Ai only matters if it moves the needle on business results. Leaders should treat Ai like any other investment, with clear metrics, baselines, and accountability.

Start by defining KPIs before the project begins. Focus on metrics decision-makers care about: cost per transaction, revenue per employee, customer retention, cycle time.

Collect a baseline for these metrics, then track results after implementation. A good Ai initiative should show impact within 90–180 days.

Include both hard metrics (time saved, cost reduced, error rate lowered) and soft metrics (employee adoption, satisfaction, customer feedback).

Finally, review ROI regularly. Kill projects that aren’t performing, double down on those that are.

This discipline turns Ai from an experiment into a competitive driver, and ensures that resources are spent where they create measurable value.