The 8 Risks of A.I. in Project Management (PMP 2026)

If you are taking your PMP exam after July 2026, artificial intelligence questions will likely appear. Understanding these ethical considerations is essential, and here are the key concerns you’ll need to know.

Bias in Data

AI models trained on only certain data sets will produce biased data, and will replicate and amplify that bias in their outputs. This has been shown recently in AI Hiring Decisions, where bias was shown against different groups of people that didn’t necessarily have anything to do with their skill or will to perform the work. Project managers must be aware that AI decisions may favor certain outcomes unfairly.

Privacy

Protecting customer data and sensitive project information is critical. AI systems that process this data must have adequate privacy safeguards in place. This often comes from paid models or enterprise models that allow a certain level of privacy, and stops the model being trained on your project’s information.

Transparency

AI decisions are often difficult to explain or understand. Project managers will often need to know why the system recommended a particular course of action before approving it, in case someone questions that decision later on.

Accountability

When something goes wrong, who is responsible? Accountability structures must be clear before deploying AI in project decision-making.

Copyright Concerns

AI tools trained on copyrighted material raise legal and ethical questions about ownership and attribution of generated outputs.

Reliability

AI can produce confident but incorrect answers, a phenomenon known as hallucination. Project managers must verify outputs before acting on them.

Sustainability

Generating AI outputs requires significant computational resources and energy consumption. The environmental impact should be considered.

These ethical considerations are worth knowing for the 2026 PMP exam and for managing AI responsibly in real projects.

– David McLachlan

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