The AI Product Playbook

CHAPTER 9ROI Calculation for AI Projects: Measuring the Impact and Demonstrating Value

You've identified potential AI opportunities; now comes a very important step: figuring out how to measure the value of your AI investments. This is where we talk about Return on Investment (ROI) for AI projects. Calculating ROI for AI can be more complex than for traditional software projects, but it's essential for justifying investments, securing resources, and demonstrating the impact of your work. As a Product Manager, you play a key role in defining how success will be measured.

This chapter isn't about complex financial modeling. It's about establishing a clear framework for understanding and quantifying the impact of your AI initiatives. We'll focus on defining the right metrics and establishing baselines to measure progress.

From Model Performance to Business Impact: A PM's Guide to AI Metrics

Calculating the ROI for an AI feature isn't a single formula; it's a process of connecting the model's technical performance to tangible business results. This requires understanding two layers of measurement. First, we need to evaluate the model itself—is it accurate? Is it fast? These are the model performance metrics. Second, we need to measure how that performance impacts our goals—did it reduce churn? Did it increase revenue? These are the business outcome metrics.

As a Product Manager, your very important role is to build the bridge between these two layers, demonstrating how improvements ...