Last reviewed: May 24, 2026

What is an AI POC? Definition and right instinct vs wrong instinct

An AI POC (proof of concept) is a short pilot project aimed at testing the technical feasibility and business value of an AI application before any industrial investment. According to RAND 2025, 80.3% of enterprise AI POCs fail to deliver their expected business value.

The failure rate of AI POCs in enterprise is consistently documented. RAND Corporation (analysis of 2,400 initiatives, 2025): 80.3% failure. MIT Project NANDA (July 2025): 95% of GenAI POCs fail to scale to production. S&P Global Market Intelligence (1,000+ enterprise survey, 2025): 42% of organisations abandoned at least one AI project in 2025. Five structural causes dominate failure. Business data not ready or not governed. Use case ill-defined or drifting (use-case drift). Lack of pre-AI measurement. No POC-to-production transition planned from the start. Gap between technical demo and real-world conditions (integration, loads, security). The average cost of an abandoned AI POC is 4.2 million dollars (S&P Global, 2025), rising to 7.2 million for POCs completed but with no value delivered.

Concrete example

A 1,100-employee private bank launches in 2025 a POC for an AI assistant for wealth advisers. Three differences from a classic POC. The perimeter is narrow: 12 volunteer advisers, 3 months of testing, on a precise customer sub-segment. Measurement is prepared upfront: 8 business indicators baselined over the previous 6 months. The transition to production is planned from the start: if indicators improve by more than 15%, deployment; otherwise, abandonment. Result at 3 months: 11% average improvement, below the threshold. Decision to abandon taken in committee, with capitalisation of learnings for the next POC.

Good vs bad reflex

BAD REFLEX

Launching an AI POC as a technical showcase: choosing a demonstration case (often an internal chatbot), entrusting to a data team isolated from the business, with no pre-AI baseline or stopping criterion, and waiting 6 to 12 months to see. This pattern produces the 80% failure rate documented by RAND: successful demo, impossible transition to production, abandonment for lack of initial framing. Average cost lost: 4.2 million dollars according to S&P Global 2025.

GOOD REFLEX

Launching an AI POC as a business experiment: narrow perimeter (10 to 20 users maximum), 3 months of testing, solid pre-AI baseline over 6 months, criteria for continuation or abandonment defined and written before the start, transition to production pre-planned if criteria are met. Accept abandonment as a legitimate outcome. A POC abandoned in 3 months for 30,000 euros is an operational success; a POC continued for 12 months at a loss is a strategic failure.

Sources

The Root Causes of Failure for Artificial Intelligence Projects and How They Can Succeed, RAND Corporation, 2024 (analysis extended to 2,400+ initiatives, 2025). https://www.rand.org/pubs/research_reports/RRA2680-1.html (accessed 2026-05-24)
Project NANDA, The GenAI Divide, MIT, July 2025. https://nanda.media.mit.edu/ (accessed 2026-05-24)

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What is an AI POC? Definition and right instinct vs wrong instinct

Concrete example

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Sources