Create a sensitivity table that shows how AI ROI changes under different adoption and capture assumptions.
An AI coding assistant has $180,000 annual fully loaded cost. Base benefit depends on adoption and captured productivity. Leaders need to know whether the ROI survives downside. Sensitivity analysis: vary the uncertain assumptions that drive benefits or costs, then compare low, base, and high cases. The common trap is defending one precise ROI number as if uncertain adoption, capture, and review burden are already known facts. Set low case Benefit $202,000, cost $180,000, net $22,000, ROI = 12%. Low case assumes slower adoption, lower capture, and higher review burden. Set base case Benefit $320,000, cost $180,000, net $140,000, ROI =…
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