How to calculate the ROI of an AI implementation without '10x' promises?

What really goes into the implementation cost?

Include data preparation, process analysis, integrations, interface, testing, training, and deployment. After launch, add costs for models, infrastructure, monitoring, connector maintenance, and updating test examples. A separate item is the time of a specialist verifying the result. This cost is easily overlooked when the demo only shows answer generation.

Also record the costs of leaving the process unchanged: growing queues, erroneous data, and multiple handling of the same case. Not every loss can be reliably valued. In such cases, present it as a separate operational metric. It is better to keep an honest unknown than to insert a convincing number without basis.

Context and references: FinOps Foundation: FinOps Framework

A step-by-step sample calculation

Let us assume 1,000 cases per month for demonstration purposes. Current handling takes 12 minutes, while after the change it takes 5 minutes, including verification. The difference is approximately 117 hours. At an agreed labor cost of 80 PLN per hour, this amounts to approximately 9,333 PLN in time value. These are assumptions for calculation, not an ALGOV implementation result or a forecast for your company.

If the current solution costs 3,000 PLN per month, the remaining net time value is approximately 6,333 PLN per month. With an initial investment of 40,000 PLN, a simple ratio gives approximately 6.3 months. This is the payback period calculated on the value of freed-up work, not a guaranteed cash return. If the team utilizes only half of this time, the calculation will be significantly less favorable.

How to distinguish ROI from a flashy presentation?

ROI for a selected period can be expressed as: benefits minus all costs, divided by all costs. The payback period answers a different question: when the cumulative benefit covers the investment. Do not use these terms interchangeably. In the model, account for the gradual increase in adoption, not full efficiency from day one.

Prepare three variants: conservative, base, and favorable. Change primarily the volume, control time, share of exceptions, and user utilization. The token rate is often less significant than an additional two minutes of manual verification for each case. Check which variable most significantly changes the investment decision.

How to gather evidence before a larger expenditure?

The pilot should answer the most expensive unknowns. If it is unknown whether documents can be read correctly, test the documents. If the problem is team work in two systems, check the integration and interface. Do not build an elaborate dashboard when the basic calculation still depends on unverified quality.

After the pilot, return to the same assumptions. Show the difference between the forecast and the measurement and explain its cause. Set a date for the next review after implementation. The business sense of the project may change with seasonality, supplier pricing, or process scope. The decision owner should see these changes without ordering a new analysis.