A Simple ROI Framework to Decide Whether to Build an AI Agent

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Before building an AI agent, teams should compare the true cost of the manual process — including labor, error correction, and opportunity cost — against the one-time build cost and ongoing per-unit inference cost. The break-even volume formula divides build cost by the savings per unit, revealing how many task completions are needed to recoup the investment. For example, a $6,000 build cost with $4.35 saved per unit breaks even at roughly 1,380 units, making high-volume tasks far more viable candidates. Developers are advised to run 100–200 real inputs through the actual model to get accurate per-run costs, rather than relying on estimates that can distort the math. Low-volume or highly variable tasks often fail to clear the break-even threshold within a reasonable timeframe, making them poor candidates for automation.

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