AI in HRM: Principles and Practices in Global Contexts

Artificial Intelligence (AI) has transformed Human Resource Management (HRM) by increasing efficiency, minimizing bias, and upgrading decision-making in a globalized workforce. The integration of AI into HRM is remarkable in recruitment, performance management, employee engagement, learning & development, workforce planning, and payroll automation (Jiang et al., 2021).

1. AI in Recruitment and Talent Acquisition

AI is used to automate resume screening, to perform chatbot-driven initial interviews, and to predict analytics that evaluate candidate eligibility against job compatibility (Upadhyay & Khandelwal, 2018). For example, AI-driven tools like HireVue and Pymetrics take advantage of machine learning to analyze resumes and predict a candidate’s suitability (Dastin, 2018).

2. AI in Performance Management

AI systems such as Microsoft Viva track employee productivity and give real-time performance insights (Bhardwaj et al., 2020). These systems uplift personalized feedback and career development recommendations, which help to increase employee efficiency on a global scale.

Video: AI system - Microsoft Viva (Microsoft 365, 2023)

3. AI in Employee Engagement and Well-being

AI-powered sentiment analysis tools analyze employee communication to evaluate morale and engagement (Leicht-Deobald et al., 2019). Moreover, AI-powered mental health chatbots like Wysa and Ginger provide personalized support to employees who are dealing with stress (Madera, 2018).

Video: AI-powered Chatbot - Wysa (Wysa, 2023)

4. AI uses for Learning and Development

Adaptive learning platforms like LinkedIn Learning and Coursera use AI to match employee training programs according to their desires. These platforms suggest courses based on employees’ skills and job roles (Nawaz, 2020).

5. AI uses for Workforce Planning and Decision-Making

AI helps to predict workforce analytics, help HR teams to predict hiring needs, and reduce employee turnover (Chamorro-Premuzic et al., 2019). AI also contributes to minimizing bias in decision-making by providing data-driven insights on recruitment and promotions (Raisch & Krakowski, 2021).

6. AI in Payroll and Compliance Automation

AI automates payroll processing, tax calculations, and benefits administration through AI-driven platforms like Workday and ADP (Kaushik & Guleria, 2020). In addition to that, AI ensures HR compliance with global labor laws such as the General Data Protection Regulation (GDPR) (Bhardwaj et al., 2020).

Global HRM Considerations

AI in HRM must be adapted to cultural sensitivities, ethical concerns, and regulatory requirements across different countries (Leicht-Deobald et al., 2019). Furthermore, AI-powered decision-making should be transparent and unbiased. Besides, we need to ensure fairness in recruitment and employee management as well (Chamorro-Premuzic et al., 2019).

Challenges of AI in HRM

Although AI has plenty of benefits, AI adoption in HRM faces several challenges as well, such as:

• Algorithmic bias: AI systems may perpetuate bias if trained on non-diverse datasets (Raisch & Krakowski, 2021).
• Employee resistance: Many employees scared of job displacement and privacy breaches due to AI integration (Upadhyay & Khandelwal, 2018).
• Data security and ethical concerns: AI-powered HRM systems must adhere to privacy regulations and comply with data protection laws (Kaushik & Guleria, 2020).

AI is reshaping global HRM practices by increasing efficiency, improving employee engagement, and optimizing workforce planning. However, ethical AI use and responsible implementation are more important to overcome challenges related to bias, transparency, and regulatory compliance.

References

• Bhardwaj, A., Singh, A.K. and Singh, S. (2020) ‘Artificial intelligence in human resource management: A literature review’, International Journal of Research in Business and Social Science, 9(2), pp. 1-12.
• Chamorro-Premuzic, T., Winsborough, D., Sherman, R.A. and Hogan, R. (2019) ‘The future of talent assessment’, Harvard Business Review, 97(6), pp. 80-86.
• Dastin, J. (2018) ‘Amazon scrapped “AI recruiter” that showed bias against women’, Reuters, 10 October. Available at: https://www.reuters.com (Accessed: 12 March 2025).
• Jiang, K., Lepak, D.P., Hu, J. and Baer, J.C. (2021) ‘How does human resource management impact organizational outcomes? A meta-analytic investigation of mediating mechanisms’, Academy of Management Journal, 64(1), pp. 151-176.
• Kaushik, M. and Guleria, N. (2020) ‘AI and its role in HR practices’, International Journal of Advanced Science and Technology, 29(3), pp. 2735-2742.
• Leicht-Deobald, U., Busch, T., Schank, C., Weibel, A., Schafheitle, S., Wildhaber, I. and Kasper, G. (2019) ‘The challenges of algorithm-based HR decision-making for personal integrity’, Journal of Business Ethics, 160(2), pp. 377-392.
• Madera, J.M. (2018) ‘Recruitment in the age of AI: A conceptual framework for artificial intelligence-based recruitment’, Journal of Business Research, 92, pp. 266-271.
• Nawaz, N. (2020) ‘Application of AI in HRM: A review and future research agenda’, Journal of Business and Management Research, 10(2), pp. 22-30.
• Raisch, S. and Krakowski, S. (2021) ‘Artificial intelligence and management: The automation–augmentation paradox’, Academy of Management Review, 46(1), pp. 192-210.
• Upadhyay, A.K. and Khandelwal, K. (2018) ‘Applying AI in recruitment’, Strategic HR Review, 17(5), pp. 255-257.
• Microsoft 365 (2023) Human Resources conversational automation with Microsoft Viva Overview. YouTube video, added by Microsoft 365. Available at: https://youtu.be/hxRSA55nRVg?si=kMQPc0_RhOneWIHX [Accessed 14 March 2025].
• Wysa (2023) Wysa: The AI bot that delivers mental health support at scale [Uplink | World Economic Forum 2023]. YouTube video, added by Wysa. Available at: https://youtu.be/ARYjC8pwiWw?si=_InJtgafoxL5M_2u [Accessed 14 March 2025].