# AI, autonomy, and institutional trust: Cultivating workforce engagement in the era of intelligent work

Published in[Phoenix Scholar](/research/publications/phoenix-scholar.html)  
[Volume 9 Issue 1, Page 53](/research/publications/phoenix-scholar/vol-9-issue-1.html), Fall, 2026

https://doi.org/10.64657/QEEV2305

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## Author

Brian Park, Ed.D.

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## Abstract

Burnout and disengagement are frequently explained through the Job Demands–Resources (JD–R) model, which holds that sustained job demands combined with insufficient resources predict strain and reduced well-being, with inadequate recovery deepening negative outcomes (Bakker & Demerouti, 2017; Sonnentag, 2018). Concurrently, artificial intelligence (AI) is reshaping task structures and skill requirements across industries (Brynjolfsson et al., 2023; Huang & Rust, 2021), and awareness of AI’s impact can heighten employment-risk perception, particularly among workers who lack adaptive confidence (Liang & Zhai, 2025). Because trust in AI systems and in institutional decision-making shapes acceptance of technological integration (Glikson & Woolley, 2020), and because sustainable-career scholarship ties long-term employability to ongoing development and organizational support (De Vos et al., 2020), this article argues that structured AI upskilling—implemented through autonomy-supportive practices—can strengthen workforce engagement and institutional trust.

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