Tool / 02 · AI
Does the cost outweigh the benefit?
Most AI business cases count the license and the hoped-for savings. This one also counts adoption, review time, integration, and security, the parts that decide whether it actually pays.
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Results
Pays back in 7 months
Reasonable, but sensitive to adoption and review overhead. Measure both during a pilot.
- Hours saved / month
- 91
- Net / month (full adoption)
- $5,575
- One-time cost
- $27,500
- 36-month net
- $166,375
- 36-month ROI
- 229%
- Break-even time saved
- 6.1%
Show the math
- Hours saved = people × adoption × hours/week × 4.33 × time saved × (1 − review overhead)
- Monthly value = hours saved × loaded rate = $6,825
- Monthly cost = seats × license + upkeep = $1,250
- One-time = setup + security review + training ($7,500) = $27,500
- Adoption ramps over the first three months (⅓, ⅔, full).
Reading the result
Where AI earns its keep.
The math only works when the task is frequent, the output is checkable, and the data can safely go where the tool runs.
Tends to pay off
- High-volume text workDrafting, summarizing, and reformatting that people do many times a week.
- Search across your own documentsFinding the answer buried in policies, specs, or past proposals.
- Code assistance with reviewBoilerplate, tests, and refactoring, with engineers still owning the result.
- First-pass triageSorting tickets, inquiries, or logs so people start from a shortlist.
Often doesn’t
- Low-volume or one-off tasksSetup and oversight cost more than the minutes saved.
- High-stakes output that needs full reviewIf every line must be checked, the savings mostly disappear.
- Messy or scattered dataThe real project becomes data cleanup — budget for it honestly.
- Regulated data you cannot shareCUI, ITAR, health, or client data may require approved environments that change the cost picture.
Hidden costs
What most estimates leave out.
Before you sign, put a number, even a rough one, next to each of these.
- Data cleanup and access permissions before the tool is useful
- Integration with the systems people already use
- Security, privacy, and contract review of the vendor and its data terms
- Time spent checking and correcting output (the “review tax”)
- Workflow and prompt upkeep as models and vendors change
- Monitoring, logging, and an owner who answers for the system
- Usage-based charges that grow faster than seat counts
The other side of the ledger
The benefit can become the risk.
Read our field notes on the security cost of AI integration.