How to Build an ROI Case for AI

Before any AI project gets approved, someone has to justify the investment. We walk through the ROI framework we use with every client — from baselining current costs to projecting realistic returns.

Why most ROI cases for AI fail to land

The typical AI ROI case is built backwards: a vendor presents a technology, estimates a percentage improvement in productivity, and asks a decision-maker to approve a budget. The decision-maker has no way to verify the productivity estimate, no confidence in the projection, and no clear accountability if it turns out to be wrong. The case fails — or if it is approved, it fails to deliver.

A credible ROI case runs in the opposite direction: start with a specific operational cost that can be measured, define what the improved state looks like, and calculate the difference. The technology is selected to close the gap between those two states. The ROI is then a function of the cost gap and the implementation cost — not a vendor promise.

Step 1: Baseline the current cost

Choose one process to model. Document the current state: how many hours per week are spent on it, who performs it, what is the fully-loaded cost rate of those people, and what are the downstream costs of errors and delays. Sum those figures to produce an annual cost. This is your baseline.

For most processes, this exercise takes half a day and produces a number that surprises the people doing it. Manual processes accrete cost invisibly over time.

Step 2: Define the improved state

Define what the process looks like if automated. How many hours per week will it require? What is the residual error rate? What downstream costs are eliminated? Translate all of this into an annual cost figure. This is your target state.

Be conservative. If you are uncertain, bias your projections toward the lower end of the benefit range. An ROI case that underestimates and overdelivers is more valuable than one that does the reverse.

Step 3: Calculate the annual saving

Subtract the target state cost from the baseline cost. This is your annual gross saving. For most automation projects, this figure is between $20,000 and $150,000 per year, depending on the volume and complexity of the process.

Step 4: Factor in implementation cost

Include the full implementation cost: design, build, testing, deployment, and first year of support. Divide the annual saving by the implementation cost to produce a payback period. For well-defined processes, a payback period of six to twelve months is typical. Anything under eighteen months is generally financeable.

Step 5: Present to the right decision-maker in the right frame

An ROI case presented to a finance director should lead with the cost reduction and payback period. One presented to an operations director should lead with the process improvement metrics. One presented to a CEO should emphasize the strategic capacity created by freeing up the team. The numbers are the same; the frame changes.

The strongest ROI cases we have seen are also the simplest: one process, one baseline, one target state, one payback period. Complexity creates doubt. Simplicity creates conviction.

We build the ROI case before we build anything else. Start with a discovery call →