AI ROI is notoriously hard to measure and easy to fake. "Hours saved" estimates from surveys are usually inflated. The metrics that actually hold up: time-to-completion for a specific task measured before and after (A/B test with and without AI), error rate on a defined set of tasks, throughput (how many units processed per person per day), and cost per outcome.
The honest math: if AI saves a knowledge worker 2 hours per day at $60/hour loaded cost, that's $31,200/year per person before AI cost. If the AI tool costs $2,400/year per seat, the net benefit is $28,800 — but only if those 2 hours are redirected to productive work rather than absorbed into other tasks.
Most AI ROI cases look better when you frame them as "enabling growth without headcount" rather than "replacing headcount." Measuring and communicating AI ROI is as much a change management task as a finance one.
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