We’ve started seeing a rise in AI detectors being used to vet project status reports and resumes. My concern is that the standardized language of Project Management—like using specific PMP terminology—often triggers these detectors as "machine-like." Is this hurting our ability to find qualified leads?
3 answers
Standardization is the enemy of accurate detection. In Project Management, we are trained to use very specific, repeatable phrasing for risk mitigation and stakeholder updates. Because AI detectors are trained to recognize these common patterns, they frequently flag high-quality, professional PM documentation as artificial. I’ve managed several PMO transitions where we explicitly told our recruiters to ignore AI probability scores for any candidate with a certified background, as their natural professional register is almost identical to the training data used by most generative models today.
Do you think the solution is for candidates to purposefully write with more "errors" or informal language to bypass the software?
The industry should focus on skill-based assessments instead of trying to play a cat-and-mouse game with detection algorithms.
Exactly, Patrick. A live case study or a technical interview reveals far more about a project manager's actual capability than a probabilistic scan of their CV.
That would be a step backward for professional standards, Bryan. Instead of asking candidates to change, we need to demand better transparency from the companies building these AI detectors. They need to provide "explainability" features that show exactly why a piece of text was flagged, rather than just giving a vague percentage that recruiters then use as a definitive truth.