How IT leaders can measure and improve agentic AI value and cost

Token prices are down 75%. Enterprise AI bills have tripled. If that math doesn't add up for your organization, this guide explains why and hands you the tools to fix it.

You'll learn the four metrics that replace token spend as a unit of value, measuring cost per completed task, retrieval efficiency, quality-adjusted efficiency, and the business value multiple your board actually cares about.

More than a scorecard, this guide is a diagnostic system. A weak score on any metric points directly to one of five levers that will move it, whether the problem is context bloat, over-provisioned models, shallow workflow integration, or governance gaps that show up as cost spikes long before they surface in a compliance report. Build the measurement layer first, and the ROI question stops being a matter of opinion.

Discover the:

  • Four metrics that replace token spend with cost per completed task as the real unit of value
  • Diagnostic system that turns a weak ROI score into a clear next action
  • Five levers that help you address weak points and cut cost per task, from context engineering to multimodel routing
  • Observability gap most enterprises haven't closed, and why it blocks defensible ROI

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