Reframe AI Costs as Human-Time to Drive Smarter Adoption, Not Fear

A developer argues that displaying AI costs in raw dollars causes cautious employees to reduce usage while careless ones continue overspending, worsening overall cost-efficiency. Token counts offer little insight into output quality, and dollar figures become hard to contextualise once costs scale into the thousands across a team. The proposed alternative is a unit called 'Human-Time,' which anchors AI spend to the fully loaded annual cost of a mid-level employee — roughly $50,000 — breaking it down into human-days, hours, minutes, and seconds. Under this framework, a $25 AI task equates to one human-hour, making it intuitive to judge whether the output justified the expense. The goal is to give teams a relatable benchmark that encourages thoughtful use rather than either reckless spending or paralysed under-adoption.