AI ROI
The business return generated by an AI deployment minus its full cost — model spend, infra, integration, change management, and risk. The 2026 procurement north-star metric.
AI ROI is what enterprise buyers actually optimize for in 2026 — not raw cost, not feature lists, not benchmark scores. The numerator: time saved, deflection, revenue lift, error reduction, employee productivity. The denominator: model spend, platform fees, integration cost, change management, governance overhead, and incident cost.
The honest ROI calculation includes things vendors don't advertise: the integration eats 2–4× the platform fee in year one; change management eats another 1–2×; and 5–15% of agent outputs need human correction in the first quarter, with that ratio dropping over time.
Vendors that win in 2026 publish ROI worksheets, instrument the buyer's metrics during the pilot, and present outcome-not-usage reports. Buyers that win build their own ROI model first, then test vendors against it — not the other way around.
Frequently asked
What is a realistic AI ROI for a 2026 enterprise deployment?+
For well-scoped use cases: 3–10× return in year one is common; 1.5–3× is good; below 1.5× usually means the use case was wrong, not the technology. Headline 100× claims are almost always partial-cost accounting.
What costs do AI ROI calculations usually miss?+
Integration engineering, ongoing prompt and eval maintenance, agent observability, incident response, change management, and the productivity tax during user onboarding. These typically add 50–150% to the model spend.