From Hype to Chaos: AI Failures in Large Companies — and What They Teach Us

In the talk, we will examine the biggest corporate mistakes in AI adoption using real-world case studies — from flawed recommendation models and biased HR automation to autonomous system failures and risky predictive algorithms. By breaking down what exactly went wrong, we will reveal recurring patterns: data biases, weak metrics, lack of oversight, and unrealistic expectations about AI capabilities.
Yet the overarching message is constructive: AI is an extraordinary, highly valuable technology, and organisations absolutely should adopt it — but they must do it wisely. With thoughtful data practices, solid processes, robust testing, and a clear understanding of its limitations, AI becomes a driver of growth rather than a source of risk. These cases will show how to harness AI effectively while avoiding costly failures.