The problem isn't the math. It's being asked to do it before anything has settled.
Most leaders aren't avoiding ROI because they dislike numbers. They're asked to calculate value before they understand what's actually changing — and AI makes that worse, not because it's unmeasurable, but because its early impact doesn't look like traditional ROI at all.
What comes out of premature math is familiar: spreadsheets that look precise but aren't, stories people feel pressured to defend, or paralysis because nothing feels provable. None of it improves the decision. There's a second sequencing error underneath it — early ROI lives at the work level, not the vendor level. Jump straight to comparing tools and you end up measuring features and price points instead of whether the underlying use case is worth optimizing at all.
The organizations that get this right aren't the ones with the best measurement stack. They're the ones who ask a smaller question first: is this AI-assisted work becoming meaningfully different — and how would we know?
The latest navaroAI issue, The ROI Mini-Model: Time, Cost, Quality, examines how to measure AI-assisted work honestly and defensibly — and why that has to happen before dashboards, calculators, or tool comparisons make any sense.
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Educational content only. Not legal, regulatory, financial, or professional advice.
