See which of your AI agents made money.
Model your number now, or start with a read-only assessment that maps every agent you run and shows what each costs and returns, no integration, results in days.
How to prove the ROI of an AI agent.
Agent ROI is the agent's measured business output divided by its full cost.
Capture the full cost of each agent, tokens, compute, tools and APIs, normalized to one currency view across every platform.
Capture the business output claims resolved, invoices matched, tickets deflected, downtime avoided.
Apply an explicit value-per-output assumption that's editable and auditable, agreed with your finance team, not an unauditable number.
Roll it up by agent, team and department.
Onepane meters both sides per agent, so the return survives CFO scrutiny. What is agent ROI?
Where the return is hiding.
A typical large enterprise leaves ~$8M a year on the table (illustrative). Adjust the inputs to model your own.
Start with a read-only Agent ROI Assessment.
- Read-only access, no production impact, your data stays in your environment.
- We map every agent you're running and show what each costs and returns.
- A shareable result in days, approvable in one meeting.
We reply within one business day.
Methodology and sources.
Last updated: June 26, 2026
- ~150 agents under management
- Enterprise AI budget ~$10M/yr ($5M AI-operations + $4M agent pilots + $1M platform/tooling)
- Total IT budget ~$50M, with ~35% (~$17.5M) on legacy maintenance
- Benchmark context: large enterprises plan $50-250M/yr on GenAI (KPMG)
| Lever | How it's calculated | Source |
|---|---|---|
| Consolidate siloed / duplicate agents (~$1.0M) | ~20% of ~$5M AI-ops spend | Deloitte, AI agent orchestration |
| Move stalled pilots to production (~$1.6M) | Recover ~40% of ~$4M pilot write-off | MIT NANDA 2025 |
| Reactivate stranded agents (~$0.8M) | Half of agents sit unused; universal tag makes them findable | Gartner, agent sprawl |
| Modernize legacy workflows (~$1.8M) | Reclaim ~10% of the ~$17.5M legacy line | McKinsey / Gartner (tech debt ~40% of IT budget) |
| Cut agent-incident cost (~$3.0M) | Lower frequency and blast radius of incidents | Gartner (40% of agentic projects canceled by 2027) |
| Total | ~$8M / year |
All figures illustrative, value pools Onepane helps capture, not guaranteed savings; validated per account.
Where these numbers come from.
- MIT NANDA, "The GenAI Divide: State of AI in Business 2025" →
- Gartner, "Over 40% of Agentic AI Projects Will Be Canceled by End of 2027" (Jun 2025) →
- Gartner, "Six Steps to Manage AI Agent Sprawl" →
- McKinsey, 88% of organizations use AI, ~23% scaling agentic systems (State of AI) →
- Forrester Predictions 2026, agentic AI's "year of reckoning"
- ISG, "Enterprise AI Spending to Rise 5.7% in 2025" →
Agent ROI questions.
What is a good ROI for an AI agent?
There's no single benchmark yet, agent ROI varies by use case and the value-per-output assumption. What matters is that the number is auditable: a return tied to measured business output and full cost, with the assumption visible and agreed by finance. A vanity number that can't survive scrutiny is worse than none.
How long does it take to prove agent ROI with Onepane?
The read-only assessment returns a first attributed-return view in days, with no integration. Continuous per-agent ROI follows once platforms are connected.
Is the read-only assessment safe to run?
Yes. It's read-only with no production impact, and your operational data stays in your environment.