The share of companies abandoning most of their AI initiatives before production more than doubled in one year.
S&P Global Market Intelligence surveyed 1,006 IT and business leaders across North America and Europe. In its 2025 survey, 42% of companies had abandoned the majority of their AI initiatives before production, up from 17% a year earlier. On average, 46% of projects were scrapped between proof of concept and broad adoption.
These projects did not stop at the idea. They stopped at the step after the pilot, when the system met real users, real data and real cost.
What carries an AI project across that step
- Timeouts, retries and fallbacks on every model and API call
- Guardrails, with a human review step for low-confidence answers
- Cost tracking per request, before the monthly bill arrives
- Logs and traces, so any failure can be traced to its cause quickly
None of these appear in a demo, yet each one decides whether a product holds up with its first customers.
I learned to build software in fintech, where one mistake costs real money. I bring that same standard to AI products.
A pilot proves that an idea can work. Production proves that it was engineered to.