Doomed enterprise AI projects usually lack vision

"Failed implementations of AI technologies are pushing CIOs to step back and try to better understand the technology and its impact before moving ahead, according to analysts and industry experts. While AI commitment in enterprises remains high, the success rate of prototyping to production is low, research firm Omdia said in a survey released last week. Proof-of-concept failure "is not usually because of inherent defects in the AI technology being tested, but because enterprises and vendors do not understand the complexity of what AI deployment involves," Omdia said."

"Enterprises with less than $100 million in revenue are prototyping fewer than five AI projects. But the failure rates of these early efforts are high. Only 10% of the companies surveyed achieved more than a 40% success rate; 37% saw between 11% and 40% of their projects reach production; and 21% reported a success rate of between 5% and 10%. The rest saw fewer than 5% of their prototype projects reach production."

""This points to a mixed, nuanced picture for [proof-of-concept] progress - a bifurcation rather than universal failure, where many enterprises are successfully transitioning from AI PoCs to production while others are still clearly struggling," Eden Zoller, chief analyst of applied AI said in a blog post on the Omdia AI Market Maturity 2025 survey. CIOs and other IT decision-makers are under pressure from boards and CEOs who want their companies to be "AI-first" operations; that runs the risk of moving too fast on execution and choosing the right projects, said Steven Dickens, principal analyst at Hyperframe Research."

Enterprises show strong commitment to AI but face low conversion from prototyping to production. Proof-of-concept failures arise mainly from misunderstanding the complexity of AI deployment rather than inherent technology defects. AI experimentation is concentrated in cash-rich firms, with 58% running six to 50 experimental projects while smaller companies prototype fewer than five. Overall production success is limited: only 10% of companies achieve over a 40% success rate, many report 5–40% success, and a substantial share sees fewer than 5% of prototypes reach production. Executive pressure to be "AI-first" can prompt rushed execution and poor project selection.

Read at Computerworld