My Research

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My research examines how artificial intelligence is changing the way organizations make decisions about people. As AI systems increasingly screen candidates, assess performance, and flag whom to develop or promote, the most consequential questions are no longer solely technical. They are human: how do managers and HR professionals interpret algorithmic recommendations, when do they trust or override them, and what does this mean for fairness, accountability, and the future of work? I study these questions with a mixed-methods approach, combining qualitative methods that take the perspective of the people inside the decision with quantitative analysis that reveals broader patterns across those decisions.

• AI in HR decision-making. How managers and HR professionals make sense of, trust, and act on algorithmic recommendations in hiring, performance evaluation, and promotion, and where human judgment and machine output collide.
• People analytics, fairness, and accountability. How organizations adopt people analytics responsibly, how employees experience being measured and ranked by systems, and who is accountable when an algorithm gets it wrong.
• The future of work and organizations. How AI reshapes roles, skills, and organizational design, and what HR and leadership practices must become in response.

I work with mixed methods, empirical research, combining qualitative approaches such as reflexive thematic analysis and the Gioia methodology with quantitative analysis, and applying careful attention to trustworthiness and rigor across both traditions. I am actively developing primary human-subjects research in this area and welcome collaboration with scholars and institutions working on AI, HR, and the future of work.

In progress (2026): a mixed-methods study of how AI is perceived to impact future organizational structures.