Expired60% confidencePredictionTime unknown
According to Gartner's prediction, by 2025, more than 30% of enterprise AI projects will fail due to a lack of proper operational infrastructure rather than insufficient model capabilities.
2
Sources
60%
Confidence
Medium-term (~90 days)
Relevance
5/31/2026
First Seen
This claim has expired. It is kept for the record and no longer describes the current state.
Valid until: 8/29/2026(expired)
Sources
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Related Claims
VerifiedMcKinsey research shows that the success rate of AI projects moving from proof-of-concept to full deployment is less than 20%, with a lack of engineering capabilities being the primary reason.73% similarUnverifiedResearch by Anthropic indicates that in production environments, more than 30% of Agent task failures originate from improper loop design.70% similarUnverifiedCore barriers to AI adoption by SMEs include human capital constraints, weak data infrastructure, limited risk tolerance, and insufficient adaptability for specific scenarios67% similarUnverifiedOrganizational inertia, the lack of a mature AI-native development paradigm, and the absence of measurement systems are the three major obstacles preventing engineering teams from undergoing deep AI transformation.66% similarUnverifiedThe primary reason software projects fail is often not technical issues, but unclear requirements.65% similar
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