Artificial intelligence (AI) is steadily entering and transforming the management, work, and organizational ecosystems. We observe AI-based applications assisting employees in daily tasks, project management, decision-making, and collaboration. AI applications are increasingly assisting also Human Resource Management (HRM) in undertaking time-critical tasks and managerial and administrative decision-making. However, more in-depth and comprehensive studies are needed to understand the specific factors affecting the full adoption of AI technology from a multi-level viewpoint and address the potential limitations of AI appropriation or its adverse outcomes in HRM. The purpose of this study is to investigate the conditions in which human talent may take advantage of the unique opportunities offered by AI. However, whereas previous studies were conducted on the individual perception of AI and technology readiness or adoption, an integrated approach aiming to combine talent management-related dimensions and managerial-related dimensions is still not available. For this research gap, we build a strategic management assessment framework of the driving factors of Talent, Trust, and Technology in AI adoption in HRM. We investigate the impact of these trends on the human-related and technology ecosystems and provide an integrated analysis of individual micro (talent management) organizational macro (trust and technology) adoption of AI technology. The paper advances the current definition and understanding of individual human facilitators and impediments behind the ability to speed up the adoption of AI-based technology. The practical contribution can facilitate the human-centered and trustworthy design and adoption of AI.

Artificial Intelligence, Human Talent, and Trust: A Management Tool for Assessing and Supporting AI Adoption in HRM

Tursunbayeva, Aizhan
2023-01-01

Abstract

Artificial intelligence (AI) is steadily entering and transforming the management, work, and organizational ecosystems. We observe AI-based applications assisting employees in daily tasks, project management, decision-making, and collaboration. AI applications are increasingly assisting also Human Resource Management (HRM) in undertaking time-critical tasks and managerial and administrative decision-making. However, more in-depth and comprehensive studies are needed to understand the specific factors affecting the full adoption of AI technology from a multi-level viewpoint and address the potential limitations of AI appropriation or its adverse outcomes in HRM. The purpose of this study is to investigate the conditions in which human talent may take advantage of the unique opportunities offered by AI. However, whereas previous studies were conducted on the individual perception of AI and technology readiness or adoption, an integrated approach aiming to combine talent management-related dimensions and managerial-related dimensions is still not available. For this research gap, we build a strategic management assessment framework of the driving factors of Talent, Trust, and Technology in AI adoption in HRM. We investigate the impact of these trends on the human-related and technology ecosystems and provide an integrated analysis of individual micro (talent management) organizational macro (trust and technology) adoption of AI technology. The paper advances the current definition and understanding of individual human facilitators and impediments behind the ability to speed up the adoption of AI-based technology. The practical contribution can facilitate the human-centered and trustworthy design and adoption of AI.
2023
978-2-9602195-5-5
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11367/119139
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