AI ROI benchmark · Operations
Operations AI ROI benchmark
A model for SOP lookup, incident summaries, and routine reporting where outputs can be checked against operational systems.
Modeled result
This is a planning scenario, not a market average. Replace every input before making a purchase decision.
| Current labor on the workflow | 600 hours/month |
|---|---|
| Loaded labor cost | $42/hour |
| Share suitable for AI assistance | 30% |
| Productivity lift on that share | 15% |
| Savings realized in practice | 55% |
| Software and usage cost | $500/month |
Monthly gross value = current hours × loaded cost × addressable share × productivity lift × realization rate. Net value subtracts software cost. Capacity has value only if the business can redeploy it, avoid new cost, or produce more useful work.
Run your own numbersWhere to use it
Good pilot candidates
- Retrieve steps from approved SOPs
- Draft incident timelines from system records
- Prepare recurring status reports from verified inputs
Keep a human decision
- Change production settings from free-form instructions
- Treat generated summaries as the system of record
Evidence and limits
General workplace studies do not prove an operations benchmark. The assumed lift is deliberately modest and applies only to document-heavy work.
- Generative AI in Real-World WorkplacesMicrosoft Research · Published 2024-07-31
A set of randomized field experiments across more than 6,000 workers found AI access increased document editing but did not establish a universal company-level ROI.
- Navigating the Jagged Technological FrontierHarvard Business School working paper; later published in Organization Science 37(2) · Published 2023-09-15
A field experiment with 758 consultants found faster, higher-quality work inside the model capability frontier and worse accuracy on a task outside it.
Read the full methodology, compare the other function benchmarks, or test a 30-day pilot against your own baseline.