Gartner predicted in July 2024 that at least 30% of generative AI projects would be abandoned after proof of concept by the end of 2025.
30%
of generative AI projects to be abandoned, Gartner predicted
Gartner predicted in July 2024 that at least 30% of generative AI projects would be abandoned after proof of concept by the end of 2025.
Gartner named poor data quality, inadequate risk controls, escalating costs and unclear business value as the causes.
Source: Gartner Predicts 30% of Generative AI Projects Will Be Abandoned After Proof of Concept By End of 2025 (opens in a new tab), First paragraph. Verified October 2026.
Related charts
- From the blog
Only 5% of organizations put a custom or vendor-sold generative AI tool into production
MIT NANDA, The GenAI Divide: State of AI in Business 2025 (July 2025) - From the blog
4 of the 7 practice problems on Kent Applied's map need no patient data
Kent Applied, Where AI tools fit in healthcare, by kind of organization; NYC Local Law 144; California Civil Rights Council - From the blog
Imaging, insurance checks, charting and billing lead dentists' current and planned AI use
ADA Health Policy Institute, The State of the US Dental Economy, 2nd Quarter 2026 Update - From research
30 of 44 top healthcare problems need no patient data, in Kent Applied's analysis
Kent Applied, Where AI tools fit in healthcare, by kind of organization; NYC Local Law 144; California Civil Rights Council
Sources for the figures above: MIT NANDA, The GenAI Divide: State of AI in Business 2025 (July 2025) (opens in a new tab).
Related facts
5%
of organizations reached production with a generative AI tool
MIT NANDA's 2025 research found that 60% of organizations evaluated custom or vendor-sold generative AI tools, 20% reached a pilot and 5% reached production.
Source: The GenAI Divide: State of AI in Business 2025.
KentApplied95%
of organizations getting zero return from generative AI
MIT NANDA's 2025 report found that 95% of organizations were getting zero return from generative AI, despite $30 billion to $40 billion in enterprise investment.
Source: The GenAI Divide: State of AI in Business 2025.
KentApplied83%
of cases, at worst, models repeated a planted error
Six large language models repeated or built on a fabricated lab value, sign or condition planted in a clinical case in up to 83% of cases, a 2025 study in Communications Medicine found.
Source: Multi-model assurance analysis showing large language models are highly vulnerable to adversarial hallucination attacks during clinical decision support.
KentApplied
Sources for the figures above: MIT NANDA, The GenAI Divide: State of AI in Business 2025 (July 2025) (opens in a new tab); Multi-model assurance analysis showing large language models are highly vulnerable to adversarial hallucination attacks during clinical decision support (opens in a new tab).
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