AI Essentials for Tech Executives

Chapter 2. The #1 Mistake Companies Make with AI

One of the first questions I ask tech leaders is how they plan to improve AI reliability, performance, or user satisfaction. If the answer is “We just bought XYZ tool for that, so we’re good,” I know they’re headed for trouble. Focusing on tools over processes is a red flag and the biggest mistake I see executives make when it comes to AI.

Improvement Requires Process

Assuming that buying a tool will solve your AI problems is like joining a gym but not actually going. You’re not going to see improvement by just throwing money at the problem. Tools are only the first step; the real work comes after. For example, the metrics that come built-in to many tools rarely correlate with what you actually care about. Instead, you need to design metrics that are specific to your business, along with tests to evaluate your AI’s performance.

The data you get from these tests should also be reviewed regularly to make sure you’re on track. No matter what area of AI you’re working on—model evaluation, retrieval-augmented generation (RAG), or prompting strategies—the process is what matters most. Of course, there’s more to making improvements than just relying on tools and metrics. You also need to develop and follow processes.

Rechat’s Success Story

Rechat is a great example of how focusing on processes can lead to real improvements. The company decided to build an AI agent for real estate agents to help with a large variety of tasks related ...