AI is not successful because it is “implemented.”
AI is successful only when it moves a business metric that matters.

Executives need clarity on what “impact” looks like, before deployment, not after.

Shift from Activity Metrics to Outcome Metrics

Most companies measure:

• number of models developed
• number of PoCs launched
• number of use cases identified

These are activity metrics.
Investors and boards care about financial & operational impact.

Examples of real AI impact:

• % reduction in claim processing time
• % increase in lead-to-conversion rate
• % improvement in underwriting accuracy
• cost per support interaction reduced
• churn reduction in premium segments

A Simple ROI Formula for Executives

ROI = (Value Generated – Cost of Implementation) / Cost of Implementation

Value Generated must be tangible:

• saved hours converted to ₹ / $
• reduced operational leakage
• revenue uplift from personalization upsells
• fraud avoided
• FTE redeployment

If you can’t measure value → it’s not a priority use case, yet.

Executive Mindset

AI ROI is strongest when:

• scope is narrow
• deployment is iterative
• measurement is tracked weekly
• success leads to expansion into adjacent processes

Start small.
Prove value fast.
Expand only after metrics show lift.