4. Generative AI Use in the Workplace
Part 4 of 17 of a research-based series exploring AI’s impact on leadership This post summarises the article Generative artificial intelligence use in the workplace: implications for management practice by Hernández-Tamurejo et al. (2025)
If trust is the strongest predictor of GenAI acceptance, what happens when managers blindly trust outputs generated from biased data? This mixed-method study finds that trust is the strongest predictor of intention to use Generative AI (GenAI). Crucially, this trust is conditioned primarily by the perception that organizational data management routines are reliable and objective. Interestingly, employee and manager perceptions of information transparency or privacy risk were found not to directly influence trust or usage intention. This raises significant risk, as users might blindly trust GenAI outcomes due to perceived efficiency benefits, leading to doubtful content usage in management decision-making and creating integrity issues in service delivery.
This reliance on perceived data integrity creates a paradox that demands rigorous human critical thinking focused on managing inputs and evaluating outputs. The research emphasizes that trustworthy data governance, not abstract explainability, is the foundation of sustainable GenAI adoption. Critical thinking must, therefore, be deployed to scrutinize both the data sources used by the AI and the factual accuracy of the outputs provided, rather than passively accepting results based on the promise of efficiency. This critical function serves as the essential check against the allure of speed, ensuring managers avoid the irresponsible use of GenAI content in high-stakes decisions.
The authors, Á. Hernández-Tamurejo, R. Bužinskienė, B. Barbosa, A. Miceikienė, and J. R. Saura, suggest that adopting monitoring, calibrated disclosure, and adaptive privacy protocols are concrete managerial levers to strengthen GenAI acceptance. In your experience, is the greatest challenge in AI adoption enforcing transparency, or instilling the critical capacity in staff to question seemingly objective algorithmic output? Share your thoughts.
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Reference: Hernández-Tamurejo, Á., Bužinskienė, R., Barbosa, B., Miceikienė, A., & Saura, J. R. (2025). Generative artificial intelligence use in the workplace: implications for management practice. Review of Managerial Science. https://doi.org/10.1007/s11846-025-00949-z
Justin O'Brien 