# A systems-level framework for autonomy, trust, and workforce engagement in AI-enabled organizations

Published in[Phoenix Scholar](/research/publications/phoenix-scholar.html)  
[Volume 9 Issue 1, Page 69](/research/publications/phoenix-scholar/vol-9-issue-1.html), Fall, 2026

https://doi.org/10.64657/MYJW1762

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## Authors

Carl Beitsayadeh, MS  
Pamayla E. Darbyshire, DHA

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## Abstract

The integration of artificial intelligence (AI) into organizational systems is transforming work design, decision-making processes, and employee experiences across contemporary workplaces. Although worker autonomy, institutional trust, and workforce engagement have been widely studied within organizational research, these constructs are often examined in isolation, limiting understanding of how they interact within AI-enabled environments. This article proposes a systems-level conceptual framework in which AI integration influences employee autonomy, which in turn shapes institutional trust and subsequently workforce engagement. The framework conceptualizes AI as both enabling and constraining employee autonomy depending on how technological systems are designed and implemented within organizations. Grounded in socio-technical systems theory and self-determination theory, the framework further reconceptualizes institutional trust as a dual-target construct encompassing trust in both organizational leadership and algorithmic systems. By integrating technological, motivational, and institutional perspectives, the framework offers theoretical and practical insights for designing AI-enabled workplaces that support autonomy, foster institutional trust, and sustain workforce engagement.

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