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

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.