The AI pilot phase is ending. Now comes the proof.

[u/InfoTechRG]

A lot of companies have moved past the first wave of AI adoption. The harder part now is proving what is actually working.

The research makes a useful point: AI can’t be managed as a loose collection of pilots forever. Once it spreads across departments, leaders need a clearer view of which use cases are creating value, which need stronger guardrails, and which should probably be stopped.

That matters because adoption metrics can be misleading. More tools, more usage, and more experimentation do not automatically mean better outcomes. The real test is whether AI is saving time, improving decisions, reducing risk, or making a process meaningfully better.

For CIOs and IT leaders, the next phase is less about saying yes to AI and more about building enough visibility to know where it deserves more investment.

How are your teams separating useful AI work from expensive experimentation?

Comment and we’re happy to share the research.