Research Identifies 3 AI ROI Approaches After 30 Executive Interviews
Updated
Updated · MIT Sloan Management Review · Jun 23
Research Identifies 3 AI ROI Approaches After 30 Executive Interviews
3 articles · Updated · MIT Sloan Management Review · Jun 23
Summary
More than 30 CEO and senior-leader interviews found companies still lack a standard way to measure returns on AI, leaving many investments judged inconsistently or not at all.
The research outlines three practical approaches to measuring and managing AI ROI, aimed at helping companies match metrics to their current AI maturity and strategic goals.
Analytical AI often yields more directly attributable financial gains in narrow use cases, while Generative AI tends to improve speed, quality or output and requires extra work to convert those gains into financial impact.
Industry context also changes what counts as return: consumer goods companies may track supply-chain responsiveness, while B2B marketing firms may focus on proposal win rates, lead conversion or creative throughput.
The broader finding is that companies treating AI less rigorously than other capital investments — or deploying generic tools without explicit ROI plans — rarely achieve durable, credible returns.