AI ROI benchmark · Local service businesses
Local service business AI ROI benchmark
Estimate savings from lead intake, estimate follow-up, and office documentation without automating commitments a field team must honor.
Modeled result
This is a planning scenario, not a market average. Replace every input before making a purchase decision.
| Current labor on the workflow | 240 hours/month |
|---|---|
| Loaded labor cost | $30/hour |
| Share suitable for AI assistance | 40% |
| Productivity lift on that share | 18% |
| Savings realized in practice | 50% |
| Software and usage cost | $250/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
- Draft replies to common lead questions
- Summarize calls into job notes
- Prepare estimate follow-ups from approved prices
Keep a human decision
- Promise appointment times without live availability
- Diagnose safety-critical work from a customer description
Evidence and limits
There is no direct field benchmark here for local service companies. The model uses adjacent support and writing evidence, then discounts both scope and realization.
- Generative AI at WorkNBER working paper 31161; later published in the Quarterly Journal of Economics · Published 2023-04-24
A field study of 5,179 customer-support agents found a 14% average productivity increase, with larger gains for less-experienced workers.
- Experimental Evidence on the Productivity Effects of Generative Artificial IntelligenceScience · Published 2023-07-13
In preregistered writing tasks with 453 college-educated professionals, ChatGPT reduced completion time by 40% and raised rated output quality by 18%.
Read the full methodology, compare the other function benchmarks, or test a 30-day pilot against your own baseline.