Integrating AI into a Product: 9 Mistakes by Product Managers

Integrating artificial intelligence into modern products often turns into an expensive experiment that fails to deliver tangible business value. This article examines nine critical mistakes product managers make when integrating AI technologies. The author analyzes a wide range of issues, from selecting the wrong problem to solve and poor data preparation, to challenges in evaluating performance metrics, project economics, and quality control of neural network functions. The material helps readers avoid common traps associated with AI hype and focus on building truly useful tools. The article is intended for product managers, technical leads, and entrepreneurs planning to implement AI in their products, as it offers a structured approach to risk assessment and development process optimization throughout the product lifecycle.