[Paper Review] Employee Well-being in the Age of AI: Perceptions, Concerns, Behaviors, and Outcomes

Soheila Sadeghi|arXiv (Cornell University)|Dec 6, 2024

Technostress in Professional Settings6 citations

TL;DR

The study analyzes how AI in HR shapes employee perceptions, well-being, and retention, highlighting the role of transparency, communication, and upskilling in balancing benefits and concerns.

ABSTRACT

The growing integration of Artificial Intelligence (AI) into Human Resources (HR) processes has transformed the way organizations manage recruitment, performance evaluation, and employee engagement. While AI offers numerous advantages, such as improved efficiency, reduced bias, and hyper-personalization, it raises significant concerns about employee well-being, job security, fairness, and transparency. This study examines how AI shapes employee perceptions, job satisfaction, mental health, and retention. Key findings reveal that while AI can enhance efficiency and reduce bias, it also raises concerns about job security, fairness, and privacy. Transparency in AI systems emerges as a critical factor in fostering trust and positive employee attitudes. AI systems can both support and undermine employee well-being, depending on how they are implemented and perceived. The research introduces an AI-employee well-being Interaction Framework, illustrating how AI influences employee perceptions, behaviors, and outcomes. Organizational strategies, such as clear communication, upskilling programs, and employee involvement in AI implementation, are identified as crucial for mitigating negative impacts and enhancing positive outcomes. The study concludes that the successful integration of AI in HR requires a balanced approach that prioritizes employee well-being, facilitates human-AI collaboration, and ensures ethical and transparent AI practices alongside technological advancement.

Motivation & Objective

• Motivate understanding of how AI in HR affects employee well-being and related outcomes.
• Identify key perceptions, concerns, and behaviors influenced by AI-enabled HR processes.
• Propose an AI-employee well-being Interaction Framework to map relationships between AI, attitudes, and outcomes.
• Recommend organizational strategies to mitigate negative effects and enhance positive well-being outcomes.

Proposed method

• Review of AI integration in HR to assess effects on recruitment, performance evaluation, and engagement.
• Synthesis of findings on efficiency gains, bias reduction, and concerns around job security, fairness, and privacy.
• Development of an AI-employee well-being Interaction Framework illustrating pathways from AI to perceptions, behaviors, and outcomes.
• Derivation of practical organizational recommendations such as communication, upskilling, and employee involvement in AI implementation.

Experimental results

Research questions

• RQ1 How does AI integration in HR influence employee perceptions of job security, fairness, and privacy?
• RQ2 What is the relationship between AI-driven HR processes and job satisfaction, mental health, and retention?
• RQ3 What role does transparency in AI systems play in shaping trust and positive employee attitudes?
• RQ4 What organizational strategies mitigate negative well-being impacts and enhance positive outcomes with AI in HR?

Key findings

• AI can both enhance efficiency and reduce bias as well as raise concerns about job security and privacy.
• Transparency in AI systems is a critical factor for trust and positive attitudes toward AI in the workplace.
• Employee well-being outcomes depend on how AI is implemented and perceived by staff.
• Clear communication, upskilling programs, and involving employees in AI implementation are crucial mitigation strategies.
• The study proposes an AI–employee well-being Interaction Framework to illustrate these dynamics.