Beyond Assumptions: Understanding Biases in AI Project Management

Claudia is the AI Product Manager for the Project Management Institute.

  Artificial Intelligence  

Have you ever thought that your project’s underperformance could stem from underlying root causes that you often do not pay attention to?

This could be the case: You are the owner of a startup, and the next round is decisive for launching your idea. You believe in it, and your team is amazing. Although invoicing in the first year could be quite tough, you forecast $1M for your investors. You get that round, but after six months, you realize you were too optimistic—and you lose your investors' help.

You might be tempted to think that your estimations were not good, that you are not experienced. But from a behavioral point of view, you were simply too optimistic, carried away by your enthusiasm. What happened to you is called optimism bias. It is not deliberate, but was the origin of your wrong estimations.

This behavioral approach to project management is nothing new. Authors like Kahneman, Gigerenzer, Klein and Tali have generated worthy reading currents of thought and nuances on the topic. Bent Flyvbjerg even described the “Top 10 Behavioral Biases in Project Management.”

With the advent of generative AI and its applications to project management, I started to wonder if there was any special behavioral bias that we need to pay more attention to, a bias that can lead us to think that we are not managing effectively in an AI context. The …

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