, "geography": "US", "fieldwork": "Spending and headcount through end of 2025; 24 months after adoption", "headline_stat": "10.2%", "headline_label": "headcount growth at high-intensity AI adopters over two years", "adoption_stage": "n/a", "summary": "Ramp Economics Lab's A New Look at AI's Impact on Jobs (June 2026; more than 21,000 US firms, spending and workforce data) found that firms in the top third of AI spend per employee grew headcount 10.2% and entry-level headcount 12% over the two years after adoption, while low-intensity adopters showed no significant change.", "findings": [ "High-intensity AI adopters grew headcount 10.2% over the two years after adoption.", "Entry-level headcount at high-intensity adopters grew 12% over the same period.", "Low-intensity adopters saw no statistically significant change in headcount.", "Headcount did not rise until 6–12 months after adoption.", "Adopters were already larger, more engineering-intensive, more likely to be venture-backed, and faster-growing before adoption." ], "trust": "medium", "source_url": "https://ramp.com/data/heavy-ai-adopters-hire-more", "access": "free" }, { "id": "anthropic-economic-index-2026-06", "url": "https://aiunite.org/reports/anthropic-economic-index-2026-06/", "kind": "report", "title": "Anthropic Economic Index report: Cadences", "publisher": "Anthropic", "publisher_type": "Technology company", "published": "2026-06-26", "updated": "2026-09-29", "topics": [ "Workforce", "Adoption" ], "method": "Usage data", "sample_n": "~9,700 linked survey respondents; Claude usage data; 81,000 user interviews (Dec 2025)", "respondents": "Claude users", "company_size": "n/a", "geography": "Global", "fieldwork": "Apr 10 – Jun 10, 2026", "headline_stat": "86%", "headline_label": "of surveyed Claude users report speed gains from AI", "adoption_stage": null, "summary": "Anthropic's Anthropic Economic Index report: Cadences (June 2026; n=~9,700 linked survey respondents; Claude usage data; 81,000 user interviews (Dec 2025), fielded Apr 10 – Jun 10, 2026) found that 86% of surveyed Claude users report speed gains from AI.", "findings": [ "Over one-third of respondents expect AI to handle most or nearly all of their work tasks within 12 months.", "10% rated losing their job in the next year as likely or very likely.", "Computer and mathematical occupations were 30% of respondents versus 4% of US employment." ], "trust": "low", "source_url": "https://www.anthropic.com/research/economic-index-june-2026-report", "access": "free" }, { "id": "tr-future-professionals-2026", "url": "https://aiunite.org/reports/tr-future-professionals-2026/", "kind": "report", "title": "Future of Professionals Report 2026", "publisher": "Thomson Reuters Institute", "publisher_type": "Technology company", "published": "2026-06-22", "updated": "2026-09-29", "topics": [ "Professional services", "Workforce" ], "method": "Mixed survey", "sample_n": "1,816", "respondents": "Professionals in law, tax, audit, accounting, compliance, risk and global trade (firms and in-house)", "company_size": null, "geography": "62 countries", "fieldwork": "Mar–Apr 2026", "headline_stat": "6%", "headline_label": "of corporate clients say most or all providers deliver AI-enabled quality improvements (78% say it is essential)", "adoption_stage": null, "summary": "Thomson Reuters Institute's Future of Professionals Report 2026 (June 2026; n=1,816, fielded Mar–Apr 2026) found that 6% of corporate clients say most or all providers deliver AI-enabled quality improvements (78% say it is essential).", "findings": [ "74% of professionals use AI tools several times a week; 44% rely on them multiple times a day.", "78% of corporate clients say AI-enabled quality improvements are very important or essential; just 6% say most providers deliver them.", "Among firms with named AI strategies, 35% say day-to-day practice does not match the stated direction." ], "trust": "high", "source_url": "https://www.thomsonreuters.com/en/institute/reports/future-of-professionals-2026", "access": "free" }, { "id": "usbank-small-business-perspective-2026", "url": "https://aiunite.org/reports/usbank-small-business-perspective-2026/", "kind": "report", "title": "The Small Business Perspective 2026 (U.S. Bank Small Business Survey)", "publisher": "U.S. Bank", "publisher_type": "Financial institution", "published": "2026-06-22", "updated": "2026-09-29", "topics": [ "Adoption" ], "method": "Small business survey", "sample_n": "1,000 (+200 Gen Z oversample)", "respondents": "Small business owners", "company_size": "Up to $25M revenue, 2–99 employees", "geography": "US", "fieldwork": "Feb 27 – Mar 17, 2026", "headline_stat": "75%", "headline_label": "of small business owners say they now use AI in their business", "adoption_stage": "tried", "summary": "U.S. Bank's The Small Business Perspective 2026 (U.S. Bank Small Business Survey) (June 2026; n=1,000 (+200 Gen Z oversample), fielded Feb 27 – Mar 17, 2026) found that 75% of small business owners say they now use AI in their business.", "findings": [ "Owners most often apply AI to marketing and sales (56%), data analysis (51%), content creation (51%) and automation (44%).", "89% say AI delivers measurable value, yet 53% also report negative impacts such as added complexity and overstated benefits.", "Growing businesses were more likely to use generative AI than non-growing ones (81% vs. 64%)." ], "trust": "medium", "source_url": "https://www.usbank.com/about-us-bank/news-and-stories/article-library/us-bank-survey-gen-z-small-business-owners-making-bigger-bets-to-drive-growth.html", "access": "free" }, { "id": "pwc-ai-jobs-barometer-2026", "url": "https://aiunite.org/reports/pwc-ai-jobs-barometer-2026/", "kind": "report", "title": "2026 Global AI Jobs Barometer: Two futures for jobs in an AI era", "publisher": "PwC", "publisher_type": "Accounting & advisory", "published": "2026-06-15", "updated": "2026-09-29", "topics": [ "Workforce" ], "method": "Labor data", "sample_n": null, "respondents": "Not a survey: analysis of 1B+ job ads plus company financial data", "company_size": "N/A", "geography": "27 countries/territories, 6 continents", "fieldwork": "Job ads data through 2025 (2018/2019 baselines)", "headline_stat": "62%", "headline_label": "average wage premium for jobs requiring AI skills, up from 57% last year", "adoption_stage": null, "summary": "PwC's 2026 Global AI Jobs Barometer: Two futures for jobs in an AI era (June 2026; fielded Job ads data through 2025 (2018/2019 baselines)) found that 62% average wage premium for jobs requiring AI skills, up from 57% last year.", "findings": [ "Most AI-exposed companies grew headcount 52% vs 36% for least exposed (2018 baseline), with higher wage growth (24% vs 17%).", "'Professionalised' roles saw twice the job growth and 42% faster salary growth than roles 'democratised' by AI.", "US AI-exposed entry-level roles requiring senior-level skills grew 35% since 2019, while other entry-level roles fell 10%." ], "trust": "medium", "source_url": "https://www.pwc.com/gx/en/news-room/press-releases/2026/pwc-2026-ai-jobs-barometer.html", "access": "free" }, { "id": "glean-work-ai-index-2026", "url": "https://aiunite.org/reports/glean-work-ai-index-2026/", "kind": "report", "title": "Work AI Index 2026: Botsitting, Botshitting & the Hidden Human Labor of AI at Work", "publisher": "Glean (Work AI Institute)", "publisher_type": "Technology company", "published": "2026-06-10", "updated": "2026-09-29", "topics": [ "Productivity", "Workforce", "ROI & value" ], "method": "Worker survey", "sample_n": "6,000", "respondents": "Full-time digital workers (U.S. 3,000; U.K. 1,500; Australia 1,500), plus AI-leader interviews and aggregated workplace AI interaction data", "company_size": null, "geography": "US, UK, Australia", "fieldwork": "Dec 2025–Jan 2026", "headline_stat": "6.4 hrs", "headline_label": "per week spent 'botsitting': feeding, checking, and fixing AI", "adoption_stage": "n/a", "summary": "Glean's Work AI Index 2026 (June 2026; n=6,000 digital workers, worker survey) found that workers say AI saves them about 11 hours a week, yet they spend 6.4 hours a week 'botsitting' AI and only 13% say AI has significantly improved their organization's performance.", "findings": [ "87% of digital workers use AI at work, 75% say it makes them more productive, and they report saving roughly 11 hours a week.", "Workers spend 6.4 hours a week 'botsitting', which is 37% of their AI time.", "69% of AI users admit to shipping AI-generated work they have not verified, don't fully understand, or can't stand behind.", "77% of AI users juggle multiple AI tools each week, and 60% rerun the same prompt across tools because the first output was not good enough.", "53% say important information they need is not accessible from their AI tools." ], "trust": "medium", "source_url": "https://www.glean.com/work-ai-institute/reports/work-ai-index", "access": "gated" }, { "id": "cpacom-bluej-tax-ai-2026", "url": "https://aiunite.org/reports/cpacom-bluej-tax-ai-2026/", "kind": "report", "title": "AI Tax Research Solution Outlook Report 2026", "publisher": "CPA.com and Blue J", "publisher_type": "Industry research & software", "published": "2026-06-08", "updated": "2026-09-29", "topics": [ "Professional services", "Adoption" ], "method": "Mixed survey", "sample_n": "1,000+", "respondents": "Tax professionals", "company_size": null, "geography": "US", "fieldwork": null, "headline_stat": "60%", "headline_label": "of tax professionals use AI for tax research at least weekly, up from 33% in 2025", "adoption_stage": "approved", "summary": "CPA.com and Blue J's AI Tax Research Solution Outlook Report 2026 (June 2026; n=1,000+) found that 60% of tax professionals use AI for tax research at least weekly, up from 33% in 2025.", "findings": [ "60% use AI for tax research at least weekly, nearly double the 33% reported in 2025.", "84% report time savings; freed time goes to client relationships (50%), staff wellness (47%) and advisory quality (46%).", "69% anticipate shifting toward value-based or fixed-fee billing." ], "trust": "low", "source_url": "https://www.cpa.com/news/blue-j-and-cpacom-survey-finds-ai-adoption-among-tax-firms-has-nearly-doubled-one-year", "access": "gated" }, { "id": "bcg-ai-at-work-2026", "url": "https://aiunite.org/reports/bcg-ai-at-work-2026/", "kind": "report", "title": "AI at Work 2026: Why Strategy Matters More Than Tools", "publisher": "Boston Consulting Group", "publisher_type": "Consultancy", "published": "2026-06-03", "updated": "2026-09-29", "topics": [ "Workforce", "Adoption" ], "method": "Worker survey", "sample_n": "11,749", "respondents": "Frontline employees, managers and leaders", "company_size": "Not specified", "geography": "14 markets", "fieldwork": "2026 (dates not stated)", "headline_stat": "74%", "headline_label": "of frontline employees are now regular AI users, up 23 points from 2025", "adoption_stage": "tried", "summary": "Boston Consulting Group's AI at Work 2026: Why Strategy Matters More Than Tools (June 2026; n=11,749, fielded 2026 (dates not stated)) found that 74% of frontline employees are now regular AI users, up 23 points from 2025.", "findings": [ "42% of frontline regular AI users save about eight hours a week, but 66% get limited or no guidance on using that time.", "Clear strategy lifts measurable business impact about 25 points; better tools alone move it about 5 points.", "30% say their organizations have integrated AI agents into workflows, up from 13%; half say governance for human-AI teams is unclear." ], "trust": "medium", "source_url": "https://www.bcg.com/publications/2026/ai-at-work-why-strategy-matters-more-than-tools", "access": "free" }, { "id": "minneapolis-fed-ai-adoption-2026", "url": "https://aiunite.org/reports/minneapolis-fed-ai-adoption-2026/", "kind": "report", "title": "AI adoption in business grows steadily but unevenly", "publisher": "Federal Reserve Bank of Minneapolis", "publisher_type": "Government & central bank", "published": "2026-05-29", "updated": "2026-09-29", "topics": [ "Minnesota & Midwest", "Adoption" ], "method": "Government statistics", "sample_n": null, "respondents": "Analysis of Census BTOS data, including an April 2026 AI supplement", "company_size": "All sizes", "geography": "US, Ninth District, Minnesota", "fieldwork": "Sep 2023 – early 2026 (BTOS waves)", "headline_stat": "~20%", "headline_label": "of Minnesota businesses use AI, the highest in the Ninth District (district ~18%)", "adoption_stage": "tried", "summary": "Federal Reserve Bank of Minneapolis's AI adoption in business grows steadily but unevenly (May 2026; fielded Sep 2023 – early 2026 (BTOS waves)) found that ~20% of Minnesota businesses use AI, the highest in the Ninth District (district ~18%).", "findings": [ "Nationally, AI use in producing goods or services was about 10% in late 2025; under the broader question it reached 20% in early 2026.", "About 30% of US firms with 250+ employees use AI versus 17% of firms with fewer than 20 employees.", "About 96% of AI-using firms reported no change in employment; 10% said AI now performs tasks previously done by employees." ], "trust": "high", "source_url": "https://www.minneapolisfed.org/article/2026/ai-adoption-in-business-grows-steadily-but-unevenly", "access": "free" }, { "id": "census-btos-ai-use-2026-05", "url": "https://aiunite.org/reports/census-btos-ai-use-2026-05/", "kind": "report", "title": "Large Firms With at Least 20 Employees Biggest AI Users (America Counts story, Business Trends and Outlook Survey)", "publisher": "U.S. Census Bureau", "publisher_type": "Government & central bank", "published": "2026-05-26", "updated": "2026-09-29", "topics": [ "Adoption", "Mid-market" ], "method": "Government statistics", "sample_n": "Biweekly nationally representative BTOS panel (~1.2M firms sampled; ~20,000 responses per wave per Fed note)", "respondents": "US employer businesses", "company_size": "All sizes, reported by employee count", "geography": "US", "fieldwork": "Dec 14, 2025 – May 3, 2026", "headline_stat": "17–20%", "headline_label": "of US businesses used AI in any business function, Dec 2025–May 2026", "adoption_stage": "tried", "summary": "U.S. Census Bureau's Large Firms With at Least 20 Employees Biggest AI Users (America Counts story, Business Trends and Outlook Survey) (May 2026; n=Biweekly nationally representative BTOS panel (~1.2M firms sampled; ~20,000 responses per wave per Fed note), fielded Dec 14, 2025 – May 3, 2026) found that 17–20% of US businesses used AI in any business function, Dec 2025–May 2026.", "findings": [ "37% of firms with 250+ employees and 32% of firms with 100–249 employees reported using AI.", "AI use rose among firms with at least 20 employees since December but did not change significantly for firms under 20.", "In November 2025 the question changed from AI use 'in producing goods or services' to use 'in any business function,' raising measured rates." ], "trust": "high", "source_url": "https://www.census.gov/library/stories/2026/05/ai-use-businesses.html", "access": "free" }, { "id": "deltek-clarity-ae-2026", "url": "https://aiunite.org/reports/deltek-clarity-ae-2026/", "kind": "report", "title": "47th Annual Deltek Clarity Architecture & Engineering Industry Study", "publisher": "Deltek", "publisher_type": "Industry research & software", "published": "2026-05-12", "updated": "2026-09-29", "topics": [ "Professional services", "Adoption", "ROI & value" ], "method": "Benchmark", "sample_n": "896", "respondents": "Architecture and engineering firms", "company_size": "Mixed", "geography": "US + Canada", "fieldwork": null, "headline_stat": "38%", "headline_label": "of A&E firms report measurable positive business impact from AI", "adoption_stage": "pnl", "summary": "Deltek's 47th Annual Deltek Clarity Architecture & Engineering Industry Study (May 2026; n=896) found that 38% of A&E firms report measurable positive business impact from AI.", "findings": [ "AI adoption among A&E firms rose from 53% to 70% year over year; generative AI use rose from 64% to 78%.", "Only 38% report a measurable positive business impact from AI.", "Utilization declined to just under 60%, operating profit fell to 16.7%, and staff growth was only 1.2%." ], "trust": "medium", "source_url": "https://www.deltek.com/company/news/latest-deltek-clarity-industry-studies-highlight-ai-challenges/", "access": "gated" }, { "id": "deltek-clarity-govcon-2026", "url": "https://aiunite.org/reports/deltek-clarity-govcon-2026/", "kind": "report", "title": "17th Annual Deltek Clarity Government Contracting Industry Study", "publisher": "Deltek", "publisher_type": "Industry research & software", "published": "2026-05-12", "updated": "2026-09-29", "topics": [ "Adoption", "Strategy" ], "method": "Benchmark", "sample_n": "917", "respondents": "Government contractors", "company_size": "Mixed", "geography": "US + Canada", "fieldwork": null, "headline_stat": "5%", "headline_label": "of government contractors describe their AI maturity as fully developed", "adoption_stage": "core", "summary": "Deltek's 17th Annual Deltek Clarity Government Contracting Industry Study (May 2026; n=917) found that 5% of government contractors describe their AI maturity as fully developed.", "findings": [ "90% are using or planning to use AI in at least one business function in 2026.", "Only 5% report fully developed AI maturity, and 45% are unclear on AI's return on investment.", "Average revenue grew 15% in 2025, yet nearly 90% saw at least one declining financial metric." ], "trust": "medium", "source_url": "https://www.deltek.com/company/news/latest-deltek-clarity-industry-studies-highlight-ai-challenges/", "access": "gated" }, { "id": "microsoft-work-trend-index-2026", "url": "https://aiunite.org/reports/microsoft-work-trend-index-2026/", "kind": "report", "title": "2026 Work Trend Index: Agents, human agency, and the opportunity for every organization", "publisher": "Microsoft", "publisher_type": "Technology company", "published": "2026-05-05", "updated": "2026-09-29", "topics": [ "Workforce", "Agents" ], "method": "Worker survey", "sample_n": "20,000", "respondents": "Knowledge workers who already use AI at work (plus a separate 1,800-person manager study and Microsoft 365 telemetry)", "company_size": "Not specified", "geography": "10 markets incl. US, UK, Germany, Japan, India, Brazil", "fieldwork": "Feb 18–Apr 20, 2026", "headline_stat": "58%", "headline_label": "of AI users say they now produce work they couldn't a year ago", "adoption_stage": null, "summary": "Microsoft's 2026 Work Trend Index: Agents, human agency, and the opportunity for every organization (May 2026; n=20,000, fielded Feb 18 – Apr 7, 2026) found that 58% of AI users say they now produce work they couldn't a year ago.", "findings": [ "Only 19% of AI users work where individual capability and organizational readiness reinforce each other (Microsoft's 'Frontier' zone).", "Organizational factors such as culture and manager support account for more than twice the reported AI impact of individual effort.", "Active agents in Microsoft 365 grew 15x year over year, 18x in large enterprises." ], "trust": "low", "source_url": "https://www.microsoft.com/en-us/worklab/work-trend-index/agents-human-agency-and-the-opportunity-for-every-organization", "access": "free" }, { "id": "ibm-ibv-ceo-study-2026", "url": "https://aiunite.org/reports/ibm-ibv-ceo-study-2026/", "kind": "report", "title": "2026 CEO Study: 5 plays for AI-first transformation", "publisher": "IBM Institute for Business Value", "publisher_type": "Technology company", "published": "2026-05-04", "updated": "2026-09-29", "topics": [ "Strategy", "Workforce" ], "method": "Executive survey", "sample_n": "2,000", "respondents": "CEOs and equivalent senior leaders", "company_size": "Not specified in press release", "geography": "33 geographies, 21 industries", "fieldwork": "Feb–Apr 2026", "headline_stat": "25%", "headline_label": "of workers use AI regularly in their jobs, though 86% of CEOs think their people are ready", "adoption_stage": "tried", "summary": "IBM Institute for Business Value's 2026 CEO Study: 5 plays for AI-first transformation (May 2026; n=2,000, fielded Feb–Apr 2026) found that 25% of workers use AI regularly in their jobs, though 86% of CEOs think their people are ready.", "findings": [ "76% of organizations now have a Chief AI Officer, up from 26% a year earlier.", "Organizations that redesigned five core areas were four times more likely to achieve their AI objectives.", "CEOs expect 48% of operational decisions to be made by AI without human intervention by 2030." ], "trust": "medium", "source_url": "https://www.ibm.com/thought-leadership/institute-business-value/en-us/c-suite-study/ceo", "access": "gated" }, { "id": "grant-thornton-ai-impact-2026", "url": "https://aiunite.org/reports/grant-thornton-ai-impact-2026/", "kind": "report", "title": "2026 AI Impact Survey Report: The AI Proof Gap", "publisher": "Grant Thornton", "publisher_type": "Accounting & advisory", "published": "2026-04-13", "updated": "2026-09-29", "topics": [ "Governance & risk", "ROI & value", "Mid-market" ], "method": "Executive survey", "sample_n": "950", "respondents": "C-suite (CEO, CFO, COO, CIO/CTO) and leaders reporting to C-suite; mostly operations, finance and IT", "company_size": "Not specified", "geography": "US", "fieldwork": "Feb 23–Mar 18, 2026 (live interviews)", "headline_stat": "78%", "headline_label": "lack strong confidence they could pass an independent AI governance audit within 90 days", "adoption_stage": null, "summary": "Grant Thornton's 2026 AI Impact Survey Report: The AI Proof Gap (April 2026; n=950, fielded Feb 23–Mar 18, 2026 (live interviews)) found that 78% lack strong confidence they could pass an independent AI governance audit within 90 days.", "findings": [ "Organizations with fully integrated AI report revenue growth far more often than those still piloting: 58% vs 15%.", "51% name strategy as the biggest driver of AI ROI, but only 22% have a fully implemented enterprise AI strategy in operations.", "74% give agentic AI access to data and processes, yet only about one in five has a tested AI-failure response plan." ], "trust": "medium", "source_url": "https://www.grantthornton.com/services/advisory-services/artificial-intelligence/2026-ai-impact-survey", "access": "free" }, { "id": "stanford-hai-ai-index-2026", "url": "https://aiunite.org/reports/stanford-hai-ai-index-2026/", "kind": "report", "title": "The 2026 AI Index Report", "publisher": "Stanford HAI", "publisher_type": "University & nonprofit", "published": "2026-04-13", "updated": "2026-09-29", "topics": [ "Adoption", "Strategy" ], "method": "Data compilation", "sample_n": null, "respondents": "Compilation of third-party datasets and surveys", "company_size": "Varies by source", "geography": "Global", "fieldwork": "Data mostly through 2025, some to Mar 2026", "headline_stat": "88%", "headline_label": "of surveyed organizations report some form of AI adoption", "adoption_stage": "tried", "summary": "Stanford HAI's The 2026 AI Index Report (April 2026; fielded Data mostly through 2025, some to Mar 2026) found that 88% of surveyed organizations report some form of AI adoption.", "findings": [ "Global corporate AI investment reached $581.7 billion in 2025, up about 130% from the prior year.", "About 70% of organizations use generative AI in at least one business function; AI agent deployment is in single digits across most functions.", "Employment among software developers aged 22–25 fell nearly 20% since 2024, per the report's labor chapter." ], "trust": "high", "source_url": "https://hai.stanford.edu/ai-index/2026-ai-index-report", "access": "free" }, { "id": "fed-feds-note-monitoring-ai-adoption-2026", "url": "https://aiunite.org/reports/fed-feds-note-monitoring-ai-adoption-2026/", "kind": "report", "title": "Monitoring AI Adoption in the U.S. Economy (FEDS Notes)", "publisher": "Federal Reserve Board", "publisher_type": "Government & central bank", "published": "2026-04-03", "updated": "2026-09-29", "topics": [ "Adoption" ], "method": "Analysis", "sample_n": "BTOS ~20,000 firms per wave; RPS ~5,000–6,000 people per wave; SBU 1,032 (Nov 2025)", "respondents": "Firms (Census BTOS), workers (Real-Time Population Survey), executives (Atlanta Fed SBU)", "company_size": "All sizes", "geography": "US", "fieldwork": "Through year-end 2025", "headline_stat": "~18%", "headline_label": "of US firms had adopted AI as of year-end 2025 (Census BTOS, firm-weighted)", "adoption_stage": "tried", "summary": "Federal Reserve Board's Monitoring AI Adoption in the U.S. Economy (FEDS Notes) (April 2026; n=BTOS ~20,000 firms per wave; RPS ~5,000–6,000 people per wave; SBU 1,032 (Nov 2025), fielded Through year-end 2025) found that ~18% of US firms had adopted AI as of year-end 2025 (Census BTOS, firm-weighted).", "findings": [ "About 78% of the labor force works at firms that have adopted AI (SBU, employment-weighted), and about 54% at firms using LLMs.", "Work-related generative AI adoption among workers was about 41% in November 2025; about 12% use it daily at work.", "Adoption estimates differ widely by survey and weighting; finance and professional services lead across measures." ], "trust": "high", "source_url": "https://www.federalreserve.gov/econres/notes/feds-notes/monitoring-ai-adoption-in-the-u-s-economy-20260403.html", "access": "free" }, { "id": "atlanta-fed-cfo-survey-ai-2026", "url": "https://aiunite.org/reports/atlanta-fed-cfo-survey-ai-2026/", "kind": "report", "title": "How Might AI Change the Workplace? Evidence from Corporate Executives (Policy Hub: Macroblog)", "publisher": "Federal Reserve Bank of Atlanta", "publisher_type": "Government & central bank", "published": "2026-03-25", "updated": "2026-09-29", "topics": [ "Adoption", "ROI & value" ], "method": "Executive survey", "sample_n": "748", "respondents": "CFOs and financial executives (The CFO Survey panel, plus FEI/Nasdaq members and Duke alumni)", "company_size": "Mixed; results split by large vs smaller firms", "geography": "US", "fieldwork": "Nov 11 – Dec 16, 2025 (main); supplemental Dec 2025 – Jan 2026", "headline_stat": "~60%", "headline_label": "of responding firms invested in AI in 2025 (about 80% of large firms)", "adoption_stage": "approved", "summary": "Federal Reserve Bank of Atlanta's How Might AI Change the Workplace? Evidence from Corporate Executives (Policy Hub: Macroblog) (March 2026; n=748, fielded Nov 11 – Dec 16, 2025 (main); supplemental Dec 2025 – Jan 2026) found that ~60% of responding firms invested in AI in 2025 (about 80% of large firms).", "findings": [ "More than 80% of firms expect to invest in AI in 2026; about 30% of large firms expect to spend over $1 million.", "Firms reported negligible AI-driven employment changes in 2025; expected 2026 effects are near zero overall, about -0.8% at large firms.", "Firms reported roughly 1.8% productivity gains in 2025, though revenue-based measures showed substantially smaller effects." ], "trust": "high", "source_url": "https://www.atlantafed.org/research-and-data/publications/policy-hub-macroblog/2026/03/25/how-might-ai-change-the-workplace-evidence-from-corporate-executives", "access": "free" }, { "id": "promethean-sods-2026", "url": "https://aiunite.org/reports/promethean-sods-2026/", "kind": "report", "title": "State of Digital Services 2026: An Uneven Return to Form", "publisher": "Promethean Research", "publisher_type": "Industry research & software", "published": "2026-03-19", "updated": "2026-09-29", "topics": [ "Professional services", "Strategy" ], "method": "Benchmark", "sample_n": "119", "respondents": "Digital agency owners and managers", "company_size": "Average 31 FTE; median 13 FTE", "geography": "74% US, 12% Canada, 14% other", "fieldwork": "February 2026", "headline_stat": "About 1 in 3", "headline_label": "digital agencies have implemented AI across their business", "adoption_stage": "core", "summary": "Promethean Research's State of Digital Services 2026: An Uneven Return to Form (March 2026; n=119, fielded February 2026) found that About 1 in 3 digital agencies have implemented AI across their business.", "findings": [ "Average digital agency revenue grew 7.5% in 2025, with large agencies rebounding and small agencies growing slowest.", "Net margins declined to 13%, and revenue per full-time employee fell for the first time in years.", "About a third of agencies have implemented AI across their businesses, with another 28% implementing; copywriting and coding lead." ], "trust": "medium", "source_url": "https://research.prometheanresearch.com/products/state-of-digital-services-2026-an-uneven-return-to-form", "access": "paid" }, { "id": "spi-ps-maturity-2026", "url": "https://aiunite.org/reports/spi-ps-maturity-2026/", "kind": "report", "title": "2026 Professional Services Maturity Benchmark", "publisher": "SPI Research", "publisher_type": "Industry research & software", "published": "2026-02-24", "updated": "2026-09-29", "topics": [ "Professional services", "ROI & value" ], "method": "Benchmark", "sample_n": "509", "respondents": "Professional services organizations (245,000+ consultants, ~$63B PS revenue)", "company_size": "Mixed; not limited to mid-market", "geography": "Global", "fieldwork": "2025 performance year", "headline_stat": "66.4%", "headline_label": "billable utilization in 2025, the lowest in SPI's 19-year history", "adoption_stage": null, "summary": "SPI Research's 2026 Professional Services Maturity Benchmark (February 2026; n=509, fielded 2025 performance year) found that 66.4% billable utilization in 2025, the lowest in SPI's 19-year history.", "findings": [ "Billable utilization fell to 66.4% in 2025, the lowest in the benchmark's history and below SPI's 70–75% targets.", "About 27% of projects used generative AI in 2025, roughly a 40% increase over the prior year; 40% of firms offer AI services.", "Average PS revenue growth was 5.2% with headcount growth of 2.8%." ], "trust": "medium", "source_url": "https://spiresearch.com/reports/2026-ps-maturity-benchmark/", "access": "paid" }, { "id": "stthomas-northstar-genai-mn-jobs-2026", "url": "https://aiunite.org/reports/stthomas-northstar-genai-mn-jobs-2026/", "kind": "report", "title": "The Highest Worker Exposure in the Midwest: The Impact of Generative AI on the Minnesota Job Market", "publisher": "North Star Policy Action & University of St. Thomas", "publisher_type": "University & nonprofit", "published": "2026-02-24", "updated": "2026-09-29", "topics": [ "Minnesota & Midwest", "Workforce" ], "method": "Labor data", "sample_n": null, "respondents": "Occupation-level exposure model (O*NET 27.2 tasks, Eloundou et al./Brookings scores) applied to BLS May 2024 and ACS 2023 employment", "company_size": "n/a", "geography": "Minnesota, compared with other states", "fieldwork": "n/a (modeled)", "headline_stat": "31.3%", "headline_label": "of Minnesota workers (800,000+) are in jobs with high exposure to generative AI", "adoption_stage": null, "summary": "North Star Policy Action & University of St. Thomas's The Highest Worker Exposure in the Midwest: The Impact of Generative AI on the Minnesota Job Market (February 2026; fielded n/a (modeled)) found that 31.3% of Minnesota workers (800,000+) are in jobs with high exposure to generative AI.", "findings": [ "High exposure means half or more of a worker's tasks could be partly or wholly done by GenAI; exposure may mean supplementing, not replacing, jobs.", "Minnesota has the highest GenAI exposure rate in the Midwest and the 10th highest nationally.", "About 79% of Minnesota finance-industry workers are highly exposed, versus 33% in manufacturing and 28% in education." ], "trust": "medium", "source_url": "https://northstarpolicy.org/generative-ai/", "access": "free" }, { "id": "caqh-index-2025", "url": "https://aiunite.org/reports/caqh-index-2025/", "kind": "report", "title": "2025 CAQH Index", "publisher": "CAQH (DataSpring)", "publisher_type": "University & nonprofit", "published": "2026-02-19", "updated": "2026-09-29", "topics": [ "Adoption" ], "method": "Data compilation", "sample_n": null, "respondents": "Transaction data from 600+ provider organizations and health plans", "company_size": "Covers 63% of insured lives", "geography": "US", "fieldwork": "2024 transaction year", "headline_stat": "25%", "headline_label": "of provider organizations use AI tools in administrative workflows (vs. 50%+ of health plans)", "adoption_stage": "approved", "summary": "CAQH (DataSpring)'s 2025 CAQH Index (February 2026; fielded 2024 transaction year) found that 25% of provider organizations use AI tools in administrative workflows (vs. 50%+ of health plans).", "findings": [ "U.S. healthcare avoided an estimated $258 billion in administrative costs in 2024 through electronic transactions, a 17% increase in cost avoidance.", "A further $21 billion savings opportunity remains from fully automating manual and partially manual transactions.", "More than 50% of health plans and 25% of provider organizations use AI tools in administrative workflows." ], "trust": "high", "source_url": "https://www.dataspring.com/blog/2025-caqh-index-shows-u.s.-healthcare-avoided-258-billion-and-accelerated-automation-interoperability-and-ai-adoption", "access": "free" }, { "id": "tr-ai-ps-2026", "url": "https://aiunite.org/reports/tr-ai-ps-2026/", "kind": "report", "title": "2026 AI in Professional Services Report", "publisher": "Thomson Reuters Institute", "publisher_type": "Technology company", "published": "2026-02-09", "updated": "2026-09-29", "topics": [ "Professional services", "Adoption", "ROI & value" ], "method": "Mixed survey", "sample_n": "1,514", "respondents": "Legal, tax/accounting, corporate risk and government professionals familiar with AI", "company_size": "Quotas across firm and department sizes", "geography": "27 countries (39% US, 18% UK, 13% Canada)", "fieldwork": "Oct–Nov 2025", "headline_stat": "40%", "headline_label": "of professionals say their organization uses GenAI, up from 22% a year earlier", "adoption_stage": "approved", "summary": "Thomson Reuters Institute's 2026 AI in Professional Services Report (February 2026; n=1,514, fielded Oct–Nov 2025) found that 40% of professionals say their organization uses GenAI, up from 22% a year earlier.", "findings": [ "Organizational GenAI use nearly doubled to 40%, up from 22% the prior year.", "Only 18% say their organization tracks ROI of AI tools.", "15% of organizations use agentic AI; another 53% are planning or considering it." ], "trust": "high", "source_url": "https://www.thomsonreuters.com/en/institute/reports/2026-ai-in-professional-services-report", "access": "free" }, { "id": "nber-firm-data-on-ai-2026", "url": "https://aiunite.org/reports/nber-firm-data-on-ai-2026/", "kind": "report", "title": "Firm Data on AI (NBER Working Paper 34836)", "publisher": "National Bureau of Economic Research", "publisher_type": "University & nonprofit", "published": "2026-02", "updated": "2026-09-29", "topics": [ "Productivity", "Workforce", "Adoption" ], "method": "Executive survey", "sample_n": "Nearly 6,000 firms", "respondents": "Senior executives (mostly CEOs, CFOs and senior finance managers) in central-bank business panels: Atlanta Fed SBU, Bank of England DMP, Bundesbank BOP-F, Macquarie BOSS; plus a U.S. employee survey", "company_size": "Broadly representative of firms in each country", "geography": "US, UK, Germany, Australia", "fieldwork": "Nov 2025 – Jan 2026 (UK questions also Feb 2025 onward)", "headline_stat": "89%", "headline_label": "of executives report no AI impact on their firm's labor productivity over the past three years", "adoption_stage": "n/a", "summary": "NBER's Firm Data on AI (February 2026, revised March 2026; nearly 6,000 executives in the U.S., UK, Germany and Australia, executive survey) found that 69% of firms use AI but more than 90% report no impact on their employment and 89% no impact on productivity over the past three years.", "findings": [ "69% of firms across the four countries actively use AI, from 78% in the U.S. to 59% in Australia.", "More than 90% of executives report no impact of AI on own-firm employment over the past three years.", "89% report no impact on labor productivity, measured as sales per employee, over the past three years.", "Executives expect AI to raise productivity 1.4% and cut employment 0.7% at their firms over the next three years.", "More than two-thirds of executives use AI themselves, averaging 1.5 hours a week." ], "trust": "high", "source_url": "https://www.nber.org/papers/w34836", "access": "free" }, { "id": "nber-genai-education-productivity-gaps-2026", "url": "https://aiunite.org/reports/nber-genai-education-productivity-gaps-2026/", "kind": "report", "title": "Does Generative AI Narrow Education-Based Productivity Gaps? Evidence from a Randomized Experiment", "publisher": "National Bureau of Economic Research", "publisher_type": "University & nonprofit", "published": "2026-02", "updated": "2026-09-29", "topics": [ "Productivity", "Workforce" ], "method": "Experiment", "sample_n": "1,174", "respondents": "Adults aged 25–45 with high school or postsecondary education, doing an incentivized business problem-solving task", "company_size": null, "geography": "Argentina", "fieldwork": null, "headline_stat": "75%", "headline_label": "of the education-based performance gap closed with AI access", "adoption_stage": "n/a", "summary": "NBER's Does Generative AI Narrow Education-Based Productivity Gaps? (February 2026; n=1,174 adults, randomized experiment) found that access to a GPT-4.1 assistant closed three-quarters of the performance gap between higher- and lower-education participants on a business task.", "findings": [ "AI access raised task scores by 1.242 standard deviations for lower-education participants and 0.834 for higher-education participants.", "Without AI, higher-education participants outscored lower-education ones by 0.548 SD; with AI, the gap fell to 0.139 SD, closing 75% of it.", "AI cut completion time by 1.514 minutes for higher-education participants against a 10.423-minute control average, and by 0.961 minutes for lower-education participants against 10.697.", "In a follow-up without AI, lower-education participants who had used AI scored 0.171 SD higher than controls.", "About 13% of control-group participants appear to have used AI anyway." ], "trust": "high", "source_url": "https://www.nber.org/papers/w34851", "access": "free" }, { "id": "schwab-ria-ai-2026", "url": "https://aiunite.org/reports/schwab-ria-ai-2026/", "kind": "report", "title": "2026 RIA & AI Research Study: Advisor AI in Action", "publisher": "Charles Schwab", "publisher_type": "Financial institution", "published": "2026-01-22", "updated": "2026-09-29", "topics": [ "Professional services", "Adoption" ], "method": "Mixed survey", "sample_n": "533", "respondents": "Independent RIA advisors who custody at Schwab (conducted by Logica Research)", "company_size": null, "geography": "US", "fieldwork": "Oct 7–26, 2025", "headline_stat": "~10%", "headline_label": "of advisors using AI have fully integrated it into their business strategy", "adoption_stage": "core", "summary": "Charles Schwab's 2026 RIA & AI Research Study: Advisor AI in Action (January 2026; n=533, fielded Oct 7–26, 2025) found that ~10% of advisors using AI have fully integrated it into their business strategy.", "findings": [ "63% of RIAs now use AI tools in some capacity, and 82% of those users rely on generative AI.", "About 10% of advisors using AI have fully integrated it into their business strategy.", "68% expect AI to be transformative to financial advice within three years." ], "trust": "medium", "source_url": "https://pressroom.aboutschwab.com/press-releases/press-release/2026/Schwab-Study-Reveals-RIA-AI-Adoption-More-Than-Doubles---But-Most-Firms-Still-in-Early-Stages/default.aspx", "access": "free" }, { "id": "deloitte-state-of-ai-enterprise-2026", "url": "https://aiunite.org/reports/deloitte-state-of-ai-enterprise-2026/", "kind": "report", "title": "The State of AI in the Enterprise 2026: The untapped edge", "publisher": "Deloitte", "publisher_type": "Accounting & advisory", "published": "2026-01-21", "updated": "2026-09-29", "topics": [ "Strategy", "ROI & value", "Governance & risk", "Agents" ], "method": "Executive survey", "sample_n": "3,235", "respondents": "Director to board/C-suite leaders, split equally IT and line of business", "company_size": "Not specified on page (organizations 'on the leading edge of AI')", "geography": "24 countries", "fieldwork": "Aug–Sep 2025", "headline_stat": "20%", "headline_label": "are already growing revenue through AI, versus 74% who hope to", "adoption_stage": "pnl", "summary": "Deloitte's The State of AI in the Enterprise 2026: The untapped edge (January 2026; n=3,235, fielded Aug–Sep 2025) found that 20% are already growing revenue through AI, versus 74% who hope to.", "findings": [ "34% are using AI to deeply transform the business; 30% are redesigning key processes; 37% use AI at a surface level.", "Worker access to AI rose 50% in 2025; the AI skills gap is seen as the biggest barrier to integration.", "Only about one in five companies has a mature governance model for autonomous AI agents." ], "trust": "medium", "source_url": "https://www.deloitte.com/us/en/what-we-do/capabilities/applied-artificial-intelligence/content/state-of-ai-in-the-enterprise.html", "access": "gated" }, { "id": "ey-parthenon-ceo-outlook-jan-2026", "url": "https://aiunite.org/reports/ey-parthenon-ceo-outlook-jan-2026/", "kind": "report", "title": "EY-Parthenon CEO Outlook Survey (January 2026)", "publisher": "EY-Parthenon", "publisher_type": "Accounting & advisory", "published": "2026-01-20", "updated": "2026-09-29", "topics": [ "Strategy" ], "method": "Executive survey", "sample_n": "1,200", "respondents": "CEOs of large companies", "company_size": "20% <$500M; 21% $500M–$1B; 29% $1B–$5B; 30% >$5B", "geography": "21 countries", "fieldwork": "Nov–Dec 2025", "headline_stat": "24%", "headline_label": "of CEOs expect AI investment to reduce headcount, down from 46% in January 2025", "adoption_stage": null, "summary": "EY-Parthenon's EY-Parthenon CEO Outlook Survey (January 2026) (January 2026; n=1,200, fielded Nov–Dec 2025) found that 24% of CEOs expect AI investment to reduce headcount, down from 46% in January 2025.", "findings": [ "58% expect AI to be a major growth engine in the next two years; 32% expect it to fundamentally reshape operations.", "Only 20% say AI significantly exceeded expectations over the last year.", "69% believe AI investments will lead them to maintain employment or hire new talent over the coming year." ], "trust": "medium", "source_url": "https://www.ey.com/en_gl/newsroom/2026/01/ceos-double-down-on-ai-transformation-and-m-and-a-to-drive-growth-amid-uncertainty-in-the-global-economy", "access": "free" }, { "id": "karbon-ai-accounting-2026", "url": "https://aiunite.org/reports/karbon-ai-accounting-2026/", "kind": "report", "title": "State of AI in Accounting Report 2026", "publisher": "Karbon", "publisher_type": "Industry research & software", "published": "2026-01-20", "updated": "2026-09-29", "topics": [ "Professional services", "Governance & risk" ], "method": "Mixed survey", "sample_n": "~600", "respondents": "Accounting professionals", "company_size": "Mixed firm sizes", "geography": "Global (six continents)", "fieldwork": null, "headline_stat": "21%", "headline_label": "of accounting firms have a documented AI policy or strategy", "adoption_stage": "approved", "summary": "Karbon's State of AI in Accounting Report 2026 (January 2026; n=~600) found that 21% of accounting firms have a documented AI policy or strategy.", "findings": [ "98% of firms now use AI, with most using it daily or several times a day.", "Only 21% of firms have a documented AI policy or strategy, and fewer than half invest in AI training.", "Firms investing in training, policies and documented strategy report greater time savings and higher confidence in AI use." ], "trust": "low", "source_url": "https://karbonhq.com/resources/state-of-ai-accounting-2026/", "access": "gated" }, { "id": "pwc-global-ceo-survey-2026", "url": "https://aiunite.org/reports/pwc-global-ceo-survey-2026/", "kind": "report", "title": "29th Annual Global CEO Survey: Leading through uncertainty in the age of AI", "publisher": "PwC", "publisher_type": "Accounting & advisory", "published": "2026-01-19", "updated": "2026-09-29", "topics": [ "ROI & value", "Strategy", "Mid-market" ], "method": "Executive survey", "sample_n": "4,454", "respondents": "CEOs", "company_size": "30% up to $100M revenue; 35% $100M–$1B; 28% $1B–$10B; 6% $10B+", "geography": "95 countries and territories (GDP-weighted)", "fieldwork": "Sep 30–Nov 10, 2025", "headline_stat": "56%", "headline_label": "of CEOs say AI delivered neither higher revenue nor lower costs in the past 12 months", "adoption_stage": "pnl", "summary": "PwC's 29th Annual Global CEO Survey: Leading through uncertainty in the age of AI (January 2026; n=4,454, fielded Sep 30–Nov 10, 2025) found that 56% of CEOs say AI delivered neither higher revenue nor lower costs in the past 12 months.", "findings": [ "Only 12% of CEOs report AI delivered both revenue gains and cost reductions.", "30% report increased revenue from AI; 26% report lower costs, while 22% say costs went up.", "Only 30% are very or extremely confident about revenue growth over the next 12 months, down from 38% in 2025." ], "trust": "high", "source_url": "https://www.pwc.com/gx/en/ceo-survey/2026/pwc-ceo-survey-2026.pdf", "access": "free" }, { "id": "hinge-high-growth-2026", "url": "https://aiunite.org/reports/hinge-high-growth-2026/", "kind": "report", "title": "2026 High Growth Study", "publisher": "Hinge Research Institute", "publisher_type": "Industry research & software", "published": "2026-01-13", "updated": "2026-09-29", "topics": [ "Professional services", "Strategy" ], "method": "Benchmark", "sample_n": "495", "respondents": "Professional services firms (AEC, consulting, technology, accounting and others)", "company_size": "Mixed; ~$85B combined revenue", "geography": "Global (six continents)", "fieldwork": null, "headline_stat": "Nearly 1 in 3", "headline_label": "firms believe AI is disrupting their businesses", "adoption_stage": null, "summary": "Hinge Research Institute's 2026 High Growth Study (January 2026; n=495) found that Nearly 1 in 3 firms believe AI is disrupting their businesses.", "findings": [ "Median growth for professional services firms cooled to 9.9%, the lowest since 2018.", "High Growth firms' interest in AI jumped 63%, with 85.2% naming it a top priority for further study.", "High Growth firms spend about 12% of revenue on marketing versus 5% for non-growth firms." ], "trust": "medium", "source_url": "https://hingemarketing.com/blog/story/5-key-takeaways-from-the-2026-high-growth-study", "access": "gated" }, { "id": "kantata-state-ps-2026", "url": "https://aiunite.org/reports/kantata-state-ps-2026/", "kind": "report", "title": "State of the Professional Services Industry Report (AI agents survey)", "publisher": "Kantata", "publisher_type": "Industry research & software", "published": "2026-01-08", "updated": "2026-09-29", "topics": [ "Professional services", "Agents", "Workforce" ], "method": "Executive survey", "sample_n": "200", "respondents": "Professional services business leaders (survey by Censuswide)", "company_size": null, "geography": "US", "fieldwork": "August 2025 (per trade coverage)", "headline_stat": "87%", "headline_label": "of PS organizations plan to use AI agents as part of their workforce", "adoption_stage": null, "summary": "Kantata's State of the Professional Services Industry Report (AI agents survey) (January 2026; n=200, fielded August 2025 (per trade coverage)) found that 87% of PS organizations plan to use AI agents as part of their workforce.", "findings": [ "89% agree future revenue growth will depend more on scaling AI than scaling headcount.", "66% have turned down work due to resourcing constraints; 68% cite skill availability as a barrier.", "Only 12% fully trust the data in their systems, down from 24% the prior year." ], "trust": "low", "source_url": "https://www.kantata.com/blog/article/kantata-survey-reveals-that-87-of-professional-services-teams-plan-to-manage-ai-agents-as-part-of-their-workforce", "access": "gated" }, { "id": "soda-agency-outlook-2026", "url": "https://aiunite.org/reports/soda-agency-outlook-2026/", "kind": "report", "title": "Agency Outlook Study '26", "publisher": "SoDA", "publisher_type": "University & nonprofit", "published": "2026-01", "updated": "2026-09-29", "topics": [ "Professional services", "Strategy" ], "method": "Executive survey", "sample_n": "251", "respondents": "Agency leaders (54% founder/owner/partner, 22% CEO/president/MD)", "company_size": "21% $10–25M, 10% $25–50M, 5% $50–100M revenue; 58% under $10M", "geography": "62% US, 25% Europe", "fieldwork": "Q4 2025", "headline_stat": "39%", "headline_label": "of agencies say clients already expect lower prices because of AI", "adoption_stage": null, "summary": "SoDA's Agency Outlook Study '26 (January 2026; n=251, fielded Q4 2025) found that 39% of agencies say clients already expect lower prices because of AI.", "findings": [ "81% of agencies use AI for creative ideation and 76% to automate or accelerate routine operational tasks.", "39% say clients already expect lower prices due to AI; 45% say clients want help with AI strategy and implementation.", "35% are rethinking pricing and commercial models around AI; 71% agree AI will change the number and types of roles they employ." ], "trust": "medium", "source_url": "https://www.sodaspeaks.com/research", "access": "free" }, { "id": "menlo-state-genai-enterprise-2025", "url": "https://aiunite.org/reports/menlo-state-genai-enterprise-2025/", "kind": "report", "title": "2025: The State of Generative AI in the Enterprise", "publisher": "Menlo Ventures", "publisher_type": "Financial institution", "published": "2025-12-09", "updated": "2026-09-29", "topics": [ "Spending & investment", "Strategy" ], "method": "Executive survey", "sample_n": "495", "respondents": "U.S. enterprise AI decision-makers, plus a bottoms-up market model of model APIs, infrastructure and applications", "company_size": "Enterprise", "geography": "US", "fieldwork": "Nov 7–25, 2025", "headline_stat": "$37B", "headline_label": "estimated enterprise spend on generative AI in 2025, up from $11.5B in 2024", "adoption_stage": "n/a", "summary": "Menlo Ventures' 2025: The State of Generative AI in the Enterprise (December 2025; n=495 U.S. enterprise AI decision-makers plus a market model) found that companies spent $37 billion on generative AI in 2025, up from $11.5 billion in 2024.", "findings": [ "Companies spent an estimated $37 billion on generative AI in 2025, up from $11.5 billion in 2024.", "The application layer took $19 billion and the infrastructure layer $18 billion.", "Anthropic earned 40% of enterprise LLM spend, OpenAI 27% and Google 21%.", "Coding was the largest departmental use at $4.0 billion, 55% of departmental AI spend.", "76% of AI use cases were purchased rather than built internally, and 47% of AI deals went to production versus 25% for traditional SaaS." ], "trust": "medium", "source_url": "https://menlovc.com/perspective/2025-the-state-of-generative-ai-in-the-enterprise/", "access": "free" }, { "id": "openai-state-of-enterprise-ai-2025", "url": "https://aiunite.org/reports/openai-state-of-enterprise-ai-2025/", "kind": "report", "title": "The State of Enterprise AI: 2025 Report", "publisher": "OpenAI", "publisher_type": "Technology company", "published": "2025-12-08", "updated": "2026-09-29", "topics": [ "Workforce", "Adoption" ], "method": "Usage data", "sample_n": "9,000 workers (survey) across ~100 enterprises; plus usage data from enterprise customers", "respondents": "Workers at OpenAI enterprise customers", "company_size": "Enterprise", "geography": "Not specified", "fieldwork": "2025", "headline_stat": "40–60 min", "headline_label": "of time saved per active day, as reported by enterprise ChatGPT users", "adoption_stage": null, "summary": "OpenAI's The State of Enterprise AI: 2025 Report (December 2025; n=9,000 workers (survey) across ~100 enterprises; plus usage data from enterprise customers, fielded 2025) found that 40–60 min of time saved per active day, as reported by enterprise ChatGPT users.", "findings": [ "ChatGPT Enterprise message volume grew 8x and API reasoning token use per organization rose about 320x year over year.", "75% of surveyed workers say AI improved the speed or quality of their output.", "Frontier workers send 6x more messages than the median; frontier firms send 2x as many messages per seat." ], "trust": "low", "source_url": "https://openai.com/index/the-state-of-enterprise-ai-2025-report/", "access": "free" }, { "id": "spi-ai-ps-2025", "url": "https://aiunite.org/reports/spi-ai-ps-2025/", "kind": "report", "title": "2025 Impact of AI on Professional Services Benchmark", "publisher": "SPI Research", "publisher_type": "Industry research & software", "published": "2025-12-02", "updated": "2026-09-29", "topics": [ "Professional services", "Adoption" ], "method": "Benchmark", "sample_n": "146", "respondents": "Professional services and embedded services organizations (PSOs and ESOs)", "company_size": "Mixed", "geography": "Global", "fieldwork": null, "headline_stat": "1 in 10", "headline_label": "PS firms attempting truly transformational AI", "adoption_stage": "core", "summary": "SPI Research's 2025 Impact of AI on Professional Services Benchmark (December 2025; n=146) found that 1 in 10 PS firms attempting truly transformational AI.", "findings": [ "Only one in ten professional services firms are attempting truly transformational AI.", "Only 40% of consultants and employees can use AI today.", "Firms expect revenue generated from AI initiatives to triple within three years." ], "trust": "medium", "source_url": "https://spiresearch.com/reports/the-2025-impact-of-ai-on-professional-services/", "access": "paid" }, { "id": "anthropic-productivity-gains-2025", "url": "https://aiunite.org/reports/anthropic-productivity-gains-2025/", "kind": "report", "title": "Estimating AI Productivity Gains from Claude Conversations", "publisher": "Anthropic", "publisher_type": "Technology company", "published": "2025-11-25", "updated": "2026-09-29", "topics": [ "Productivity" ], "method": "Usage data", "sample_n": "100,000 conversations", "respondents": "Claude.ai Free, Pro, and Max conversations, analyzed with a privacy-preserving system", "company_size": null, "geography": null, "fieldwork": null, "headline_stat": "~80%", "headline_label": "estimated reduction in task time with Claude", "adoption_stage": "n/a", "summary": "Anthropic's Estimating AI Productivity Gains from Claude Conversations (November 2025; n=100,000 conversations, model-estimated usage data) found that Claude estimated AI cut task completion time by about 80%, implying a 1.8% annual boost to US labor productivity growth if applied economy-wide.", "findings": [ "Claude estimated that AI cut task completion time by about 80%; the median conversation showed an estimated 84% time savings.", "Tasks brought to Claude would take about 1.4 hours on average without AI, worth an estimated $55 in human labor.", "Savings varied by task: about 90% for healthcare assistance tasks versus 56% for hardware issues, and 20% for checking diagnostic images.", "Extrapolated economy-wide, the estimates imply a 1.8% annual increase in US labor productivity growth over the next decade.", "Software developers account for 19% of the implied productivity gain, followed by general and operations managers (about 6%) and marketing specialists (5%)." ], "trust": "medium", "source_url": "https://www.anthropic.com/research/estimating-productivity-gains", "access": "free" }, { "id": "mckinsey-state-of-ai-2025", "url": "https://aiunite.org/reports/mckinsey-state-of-ai-2025/", "kind": "report", "title": "The state of AI in 2025: Agents, innovation, and transformation", "publisher": "McKinsey & Company", "publisher_type": "Consultancy", "published": "2025-11-05", "updated": "2026-09-29", "topics": [ "Adoption", "ROI & value", "Agents" ], "method": "Mixed survey", "sample_n": "1,993", "respondents": "Online survey respondents at all levels, functions and tenures", "company_size": "Full range; 38% at organizations with >$1B revenue", "geography": "105 nations (weighted by GDP)", "fieldwork": "Jun 25–Jul 29, 2025", "headline_stat": "88%", "headline_label": "report regular AI use in at least one business function (up from 78%)", "adoption_stage": "tried", "summary": "McKinsey & Company's The state of AI in 2025: Agents, innovation, and transformation (November 2025; n=1,993, fielded Jun 25–Jul 29, 2025) found that 88% report regular AI use in at least one business function (up from 78%).", "findings": [ "Nearly two-thirds say their organizations have not yet begun scaling AI across the enterprise.", "62% are at least experimenting with AI agents; 23% report scaling an agentic system somewhere in the enterprise.", "39% attribute any EBIT impact to AI; most of those say it is under 5% of EBIT. About 6% qualify as high performers." ], "trust": "medium", "source_url": "https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai-2025", "access": "free" }, { "id": "remote-labor-index-2025", "url": "https://aiunite.org/reports/remote-labor-index-2025/", "kind": "report", "title": "Remote Labor Index: Measuring AI Automation of Remote Work", "publisher": "Center for AI Safety", "publisher_type": "University & nonprofit", "published": "2025-10-30", "updated": "2026-09-29", "topics": [ "Agents", "Productivity", "Workforce" ], "method": "Benchmark", "sample_n": "240 projects", "respondents": "Real freelance projects commissioned from 358 verified Upwork freelancers; AI output graded by trained evaluators against the human deliverable", "company_size": null, "geography": "Global (online freelance work)", "fieldwork": "2025", "headline_stat": "2.5%", "headline_label": "of real freelance projects completed acceptably by the best AI agent tested", "adoption_stage": "n/a", "summary": "The Center for AI Safety and Scale AI's Remote Labor Index (October 2025; 240 real freelance projects, benchmark) found that the best AI agent tested completed only 2.5% of projects at a quality a reasonable client would accept.", "findings": [ "The best-performing agent, Manus, reached an automation rate of 2.5%; Grok 4 and Claude Sonnet 4.5 each reached 2.1%, GPT-5 1.7%, ChatGPT agent 1.3%, and Gemini 2.5 Pro 0.8%.", "The 240 projects span 23 Upwork work categories and represent over 6,000 hours of human work valued at over $140,000.", "Projects took human freelancers a mean of 28.9 hours (median 11.5) and cost a mean of $632.60 (median $200).", "45.6% of AI deliverables were rated poor quality, 35.7% incomplete, 17.6% had corrupted or unusable files, and 14.8% had inconsistencies.", "AI did comparably well on a narrow set of work: audio editing and mixing, image generation, report writing, and code for interactive data visualizations." ], "trust": "high", "source_url": "https://www.remotelabor.ai/", "access": "free" }, { "id": "clio-legal-trends-2025", "url": "https://aiunite.org/reports/clio-legal-trends-2025/", "kind": "report", "title": "2025 Legal Trends Report", "publisher": "Clio", "publisher_type": "Industry research & software", "published": "2025-10-16", "updated": "2026-09-29", "topics": [ "Professional services", "ROI & value" ], "method": "Usage data", "sample_n": null, "respondents": "Aggregated Clio platform data plus survey and a neuroscience study of 63 legal professionals", "company_size": "Mostly solo, small and mid-sized law firms", "geography": null, "fieldwork": null, "headline_stat": "Nearly 3x", "headline_label": "firms with wide AI adoption are more likely to report revenue growth than non-adopters", "adoption_stage": "pnl", "summary": "Clio's 2025 Legal Trends Report (October 2025) found that Nearly 3x firms with wide AI adoption are more likely to report revenue growth than non-adopters.", "findings": [ "Firms with wide AI adoption are nearly three times more likely to report revenue growth than firms that have not adopted AI.", "77% of firms that grew revenue with AI credited operational improvements such as document generation, workflows and client communication.", "In a 63-person neuroscience study, technology-assisted tasks cut overall cognitive load by 25%." ], "trust": "medium", "source_url": "https://www.clio.com/resources/legal-trends/read-online/", "access": "free" }, { "id": "air-street-state-of-ai-2025", "url": "https://aiunite.org/reports/air-street-state-of-ai-2025/", "kind": "report", "title": "State of AI Report 2025", "publisher": "Air Street Capital", "publisher_type": "Industry research & software", "published": "2025-10-09", "updated": "2026-09-29", "topics": [ "Adoption", "Strategy" ], "method": "Data compilation", "sample_n": "1,200 (practitioner survey component)", "respondents": "AI practitioners (survey); plus third-party data such as Ramp spend data", "company_size": "Varies", "geography": "Global; business-spend data US", "fieldwork": "2025", "headline_stat": "44%", "headline_label": "of US businesses now pay for AI tools, up from 5% in 2023 (Ramp data)", "adoption_stage": "approved", "summary": "Air Street Capital's State of AI Report 2025 (October 2025; n=1,200 (practitioner survey component), fielded 2025) found that 44% of US businesses now pay for AI tools, up from 5% in 2023 (Ramp data).", "findings": [ "Average contract value for AI products hit $530k in 2025 and is expected to pass $1M in 2026.", "Twelve-month retention for AI products is now 80%+, and AI-first companies grew 1.5x faster than peers on Standard Metrics data.", "A survey of 1,200 practitioners found 95% use AI at work or home, and 76% pay for tools out of pocket." ], "trust": "medium", "source_url": "https://www.stateof.ai/", "access": "free" }, { "id": "wk-future-ready-accountant-2025", "url": "https://aiunite.org/reports/wk-future-ready-accountant-2025/", "kind": "report", "title": "2025 Future Ready Accountant Report", "publisher": "Wolters Kluwer", "publisher_type": "Industry research & software", "published": "2025-10-08", "updated": "2026-09-29", "topics": [ "Professional services", "Adoption" ], "method": "Mixed survey", "sample_n": "2,700+", "respondents": "Tax and accounting professionals", "company_size": null, "geography": "Global (U.S., Canada, Europe, APAC editions)", "fieldwork": null, "headline_stat": "41%", "headline_label": "AI adoption among tax and accounting firms in 2025, up from 9% in 2024, as reported by Wolters Kluwer", "adoption_stage": "tried", "summary": "Wolters Kluwer's 2025 Future Ready Accountant Report (October 2025; n=2,700+) found that 41% of firms report adopting AI in 2025, up from 9% in 2024.", "findings": [ "Reported AI adoption rose from 9% in 2024 to 41% in 2025.", "77% of firms plan to increase AI investment over the next three years.", "35% use AI daily and 72% at least weekly; 73% of regular users report better-than-expected results." ], "trust": "medium", "source_url": "https://www.wolterskluwer.com/en/know/future-ready-accountant", "access": "gated" }, { "id": "bcg-widening-ai-value-gap-2025", "url": "https://aiunite.org/reports/bcg-widening-ai-value-gap-2025/", "kind": "report", "title": "The Widening AI Value Gap: Build for the Future 2025", "publisher": "Boston Consulting Group", "publisher_type": "Consultancy", "published": "2025-09-30", "updated": "2026-09-29", "topics": [ "ROI & value", "Strategy" ], "method": "Executive survey", "sample_n": "1,250", "respondents": "CxOs and senior executives who are AI decision makers", "company_size": "10% <$1B revenue; 42% $1B–$9.9B; 48% $10B+", "geography": "68 countries (37% North America, 40% Europe, 23% APAC)", "fieldwork": "2025 (dates not stated)", "headline_stat": "60%", "headline_label": "of companies report little or no material value from AI despite investment", "adoption_stage": "pnl", "summary": "Boston Consulting Group's The Widening AI Value Gap: Build for the Future 2025 (September 2025; n=1,250, fielded 2025 (dates not stated)) found that 60% of companies report little or no material value from AI despite investment.", "findings": [ "Only 5% of companies are 'future-built,' achieving AI value at scale; 35% are scaling with some returns.", "Future-built firms report 1.7x revenue growth and 1.6x EBIT margins versus the 60% lagging.", "Agents accounted for 17% of total AI value in 2025, expected to reach 29% by 2028." ], "trust": "medium", "source_url": "https://www.bcg.com/press/30september2025-ai-leaders-outpace-laggards-revenue-growth-cost-savings", "access": "free" }, { "id": "openai-gdpval-2025", "url": "https://aiunite.org/reports/openai-gdpval-2025/", "kind": "report", "title": "GDPval: Evaluating AI Model Performance on Real-World Economically Valuable Tasks", "publisher": "OpenAI", "publisher_type": "Technology company", "published": "2025-09-25", "updated": "2026-09-29", "topics": [ "Productivity", "Agents", "Workforce" ], "method": "Benchmark", "sample_n": "1,320 tasks (220-task gold subset graded by experts)", "respondents": "Tasks built from real work products by professionals averaging 14 years' experience; blinded pairwise grading by occupational experts", "company_size": null, "geography": "US occupations", "fieldwork": "2025", "headline_stat": "47.6%", "headline_label": "of tasks where the best model's work was rated as good as or better than an expert's", "adoption_stage": "n/a", "summary": "OpenAI's GDPval (September 2025; 220 expert-graded tasks across 44 occupations, benchmark) found that the best model tested, Claude Opus 4.1, produced work rated as good as or better than an industry expert's on 47.6% of tasks.", "findings": [ "Claude Opus 4.1's deliverables were rated better than or as good as the human expert's on 47.6% of the 220 gold-subset tasks.", "Among OpenAI models, the win rate against experts rose from 12.5% for GPT-4o to 39.0% for GPT-5.", "When an expert tries GPT-5, reviews the output and redoes the work if it falls short, the process was estimated to be 1.12x to 1.39x faster and 1.18x to 1.63x cheaper than the expert alone.", "About 29% of expert ratings of GPT-5's losing deliverables called them bad or catastrophic, with about 3% catastrophic.", "The 44 occupations come from the 9 sectors contributing most to U.S. GDP and collectively earn $3 trillion a year." ], "trust": "medium", "source_url": "https://openai.com/index/gdpval/", "access": "free" }, { "id": "bain-technology-report-2025", "url": "https://aiunite.org/reports/bain-technology-report-2025/", "kind": "report", "title": "Technology Report 2025", "publisher": "Bain & Company", "publisher_type": "Consultancy", "published": "2025-09-23", "updated": "2026-09-29", "topics": [ "Strategy", "Agents" ], "method": "Analysis", "sample_n": null, "respondents": "Not a single survey; analysis drawing on Bain client work and research", "company_size": "N/A", "geography": "Global", "fieldwork": "N/A", "headline_stat": "10–15%", "headline_label": "typical productivity boost for software teams using AI assistants, often not turning into business value", "adoption_stage": null, "summary": "Bain & Company's Technology Report 2025 (September 2025; fielded N/A) found that 10–15% typical productivity boost for software teams using AI assistants, often not turning into business value.", "findings": [ "Two out of three software firms have rolled out generative AI tools, but developer adoption remains low.", "Leaders pairing AI with end-to-end process redesign report 25–30% productivity gains, versus 10–15% from assistants alone.", "Sellers spend only about 25% of their time actually selling; Bain says AI could roughly double that." ], "trust": "low", "source_url": "https://www.bain.com/insights/topics/technology-report/", "access": "free" }, { "id": "harvard-seniority-biased-genai-2025", "url": "https://aiunite.org/reports/harvard-seniority-biased-genai-2025/", "kind": "report", "title": "Generative AI as Seniority-Biased Technological Change: Evidence from U.S. Résumé and Job Posting Data", "publisher": "Harvard University", "publisher_type": "University & nonprofit", "published": "2025-08-31", "updated": "2026-09-29", "topics": [ "Workforce" ], "method": "Labor data", "sample_n": "62 million workers; 285,000 firms", "respondents": "Résumé (linked employer-employee) and job posting data", "company_size": null, "geography": "US", "fieldwork": "2015–2025", "headline_stat": "~9%", "headline_label": "relative drop in junior employment at GenAI-adopting firms after six quarters", "adoption_stage": "n/a", "summary": "Harvard researchers' Generative AI as Seniority-Biased Technological Change (August 2025, revised October 2025; 62 million workers at 285,000 firms, labor data) found that junior employment at firms adopting generative AI fell about 9% relative to non-adopters within six quarters, while senior employment kept rising.", "findings": [ "Junior employment at adopting firms fell about 9% relative to non-adopters six quarters after early 2023.", "A stricter triple-difference comparison of juniors versus seniors within firms shows roughly a 10% relative drop after six quarters.", "In an event study around each firm's adoption date, junior employment began falling about three quarters after adoption and was down 8% after eight quarters.", "10,599 firms, about 3.7% of the sample, adopted GenAI by March 2025, but they account for 17.3% of employment.", "The junior decline is driven mainly by a substantial reduction in hiring, not by more separations or fewer promotions." ], "trust": "medium", "source_url": "https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5425555", "access": "free" }, { "id": "faros-ai-productivity-paradox-2025", "url": "https://aiunite.org/reports/faros-ai-productivity-paradox-2025/", "kind": "report", "title": "The AI Productivity Paradox Report 2025", "publisher": "Faros AI", "publisher_type": "Industry research & software", "published": "2025-07-23", "updated": "2026-09-29", "topics": [ "Productivity", "ROI & value" ], "method": "Usage data", "sample_n": "10,000+ developers; 1,255 teams", "respondents": "Engineering teams at Faros AI customer organizations", "company_size": null, "geography": null, "fieldwork": "Up to two years of historical telemetry, aggregated quarterly", "headline_stat": "98%", "headline_label": "more pull requests merged on high-AI-adoption teams", "adoption_stage": "n/a", "summary": "Faros AI's The AI Productivity Paradox Report 2025 (July 2025; n=10,000+ developers across 1,255 teams, telemetry analysis) found that developers on high-AI-adoption teams merged 98% more pull requests, but review time rose 91% and company-level delivery showed no measurable improvement.", "findings": [ "Developers on teams with high AI adoption completed 21% more tasks and merged 98% more pull requests.", "Pull request review time increased 91% on those teams.", "AI adoption was associated with a 9% increase in bugs per developer and a 154% increase in average PR size.", "Developers on high-adoption teams touched 9% more tasks and 47% more pull requests per day.", "There was no significant correlation between AI adoption and company-level improvement in throughput, DORA metrics, or quality." ], "trust": "medium", "source_url": "https://www.faros.ai/blog/ai-software-engineering", "access": "gated" }, { "id": "metr-early-2025-ai-dev-productivity-2025", "url": "https://aiunite.org/reports/metr-early-2025-ai-dev-productivity-2025/", "kind": "report", "title": "Measuring the Impact of Early-2025 AI on Experienced Open-Source Developer Productivity", "publisher": "METR (Model Evaluation & Threat Research)", "publisher_type": "University & nonprofit", "published": "2025-07-10", "updated": "2026-09-29", "topics": [ "Productivity" ], "method": "Experiment", "sample_n": "16 developers; 246 tasks", "respondents": "Experienced open-source developers working in repositories they had contributed to for multiple years", "company_size": null, "geography": null, "fieldwork": "Feb–Jun 2025", "headline_stat": "19%", "headline_label": "longer to complete tasks when AI tools were allowed", "adoption_stage": "n/a", "summary": "METR's Measuring the Impact of Early-2025 AI on Experienced Open-Source Developer Productivity (July 2025; n=16 developers, 246 tasks, randomized controlled trial) found that developers took 19% longer to finish tasks when AI tools were allowed.", "findings": [ "Developers took 19% longer to complete issues when AI tools were allowed.", "Before the study, developers expected AI to speed them up by 24%.", "After experiencing the slowdown, developers still believed AI had sped them up by 20%.", "The 19% slowdown had a confidence interval of +2% to +39%.", "Tasks averaged about two hours each, in repositories averaging 22k+ GitHub stars and 1M+ lines of code." ], "trust": "high", "source_url": "https://metr.org/blog/2025-07-10-early-2025-ai-experienced-os-dev-study/", "access": "free" }, { "id": "mit-nanda-genai-divide-2025", "url": "https://aiunite.org/reports/mit-nanda-genai-divide-2025/", "kind": "report", "title": "The GenAI Divide: State of AI in Business 2025", "publisher": "MIT NANDA", "publisher_type": "University & nonprofit", "published": "2025-07", "updated": "2026-09-29", "topics": [ "ROI & value", "Adoption" ], "method": "Interviews + survey", "sample_n": "153 survey responses + 52 organization interviews + 300+ public initiatives reviewed", "respondents": "Senior leaders surveyed at four industry conferences; interviews with enterprise stakeholders", "company_size": "Enterprise and mid-market (not further specified)", "geography": "Not specified", "fieldwork": "Jan–Jun 2025", "headline_stat": "95%", "headline_label": "of organizations are getting zero return from GenAI, per the report's executive summary", "adoption_stage": "pnl", "summary": "MIT NANDA's The GenAI Divide: State of AI in Business 2025 (July 2025; n=153 survey responses + 52 organization interviews + 300+ public initiatives reviewed, fielded Jan–Jun 2025) found that 95% of organizations are getting zero return from GenAI, per the report's executive summary.", "findings": [ "Just 5% of integrated AI pilots are extracting millions in value; most show no measurable P&L impact.", "Over 80% of organizations explored or piloted tools like ChatGPT/Copilot; only 5% of custom enterprise AI tools reached production.", "In the interview sample, externally partnered tools reached deployment about 67% of the time versus about 33% for internally built tools." ], "trust": "low", "source_url": "https://mlq.ai/media/quarterly_decks/v0.1_State_of_AI_in_Business_2025_Report.pdf", "access": "free" }, { "id": "bcg-ai-first-companies-2025", "url": "https://aiunite.org/reports/bcg-ai-first-companies-2025/", "kind": "playbook", "title": "How Companies Can Prepare for an AI-First Future (AI-First Companies Win the Future)", "publisher": "Boston Consulting Group", "publisher_type": "Consultancy", "published": "2025-06-17", "updated": "2026-09-29", "topics": [ "Strategy" ], "method": "Playbook", "sample_n": null, "respondents": null, "company_size": null, "geography": null, "fieldwork": null, "headline_stat": "5 moves", "headline_label": "business-led agenda, use AI yourself, plan for workforce shifts, prove impact on a few bets, fund what works", "adoption_stage": null, "summary": "How Companies Can Prepare for an AI-First Future (AI-First Companies Win the Future) is a 2025 guide from Boston Consulting Group. Its core idea: business-led agenda, use AI yourself, plan for workforce shifts, prove impact on a few bets, fund what works.", "findings": [ "Argues AI-first firms reshape competition: trust, brand, IP, proprietary data and AI-fluent talent gain importance, while scale and headcount matter less.", "Expects spending to shift from people to technology, with business units owning and deploying AI instead of central IT.", "Short-term agenda: business-led AI priorities, leaders using AI daily, workforce planning, a few high-value initiatives, and funding proven wins." ], "trust": "medium", "source_url": "https://www.bcg.com/publications/2025/how-companies-can-prepare-for-ai-first-future", "access": "free" }, { "id": "microsoft-strategic-cio-genai-playbook-2025", "url": "https://aiunite.org/reports/microsoft-strategic-cio-genai-playbook-2025/", "kind": "playbook", "title": "The Strategic CIO's Generative AI Playbook", "publisher": "Microsoft", "publisher_type": "Technology company", "published": "2025-05-08", "updated": "2026-09-29", "topics": [ "Strategy", "Governance & risk" ], "method": "Playbook", "sample_n": null, "respondents": null, "company_size": null, "geography": null, "fieldwork": null, "headline_stat": "3 pillars", "headline_label": "leadership, human change, and technical readiness", "adoption_stage": null, "summary": "The Strategic CIO's Generative AI Playbook is a 2025 guide from Microsoft. Its core idea: leadership, human change, and technical readiness.", "findings": [ "Organized in three sections: the AI-ready organization, enabling all employees, and moving from functional workflows to intelligent agents.", "Stresses data readiness, security and governance before rollout, including cleaning up oversharing and stale content.", "Proposes measuring AI across readiness, adoption and impact; much guidance is specific to Microsoft 365 Copilot." ], "trust": "low", "source_url": "https://techcommunity.microsoft.com/blog/microsoft-copilot-blog/rewriting-the-it-playbook-empowering-cios-to-lead-with-confidence-in-the-ai-era/4411734", "access": "free" }, { "id": "accenture-front-runners-guide-scaling-ai-2025", "url": "https://aiunite.org/reports/accenture-front-runners-guide-scaling-ai-2025/", "kind": "playbook", "title": "The front-runners' guide to scaling AI: Lessons from industry leaders", "publisher": "Accenture", "publisher_type": "Consultancy", "published": "2025-05-06", "updated": "2026-09-29", "topics": [ "Strategy", "ROI & value" ], "method": "Playbook", "sample_n": null, "respondents": null, "company_size": null, "geography": null, "fieldwork": null, "headline_stat": "5 imperatives", "headline_label": "lead with value, reinvent talent, build a secure digital core, close the responsible-AI gap, keep reinventing", "adoption_stage": null, "summary": "The front-runners' guide to scaling AI: Lessons from industry leaders is a 2025 guide from Accenture. Its core idea: lead with value, reinvent talent, build a secure digital core, close the responsible-AI gap, keep reinventing.", "findings": [ "Only 8% of the 2,000 companies surveyed are 'front-runners' scaling AI enterprise-wide; 15% are 'reinvention-ready'.", "Front-runners pair table-stakes AI investments with a few strategic bets; companies that scale even one bet are nearly 3x likelier to beat ROI expectations.", "Five imperatives: lead with value, reinvent talent and ways of working, build a secure digital core, close the responsible-AI gap, drive continuous reinvention." ], "trust": "medium", "source_url": "https://www.accenture.com/en/insights/ai-data/front-runners-guide-scaling-ai", "access": "free" }, { "id": "openai-identifying-scaling-ai-use-cases-2025", "url": "https://aiunite.org/reports/openai-identifying-scaling-ai-use-cases-2025/", "kind": "playbook", "title": "Identifying and scaling AI use cases: How early adopters focus their AI efforts", "publisher": "OpenAI", "publisher_type": "Technology company", "published": "2025-04", "updated": "2026-09-29", "topics": [ "Strategy" ], "method": "Playbook", "sample_n": null, "respondents": null, "company_size": null, "geography": null, "fieldwork": null, "headline_stat": "6 primitives", "headline_label": "content creation, research, coding, data analysis, ideation/strategy, automation", "adoption_stage": null, "summary": "Identifying and scaling AI use cases: How early adopters focus their AI efforts is a 2025 guide from OpenAI. Its core idea: content creation, research, coding, data analysis, ideation/strategy, automation.", "findings": [ "Three steps: spot where AI helps (repetitive tasks, skill bottlenecks, ambiguity), teach six use-case primitives, then collect and prioritize use cases.", "Recommends leadership-led adoption, starting with simple employee-found use cases, and hackathons or workshops to speed discovery.", "Prioritizes use cases on an impact-versus-effort view; based on OpenAI's customer implementations and adoption surveys." ], "trust": "medium", "source_url": "https://openai.com/business/guides-and-resources/identifying-and-scaling-ai-use-cases/", "access": "free" }, { "id": "openai-practical-guide-building-agents-2025", "url": "https://aiunite.org/reports/openai-practical-guide-building-agents-2025/", "kind": "playbook", "title": "A practical guide to building agents", "publisher": "OpenAI", "publisher_type": "Technology company", "published": "2025-04", "updated": "2026-09-29", "topics": [ "Agents" ], "method": "Playbook", "sample_n": null, "respondents": null, "company_size": null, "geography": null, "fieldwork": null, "headline_stat": "3 components", "headline_label": "an agent is a model, tools, and instructions, wrapped in guardrails", "adoption_stage": null, "summary": "A practical guide to building agents is a 2025 guide from OpenAI. Its core idea: an agent is a model, tools, and instructions, wrapped in guardrails.", "findings": [ "Suggests agents where rules-based automation struggles: complex judgment calls, hard-to-maintain rule sets, or heavy unstructured data.", "Defines an agent as model, tools and instructions; start with a single agent and add multi-agent patterns only when needed.", "Layered guardrails and human intervention for high-risk or failing actions are essential; customers succeed with an incremental approach." ], "trust": "medium", "source_url": "https://openai.com/business/guides-and-resources/a-practical-guide-to-building-ai-agents/", "access": "free" }, { "id": "bain-transforming-business-with-ai-2025", "url": "https://aiunite.org/reports/bain-transforming-business-with-ai-2025/", "kind": "playbook", "title": "Transforming your business with AI: five questions for every CEO", "publisher": "Bain & Company", "publisher_type": "Consultancy", "published": "2025-01-16", "updated": "2026-09-29", "topics": [ "Strategy" ], "method": "Playbook", "sample_n": null, "respondents": null, "company_size": null, "geography": null, "fieldwork": null, "headline_stat": "3 reinventions", "headline_label": "set an AI agenda across three parallel reinventions, with CEO sponsorship from day one", "adoption_stage": null, "summary": "Transforming your business with AI: five questions for every CEO is a 2025 guide from Bain & Company. Its core idea: set an AI agenda across three parallel reinventions, with CEO sponsorship from day one.", "findings": [ "Urges CEOs to form a clear view of how AI could reshape their industry's profit pools before setting an agenda.", "Recommends an agenda built across three parallel reinventions and moving past experimentation to full business transformation.", "Cites benefits from AI-enhanced customer offerings such as 5–15% top-line increases and 15–20% churn reduction." ], "trust": "medium", "source_url": "https://www.bain.com/insights/transform-business-with-ai-five-questions-for-every-ceo/", "access": "free" }, { "id": "anthropic-building-effective-agents-2024", "url": "https://aiunite.org/reports/anthropic-building-effective-agents-2024/", "kind": "playbook", "title": "Building effective agents", "publisher": "Anthropic", "publisher_type": "Technology company", "published": "2024-12-19", "updated": "2026-09-29", "topics": [ "Agents" ], "method": "Playbook", "sample_n": null, "respondents": null, "company_size": null, "geography": null, "fieldwork": null, "headline_stat": "Start simple", "headline_label": "use the simplest solution that works; add agentic complexity only when it clearly pays off", "adoption_stage": null, "summary": "Building effective agents is a 2024 guide from Anthropic. Its core idea: use the simplest solution that works; add agentic complexity only when it clearly pays off.", "findings": [ "Distinguishes workflows (predefined code paths) from agents (models directing their own process and tool use).", "Describes common patterns, including prompt chaining, routing, parallelization, orchestrator-workers and evaluator-optimizer, drawn from customer work.", "Advises keeping designs simple and transparent and investing in well-documented tools; agents trade cost and latency for flexibility." ], "trust": "medium", "source_url": "https://www.anthropic.com/engineering/building-effective-agents", "access": "free" }, { "id": "sba-ai-for-small-business", "url": "https://aiunite.org/reports/sba-ai-for-small-business/", "kind": "playbook", "title": "AI for small businesses (SBA business guide)", "publisher": "U.S. Small Business Administration", "publisher_type": "Government & central bank", "published": "2024-12", "updated": "2026-09-29", "topics": [ "Strategy" ], "method": "Playbook", "sample_n": null, "respondents": null, "company_size": null, "geography": null, "fieldwork": null, "headline_stat": "Start small", "headline_label": "test low-cost AI tools against real needs, and weigh risks as well as benefits", "adoption_stage": null, "summary": "AI for small businesses (SBA business guide) is a 2024 guide from U.S. Small Business Administration. Its core idea: test low-cost AI tools against real needs, and weigh risks as well as benefits.", "findings": [ "Advises small businesses to start small, noting many AI tools offer free or low-cost tiers to test before committing.", "Covers AI benefits, risks of AI use, common terminology, and links to additional federal resources.", "Emphasizes ethical use of AI tools and improving internal efficiency so owners can focus on growth." ], "trust": "high", "source_url": "https://www.sba.gov/counseling/manage-your-business/#ai-for-small-business", "access": "free" }, { "id": "ibm-ibv-ceo-guide-generative-ai-2024", "url": "https://aiunite.org/reports/ibm-ibv-ceo-guide-generative-ai-2024/", "kind": "playbook", "title": "The CEO's Guide to Generative AI", "publisher": "IBM Institute for Business Value", "publisher_type": "Technology company", "published": "2024-10-07", "updated": "2026-09-29", "topics": [ "Strategy" ], "method": "Playbook", "sample_n": null, "respondents": null, "company_size": null, "geography": null, "fieldwork": null, "headline_stat": "22 chapters", "headline_label": "function-by-function CEO briefings, from talent and customer service to finance and cost of compute", "adoption_stage": null, "summary": "The CEO's Guide to Generative AI is a 2024 guide from IBM Institute for Business Value. Its core idea: function-by-function CEO briefings, from talent and customer service to finance and cost of compute.", "findings": [ "A 22-chapter series, each a short CEO briefing on one area: talent, customer service, cybersecurity, finance, procurement, operating model, and more.", "Draws on IBM IBV surveys of C-suite executives, released in installments from 2023 through October 2024.", "Each chapter pairs survey findings with recommended actions for leaders." ], "trust": "medium", "source_url": "https://www.ibm.com/thought-leadership/institute-business-value/en-us/report/ceo-generative-ai", "access": "free" }, { "id": "nist-ai-rmf-genai-profile", "url": "https://aiunite.org/reports/nist-ai-rmf-genai-profile/", "kind": "playbook", "title": "AI Risk Management Framework (AI RMF 1.0) + Generative AI Profile (NIST-AI-600-1)", "publisher": "NIST", "publisher_type": "Standards body", "published": "2024-07-26", "updated": "2026-09-29", "topics": [ "Governance & risk" ], "method": "Playbook", "sample_n": null, "respondents": null, "company_size": null, "geography": null, "fieldwork": null, "headline_stat": "4 functions", "headline_label": "Govern, Map, Measure, Manage", "adoption_stage": null, "summary": "AI Risk Management Framework (AI RMF 1.0) + Generative AI Profile (NIST-AI-600-1) is a 2024 guide from NIST. Its core idea: Govern, Map, Measure, Manage.", "findings": [ "AI RMF 1.0 (Jan 2023) organizes AI risk work into four functions: Govern, Map, Measure, Manage; voluntary and sector-neutral.", "The Generative AI Profile (July 2024) names 12 risks unique to or worsened by generative AI and suggests 200+ actions.", "A companion online Playbook gives suggested actions per subcategory; NIST is revising the framework under the 2025 White House AI Action Plan." ], "trust": "high", "source_url": "https://www.nist.gov/itl/ai-risk-management-framework", "access": "free" }, { "id": "iso-iec-42001-2023", "url": "https://aiunite.org/reports/iso-iec-42001-2023/", "kind": "playbook", "title": "ISO/IEC 42001:2023 AI management systems (overview: What businesses need to know)", "publisher": "ISO / IEC", "publisher_type": "Standards body", "published": "2023-12", "updated": "2026-09-29", "topics": [ "Governance & risk" ], "method": "Playbook", "sample_n": null, "respondents": null, "company_size": null, "geography": null, "fieldwork": null, "headline_stat": "Plan-Do-Check-Act", "headline_label": "the first certifiable AI management system standard, run like ISO 9001 or 27001", "adoption_stage": null, "summary": "ISO/IEC 42001:2023 AI management systems (overview: What businesses need to know) is a 2023 guide from ISO / IEC. Its core idea: the first certifiable AI management system standard, run like ISO 9001 or 27001.", "findings": [ "ISO/IEC 42001 is described as the world's first AI management system standard, published December 2023 (edition 1, 51 pages).", "Uses a Plan-Do-Check-Act cycle with periodic AI risk assessment and treatment, similar to ISO 9001 and ISO/IEC 27001.", "Certifiable by third-party auditors; ISO's free overview explains it, while the standard itself must be purchased." ], "trust": "high", "source_url": "https://www.iso.org/artificial-intelligence/ai-management-systems", "access": "paid" }, { "id": "wef-ai-csuite-toolkit-2022", "url": "https://aiunite.org/reports/wef-ai-csuite-toolkit-2022/", "kind": "playbook", "title": "Empowering AI Leadership: AI C-Suite Toolkit", "publisher": "World Economic Forum", "publisher_type": "University & nonprofit", "published": "2022-01-12", "updated": "2026-09-29", "topics": [ "Strategy", "Governance & risk" ], "method": "Playbook", "sample_n": null, "respondents": null, "company_size": null, "geography": null, "fieldwork": null, "headline_stat": "5 modules", "headline_label": "intro to AI, AI strategy, people and organization, responsible AI, implementation", "adoption_stage": null, "summary": "Empowering AI Leadership: AI C-Suite Toolkit is a 2022 guide from World Economic Forum. Its core idea: intro to AI, AI strategy, people and organization, responsible AI, implementation.", "findings": [ "Organized into five modules: introduction to AI, AI strategy, people and organization, responsible AI, and implementation, plus a sixth on specialized topics.", "Includes a preparedness assessment tool and a guidance tool as appendices for executives.", "Built with multiple companies and experts, including PwC; published under a Creative Commons non-commercial license." ], "trust": "medium", "source_url": "https://www.weforum.org/publications/empowering-ai-leadership-ai-c-suite-toolkit/", "access": "free" }, { "id": "google-cloud-ai-adoption-framework-2020", "url": "https://aiunite.org/reports/google-cloud-ai-adoption-framework-2020/", "kind": "playbook", "title": "Google Cloud's AI Adoption Framework", "publisher": "Google Cloud", "publisher_type": "Technology company", "published": "2020-06-29", "updated": "2026-09-29", "topics": [ "Strategy" ], "method": "Playbook", "sample_n": null, "respondents": null, "company_size": null, "geography": null, "fieldwork": null, "headline_stat": "6 themes × 3 phases", "headline_label": "Lead, Learn, Access, Scale, Secure, Automate across tactical, strategic and transformational maturity", "adoption_stage": null, "summary": "Google Cloud's AI Adoption Framework is a 2020 guide from Google Cloud. Its core idea: Lead, Learn, Access, Scale, Secure, Automate across tactical, strategic and transformational maturity.", "findings": [ "Frames AI capability across four areas: people, process, technology and data.", "Six maturity themes (Lead, Learn, Access, Scale, Secure, Automate) scored across three phases: tactical, strategic, transformational.", "Part two is a technical deep dive aimed at technology leaders building ML capability on cloud platforms." ], "trust": "low", "source_url": "https://cloud.google.com/resources/cloud-ai-adoption-framework-whitepaper", "access": "gated" }, { "id": "mckinsey-executives-ai-playbook-2018", "url": "https://aiunite.org/reports/mckinsey-executives-ai-playbook-2018/", "kind": "playbook", "title": "The executive's AI playbook", "publisher": "McKinsey & Company", "publisher_type": "Consultancy", "published": "2018-11-07", "updated": "2026-09-29", "topics": [ "Strategy" ], "method": "Playbook", "sample_n": null, "respondents": null, "company_size": null, "geography": null, "fieldwork": null, "headline_stat": "Pilot purgatory", "headline_label": "size the AI opportunity by industry, then build the data, tech and practices to scale beyond pilots", "adoption_stage": null, "summary": "The executive's AI playbook is a 2018 guide from McKinsey & Company. Its core idea: size the AI opportunity by industry, then build the data, tech and practices to scale beyond pilots.", "findings": [ "Interactive tool that sizes the AI value opportunity by industry using McKinsey market data.", "Outlines the data and technology capabilities a company needs to capture that value.", "Collects best practices aimed at moving AI efforts out of pilots and into organization-wide use." ], "trust": "medium", "source_url": "https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-executives-ai-playbook", "access": "free" } ] }