How Organizations Measure and Maximize Value from Artificial Intelligence
A global survey of 1,006 executives across 11 countries reveals why 90% of organizations report AI value but only 16% are capturing it systematically
This research challenges assumptions driving most AI investment decisions today.
The measurement gap is larger than most executives realize.
Organizations that formally report AI value to their boards achieve strong returns 85% of the time. Those still running unmeasured pilots achieve them 4% of the time.
The workforce risk is already here.
A majority of organizations have already cut staff or frozen hiring based on AI productivity gains that have not yet materialized. Only 2% have made reductions tied to confirmed AI outcomes.
The most hyped AI is delivering the least value.
Generative AI dominates boardroom conversations, yet fewer than 1 in 10 organizations identify it as their primary source of value. Analytical AI, by contrast, is cited by 50%.
The highest-impact governance decision is almost universally ignored.
When CFOs own AI value accountability, 76% of organizations achieve strong returns. Only 2% have made that assignment.
The gap between AI investment and AI return is not a technology problem. It is a measurement, governance, and accountability problem. This report shows where it starts and what the organizations closing it are doing differently.
Research by Thomas H. Davenport (Babson College/MIT) and Laks Srinivasan (Return on AI Institute). Based on 1,006 C-suite executives across 11 countries and 32 industries. Sponsored by AI-Native by Scaled Agile.
