Interactive essay · synthetic scenarios
Where does enterprise AI value go?
A successful automated case can be cheap. The business case still depends on how many people use the system, how often exceptions occur, and how much work those exceptions create.
Start with the operating model
Consider a team processing a thousand cases each month. An AI system handles some of them, while people continue to handle the rest. Among the adopted cases, a proportion needs human review. Change those assumptions below and watch the operating model move.
Try the operating model
All values are illustrative. Currency is USD; change the costs to fit your own model.
| Fully manual baseline | $20,000 |
|---|---|
| Unadopted cases: labour | $8,000 |
| Exception review: labour | $4,500 |
| AI usage | $600 |
| Fixed operating cost | $2,000 |
| Total with AI | $15,100 |
Follow the exception work
The starting scenario appears attractive. Yet a higher review rate or a longer review process can absorb the time saved by successful automation. An evaluation should measure recovery cost alongside answer quality.
Adoption matters for a different reason. Fixed operating costs are paid even when few cases use the system. A technically sound product can therefore have weak economics until enough suitable work passes through it.
Released capacity is an operating option. Turning it into financial value requires a separate plan: more throughput, shorter turnaround, less overtime, or other measurable work. A modelled labour difference alone does not establish realised savings.
Model and assumptions
Manual baseline hours = cases × manual minutes ÷ 60. Adopted cases = cases × adoption. Remaining manual hours = unadopted cases × manual minutes ÷ 60. Review hours = adopted cases × exception rate × review minutes ÷ 60.
Net benefit = baseline labour cost − remaining manual labour − review labour − AI usage − fixed operating cost. Where per-case value is positive, break-even adoption = fixed cost ÷ (monthly cases × value per adopted case). Per-case value is avoided manual labour minus expected review labour and AI cost.
With zero fixed cost and negative per-case value, only zero adoption breaks even; additional adoption reduces benefit. With zero fixed cost and zero per-case value, every adoption level breaks even. “Not reachable” means no adoption level between zero and 100% breaks even.
Adopted cases without exceptions are assumed to need no additional human handling. The model assumes constant volume, average labour rates and linear costs. Include residual handling in expected review time or extend the model if needed. Up-front implementation, quality failures outside review, transition effort and demand changes are excluded. No customer outcomes or deployed product performance are represented.
What to measure next
Measure adoption on eligible work, the share of cases needing intervention, and the minutes required to resolve them. Then test whether released capacity creates an outcome anyone values. Those observations give a stronger business case than multiplying a successful demonstration by the size of a team.
This is an illustrative operating model, not observed ROI. Its assumptions are synthetic. Your scenario stays in this page and is not uploaded.
Sources and attribution
This is an original, self-published piece by Vihang Patel. The sources below support the referenced frameworks; fictional examples and personal judgments are identified in the text.