An AI ROI business case builder turns scattered estimates into the numbers a board actually asks for: payback period, return on investment, and net present value. Many AI pilots stall not because the idea is weak but because nobody put a defensible financial case behind it. This tool does the arithmetic so you can focus on getting the assumptions right.
How it works
You enter four figures: the one-off implementation cost, the recurring annual running cost, the expected annual productivity savings, and any annual revenue uplift. The tool computes the net annual benefit (savings plus revenue minus running cost), then derives the payback period by dividing the upfront cost by that benefit. It computes ROI over your chosen horizon and a simple NPV that discounts each year’s benefit by a rate you set and subtracts the upfront cost. All maths runs in your browser, so your numbers never leave your machine.
Tips and examples
Use conservative inputs — a case that survives pessimistic assumptions is far more persuasive than an optimistic one that collapses under a question. Separate hard savings (hours removed, licences retired) from soft benefits (faster turnaround) and, if challenged, be ready to defend the case on hard savings alone. Stress-test by raising the discount rate and shrinking the benefits; if NPV stays positive, the project is robust. Pair this with the AI use case library to pick high-ROI candidates, and revisit the model after a pilot with measured rather than estimated figures so the full rollout case is grounded in evidence.
Building inputs you can defend
The business case is only as trustworthy as its inputs, and a board or CFO will probe each number. Knowing how to construct defensible estimates matters as much as understanding the formulas.
Implementation cost should include everything incurred before the project is live: software licences, infrastructure setup, integration development, data preparation, change management, and training. A common mistake is estimating only the vendor fee and forgetting the internal engineering time. For example, a tool that costs £20,000 per year in licence fees might require three months of a senior engineer’s time to integrate — easily another £30,000 in allocated cost that changes the payback calculation significantly.
Annual running cost includes the ongoing licence, infrastructure, support, monitoring, and any internal time required to maintain and update the system. AI costs often grow with adoption — API costs are proportional to usage — so build in a realistic assumption about volume.
Productivity savings are most credible when expressed in time units first, then converted to cost. Rather than asserting “£50,000 in productivity savings,” build up from: “This process currently takes 8 analyst hours per week. The tool reduces that to 2 hours. At a fully loaded cost of £50/hour for an analyst, that is 6 hours × £50 × 52 weeks = £15,600 per year per analyst.” That chain of reasoning is auditable; a bare number is not.
Revenue uplift is harder to estimate and should be treated with more scepticism. Where possible, ground it in a specific mechanism: faster turnaround time converts a measurable number of leads that currently go cold; personalisation lifts conversion on a traffic volume you already know. Avoid estimating “improved decisions” or “better customer experience” unless you have a quantified relationship between those things and revenue.
Reading the outputs
Payback period — how long before the upfront cost is recovered. Under 18 months is generally considered attractive for technology investments. Over 3 years should prompt scrutiny of whether the benefits are realistic.
ROI — total net benefit over the horizon as a percentage of total cost. This is useful for comparison across alternative investments but depends heavily on the horizon chosen.
NPV — the present value of all future net benefits minus the upfront cost, at your discount rate. A positive NPV means the project creates economic value after accounting for the time value of money. The discount rate reflects the opportunity cost of capital — if you could get a reliable return of 10% elsewhere, projects with an NPV positive only at 6% are marginal.
A useful stress test: halve the benefits and double the implementation cost. If NPV is still positive, the case is robust. If it goes negative, the case depends on assumptions being right — and you should say so explicitly.