Beyond Tokenmaxxing: Measuring Enterprise Generative AI Net Business Value
| Scale Tier | Volume | Inference Cost | Escalation Cost | Fixed Amort. | Total Cost/Task | Net ROI |
|---|
Methodology: Evaluates total cost of ownership (TCO) beyond raw LLM API consumption. Incorporates human-in-the-loop review penalties ($ / failed task routing), fixed tooling amortizations, and labor displacement thresholds to deliver verifiable bottom-line enterprise returns.
Enterprise generative artificial intelligence evaluations often fixate on raw token costs, yet inference represents merely a fraction of total operating expenditures. When automation accuracy sits at seventy-eight percent, the remaining twenty-two percent of failed tasks escalate to human reviewers at eight dollars and twenty cents each. Adding fixed tooling and engineering overhead yields total operating expenses, which subtract from displaced labor to deliver over one point one million dollars in net monthly value. Adjusting task volume or workflow accuracy dynamically recomputes the breakeven threshold and unit return on investment across every operational tier.