Introduction

Companies are investing more in artificial intelligence, yet many cannot answer a basic question: how much return is that investment generating? Without a clear way to measure AI ROI, projects are judged by instinct and are the first to be cut when priorities shift.

Unlike other technology projects, AI mixes visible costs, such as development and infrastructure, with less obvious ones, such as maintenance, human oversight and change management. Its benefits also go beyond saved time: they include fewer errors, higher revenue and lower risk.

This whitepaper shows how to measure AI ROI with a practical framework, from setting the baseline to tracking results. It includes a formula, an illustrative example, a checklist and the most common mistakes to avoid. It is written for technology, finance and operations leaders who need to justify and prioritize AI initiatives.

What You'll Learn

• How to set a baseline before launching an AI project.
• Which build, run and change costs belong in the calculation.
• Which benefits to measure: time, errors, revenue and risk.
• How to use the ROI formula as a simple AI ROI calculator, with a step-by-step example.
• Which mistakes to avoid when presenting results to leadership.