Slide 4: Link of These Issues with HRM Frameworks/Concepts
These challenges are deeply connected with several HRM frameworks and concepts:
- Employee Motivation, Satisfaction, and Employment Security:
- According to Maslow's Hierarchy of Needs, employees require job security and safety beyond their basic physiological needs to achieve higher levels of motivation and satisfaction (Mira et al., 2019). When AI creates job insecurity, it undermines employees' sense of safety, which can decrease motivation and job satisfaction.
- Skills Gap:
- The Competency Theory emphasizes aligning employee skills with job requirements. The resistance due to a skills gap reflects a mismatch between employees’ competencies and the technological demands of AI (Budhwar et al., 2022). This gap can lead to demotivation and reluctance to embrace AI.
- Inclusion and Diversity in Recruitment:
- Fairness and Diversity Management are crucial in HRM. AI algorithms, if not properly designed, can perpetuate biases and discrimination, impacting diversity in recruitment (Köchling & Wehner, 2020). Ensuring fairness in AI-driven recruitment is essential to maintain a diverse workforce.
- Employee Engagement:
- Employee engagement is a critical component of HRM and affects both individual and organizational performance. The resistance to AI can negatively impact engagement levels, as employees who feel disempowered or disconnected may become less engaged and productive (Budrienė & Diskienė, 2020).
- Employee Trust and Privacy:
- Trust and privacy are fundamental to effective HRM. Invasion of privacy and lack of transparency can erode employee trust, leading to lower productivity and higher turnover (Iqbal et al., 2019). HRM must address these concerns to foster a trustworthy and supportive work environment.
