Three Approaches to Measuring and Managing AI ROI
Executive Take
A generic AI rollout without a matching measurement framework is why so many pilots stall the framework here forces a choice between fast, comparable proof points now and rigorous portfolio governance later, and few companies can do both at once.
Executive Summary
MIT Sloan Management Review, based on interviews with 30+ CEOs and senior leaders, outlines three approaches companies use to measure AI ROI: function-focused (single-department metrics like response time), coordinated (shared platforms across teams, e.g., JPMorgan Chase's LLM Suite with 200,000+ users), and enterprise portfolio (NPV/IRR-based governance, as at Morgan Stanley). Companies typically progress through all three stages.
Why It Matters
Technology and finance leaders are under pressure to justify AI spend with the same discipline applied to capital projects, and this piece gives them a concrete maturity model rather than another call to "invest more." HR leaders should note the Unilever recruitment example as a rare case of function-level AI ROI translated into hard hiring-cost savings.