DOI: 10.1177/00187208261474345 ISSN: 0018-7208

Cognitive Readiness for Human-AI Collaboration

Sébastien Tremblay, Delphine de Hemptinne, Gabrielle Teyssier-Roberge, Adèle Gallant, Alexandre Marois, Daniel Lafond

Objective

This narrative review examines the cognitive, metacognitive, and team competency requirements that may contribute to productive and reliable collaboration between human and AI to address two questions: What capabilities make AI a competent collaborator? What makes humans ready for AI collaboration?

Background

As AI systems are increasingly integrated into workplaces and framed as teammates rather than tools, humans face challenges that include maintaining situation awareness, calibrating trust, and working with systems that may surpass them cognitively. We analyzed Human-Agent Teaming (HAT) readiness around two complementary levels: operational team competencies (communication, coordination, and adaptability) and regulatory capacities (trust calibration and metacognitive awareness).

Method

We conducted a structured narrative review of literature from 2010 through January 2026, searching Google Scholar, Scopus, PsycINFO, IEEE Xplore, ACM Digital Library, and Semantic Scholar, complemented by forward citation tracking. After screening 572 records, 192 articles were included for synthesis.

Results

Communication inflexibility, limited shared understanding, and trust miscalibration emerge as recurring barriers to HAT, while regulatory capacities (trust calibration and metacognitive awareness) represent particularly critical dimensions of HAT readiness that remain to be fully operationalized.

Conclusion

HAT requires mutual readiness, with both humans and AI developing metacognitive and adaptive capabilities. Despite methodological heterogeneity limiting clear conclusions, cross-training and co-learning methods offer a promising avenue for building shared understanding and calibrated collaboration.

Application

This review provides practical principles for designing AI systems that support calibrated collaboration and for preparing humans to work adaptively with AI, thereby enhancing team effectiveness, reliability, and resilience in collaborative work environments.

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