A metacognitive competency defined as the ability to move fluidly between different perspectives, analytical frameworks, and modes of reasoning — without anchoring prematurely to a single interpretation.
In human-AI collaboration, cognitive flexibility determines how a person responds to AI outputs. Those with low cognitive flexibility tend to treat AI responses as conclusions. Those with high cognitive flexibility treat them as scaffolding — a starting point to be interrogated, challenged, and refined.
Research finding: Studies on early adopters of AI tools show that openness to experience — one of the strongest predictors of cognitive flexibility — correlates directly with measurable differences in output quality when working with AI. The tool is the same. The mind using it is not.
Distinction from adaptability: Cognitive flexibility operates at the level of thinking itself — the willingness to question one's own framing. Adaptability operates at the level of behaviour. You can adapt your actions without ever questioning your assumptions. Cognitive flexibility demands questioning the assumptions.
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Related concepts
One of the five metacognitive competencies identified in research on mental models in the AI era. Linked to Ambiguity Navigation (which requires flexibility as a prerequisite) and to Cognitive Sovereignty (which depends on the ability to evaluate AI outputs critically rather than defer to them).