Identifying and Prioritizing Factors Affecting Knowledge Workers' Experience in the Age of Artificial Intelligence

Document Type : Research Paper

Authors

1 Faculty of Management & Industrial Engineering, Malek Ashtar of Technology Tehran, Iran.

2 Faculty of Management & Industrial Engineering, Malek Ashtar University of Technology, Tehran, Iran.

10.22054/jims.2026.93819.3048
Abstract
With the advent of artificial intelligence (AI), human resource management has encountered fundamental opportunities and challenges, making the enhancement and sustainability of knowledge workers’ productivity a critical concern. This study aimed to analyze the factors influencing the experience of knowledge workers in the AI era and to develop a managerial roadmap within a mission-based university context. This applied research adopted an exploratory–explanatory, cross-sectional mixed-methods design based on an inductive approach. Data were collected using researcher-developed questionnaires grounded in the ISO 34000 Human Resource Management Standard and validated through an expert panel of university specialists. Interpretive Structural Modeling (ISM) and MICMAC analysis were employed to identify and classify the relationships among the factors, while the Analytic Network Process (ANP) was used to determine their relative importance and weights. The findings revealed that intelligent leadership and organizational culture are the most influential underlying drivers, exerting the greatest impact on other dimensions of employee experience. These factors serve as the foundation for shaping and improving the work environment of knowledge employees in the AI era. Based on the results, a comprehensive managerial roadmap was developed and validated, comprising five phases: foundational preparation, managerial and cultural transformation, job experience optimization, emergence of innovation and scientific leadership, and retention of knowledge capital. The proposed roadmap provides a practical framework for effective policymaking and strategic decision-making in knowledge-based organizations, particularly higher education institutions undergoing AI-driven transformation.

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