{ "name": "AI Project Failure Statistics for 2026", "version": "2026-08-17", "license": "CC BY 4.0", "methodologyUrl": "https://cognautic.com/answers/ai-project-failure-statistics#method", "records": [ { "id": "gartner-2024-genai-abandonment-forecast", "statistic": "Generative AI projects forecast to be abandoned after proof of concept by the end of 2025", "value": "30", "unit": "percent_at_least", "evidenceType": "forecast", "population": "Organizations pursuing generative AI projects", "period": "Forecast published July 2024 for year-end 2025", "sample": "Not stated in the public newsroom release", "definition": "Project abandoned after proof of concept because of poor data quality, inadequate risk controls, escalating costs, or unclear business value", "sourceName": "Gartner", "sourceUrl": "https://www.gartner.com/en/newsroom/press-releases/2024-07-29-gartner-predicts-30-percent-of-generative-ai-projects-will-be-abandoned-after-proof-of-concept-by-end-of-2025", "limitation": "A forecast, not an observed universal failure rate; the public release does not disclose a project denominator or sampling method for this figure.", "checkedAt": "2026-08-17" }, { "id": "gartner-2026-genai-abandonment-statement", "statistic": "Generative AI projects stated to have been abandoned after proof of concept by the end of 2025", "value": "50", "unit": "percent_at_least", "evidenceType": "analyst finding", "population": "Generative AI projects analyzed by Gartner", "period": "Projects analyzed through the end of 2025; article published 2026", "sample": "Hundreds of generative AI projects; exact count not stated publicly", "definition": "Project abandoned after proof of concept for reasons including unclear business value, data problems, total cost, responsible-AI gaps, or model performance", "sourceName": "Gartner", "sourceUrl": "https://www.gartner.com/en/articles/genai-project-failure", "limitation": "The public article says Gartner analyzed hundreds of projects but does not publish the full sampling frame, denominator, or calculation needed to generalize the percentage.", "checkedAt": "2026-08-17" }, { "id": "gartner-2025-ai-ready-data-forecast", "statistic": "AI projects unsupported by AI-ready data forecast to be abandoned through 2026", "value": "60", "unit": "percent", "evidenceType": "conditional forecast", "population": "AI projects that are not supported by AI-ready data", "period": "Forecast published February 2025 for the period through 2026", "sample": "Prediction informed by Gartner research; a related survey covered 1,203 data-management leaders", "definition": "Project abandonment associated with an organization's failure to maintain AI-ready data", "sourceName": "Gartner", "sourceUrl": "https://www.gartner.com/en/newsroom/press-releases/2025-02-26-lack-of-ai-ready-data-puts-ai-projects-at-risk", "limitation": "Conditional forecast about projects lacking AI-ready data, not a measured rate for every AI project; the related survey is not presented as the direct denominator for the forecast.", "checkedAt": "2026-08-17" }, { "id": "gartner-2024-genai-prototypes-production", "statistic": "Generative AI prototypes reported to reach production", "value": "41", "unit": "percent_average", "evidenceType": "survey finding", "population": "Organizations represented in a 2024 Gartner survey", "period": "2024 survey; abstract published 2025", "sample": "Not stated in the public abstract", "definition": "Average share of generative AI prototypes that respondents reported progressing into production", "sourceName": "Gartner", "sourceUrl": "https://www.gartner.com/en/documents/6587902", "limitation": "Self-reported average; the public abstract does not disclose the sample, question wording, distribution, or whether production meant limited or broad deployment.", "checkedAt": "2026-08-17" }, { "id": "gartner-2024-nongenai-prototypes-production", "statistic": "Non-generative AI prototypes reported to reach production", "value": "42", "unit": "percent_average", "evidenceType": "survey finding", "population": "Organizations represented in a 2024 Gartner survey", "period": "2024 survey; abstract published 2025", "sample": "Not stated in the public abstract", "definition": "Average share of non-generative AI prototypes that respondents reported progressing into production", "sourceName": "Gartner", "sourceUrl": "https://www.gartner.com/en/documents/6587902", "limitation": "Self-reported average with no public sample detail; a prototype not reaching production is not necessarily a failed project because experimentation may be designed to stop weak ideas.", "checkedAt": "2026-08-17" }, { "id": "sp-global-companies-abandon-majority", "statistic": "Companies reporting that they abandoned the majority of AI initiatives before production", "value": "42", "unit": "percent_of_companies", "evidenceType": "survey finding", "population": "Mid-level and senior IT and line-of-business respondents at organizations in North America and Europe", "period": "Survey fielded in 2025", "sample": "1,006 respondents", "definition": "Respondent's company abandoned the majority of its AI initiatives before reaching production", "sourceName": "S&P Global Market Intelligence", "sourceUrl": "https://www.spglobal.com/market-intelligence/en/news-insights/research/ai-experiences-rapid-adoption-but-with-mixed-outcomes-highlights-from-vote-ai-machine-learning", "limitation": "Organization-level self-report from a regional business sample; it does not say that 42% of individual projects failed.", "checkedAt": "2026-08-17" }, { "id": "sp-global-projects-scrapped-before-broad-adoption", "statistic": "AI projects scrapped between proof of concept and broad adoption", "value": "46", "unit": "percent_average", "evidenceType": "survey finding", "population": "AI projects represented by surveyed organizations in North America and Europe", "period": "Survey fielded in 2025", "sample": "1,006 mid-level and senior IT and line-of-business respondents", "definition": "Average share of AI projects reported as scrapped after proof of concept but before broad adoption", "sourceName": "S&P Global Market Intelligence", "sourceUrl": "https://www.spglobal.com/market-intelligence/en/news-insights/research/ai-experiences-rapid-adoption-but-with-mixed-outcomes-highlights-from-vote-ai-machine-learning", "limitation": "Self-reported average; broad adoption is a higher threshold than first production, and a deliberately stopped experiment may be a sound portfolio decision rather than an implementation failure.", "checkedAt": "2026-08-17" }, { "id": "sp-global-no-strong-positive-impact", "statistic": "Organizations investing in generative AI that reported no strong positive impact on any enterprise objective", "value": "46", "unit": "percent_of_respondents", "evidenceType": "survey finding", "population": "Respondents at organizations actively investing in generative AI", "period": "Survey fielded in 2025", "sample": "Subgroup of 1,006 survey respondents; subgroup count not stated on the public page", "definition": "No strong positive impact reported for any listed enterprise objective", "sourceName": "S&P Global Market Intelligence", "sourceUrl": "https://www.spglobal.com/market-intelligence/en/news-insights/research/ai-experiences-rapid-adoption-but-with-mixed-outcomes-highlights-from-vote-ai-machine-learning", "limitation": "A self-reported impact threshold, not a project failure rate or a causal ROI measurement; limited and early deployments may not yet produce enterprise-wide effects.", "checkedAt": "2026-08-17" }, { "id": "rand-cited-ai-project-failure-estimate", "statistic": "AI projects described as failing in an estimate cited by RAND", "value": "80", "unit": "percent_greater_than", "evidenceType": "secondary estimate cited in a RAND report", "population": "AI projects described by an external secondary source", "period": "RAND report published 2024", "sample": "Not measured by RAND", "definition": "Project failure as described in an external article cited by the RAND report", "sourceName": "Fortune", "sourceUrl": "https://fortune.com/2022/07/26/a-i-success-business-sense-aible-sengupta/", "citedByName": "RAND Corporation", "citedByUrl": "https://www.rand.org/content/dam/rand/pubs/research_reports/RRA2600/RRA2680-1/RAND_RRA2680-1.pdf", "limitation": "The Fortune article describes recent surveys as placing AI project failure between 83% and 92% but does not name or link those surveys. RAND cites the Fortune article for its 'more than 80%' statement and did not measure the percentage.", "checkedAt": "2026-08-17" }, { "id": "rand-industry-interviews-leadership-causes", "statistic": "Industry interviewees citing one or more leadership-driven reasons as a primary cause of AI project failure", "value": "84", "unit": "percent_of_industry_interviewees", "evidenceType": "qualitative interview coding", "population": "Experienced AI practitioners interviewed from industry", "period": "Interviews supporting a 2024 RAND report", "sample": "Industry subset of 65 total interviewees from industry and academia", "definition": "Interviewee identified at least one leadership-driven root cause among the primary reasons AI projects fail", "sourceName": "RAND Corporation", "sourceUrl": "https://www.rand.org/content/dam/rand/pubs/research_reports/RRA2600/RRA2680-1/RAND_RRA2680-1.pdf", "limitation": "Qualitative interview coding about causes, not a percentage of projects that failed; the public text reports 65 total interviewees but this statistic applies only to the industry subset.", "checkedAt": "2026-08-17" } ] }