Exploration of AI-Induced Job Displacement using HRM Concepts and Theories

(Bhardwaj, 2023)

To critically evaluate AI-induced job displacement within HRM, it is essential to integrate key concepts from HRM theory, current trends, and emerging theories while linking them to real-world practices. Below is an exploration of AI-induced job displacement using HRM concepts and theories.

1. HRM Concepts: 

Technological Change and Job Design

One of the core HRM concepts that is relevant to this discussion is technological change and its impact on job design. Technological advancements in AI and automation have radically altered the design of jobs in various sectors. HR professionals need to adapt to these changes by redesigning jobs to emphasize higher-order tasks that AI cannot perform, such as creativity, critical thinking, and decision-making.

The Job Characteristics Model (Hackman & Oldham, 1976) can be applied here to argue that job roles should be redesigned to enhance core job dimensions like skill variety, task identity, and task significance. By leveraging AI for repetitive tasks, HR departments can help employees engage in more meaningful work, fostering greater job satisfaction and motivation.

For example, Google and Salesforce have redesigned their HR roles to focus more on strategic decisions and employee engagement, using AI to automate administrative tasks. This shift allows HR professionals to focus on more impactful work while reducing the redundancy of routine tasks (Salesforce, 2020).

2. Emerging Theories of HRM: 

HR Analytics and Workforce Planning

The HR analytics theory, which involves the use of data and AI to make decisions related to recruitment, retention, and performance management, plays a significant role in the shift toward AI. AI and machine learning algorithms allow HR departments to analyze large sets of data to predict employee turnover, identify high-potential candidates, and optimize talent management strategies.

For instance, IBM Watson uses AI to process HR data, helping organizations predict which employees are likely to leave and suggesting targeted interventions. By implementing HR analytics, organizations can enhance workforce planning while minimizing the risk of unnecessary job displacement due to AI automation (IBM, 2019).

Furthermore, strategic HRM frameworks emphasize aligning HR policies with organizational goals. AI provides HR departments with tools to assess the future workforce needs of the organization, helping to anticipate potential job displacement and implement reskilling programs proactively. For example, Cognizant, a global IT services company, has used HR analytics to assess talent gaps and reskill its employees in areas where AI is unlikely to replace them (Cognizant, 2020).

3. Practice Example: 

AI in Recruitment and Selection

AI's impact on recruitment and selection is a key practice area where job displacement is most visible. AI-driven tools are now used to automate many aspects of the recruitment process, including candidate sourcing, resume screening, and even interview scheduling. These tasks, traditionally handled by HR assistants or administrative staff, can now be automated through chatbots and machine learning algorithms.

However, AI's role in recruitment is not limited to job displacement. It also creates opportunities to eliminate biases in hiring decisions and improve diversity in recruitment. Companies like Unilever use AI tools to screen candidates, focusing purely on skills and qualifications rather than demographic characteristics (Unilever, 2020). This aligns with diversity and inclusion theory in HRM, which advocates for a more equitable and bias-free recruitment process.

Despite the efficiency benefits, there are concerns regarding AI's limitations in understanding human emotions and the complexity of interpersonal interactions, which are critical in recruitment. This challenge calls for a hybrid approach where AI supports but does not replace the human element in the hiring process.

4. Organizational Change and Employee Adaptation: 

Theories of Change Management

As AI disrupts traditional HR roles, organizations must manage the change process effectively to mitigate resistance and support employees through transitions. Kotter's 8-Step Change Model (Kotter, 1996) is particularly useful here, as it emphasizes the importance of creating a sense of urgency, forming a guiding coalition, and empowering employees to embrace new technology.

One practice that has worked well for companies like Microsoft is the integration of change management strategies that involve clear communication, continuous learning, and upskilling opportunities. Microsoft has implemented comprehensive training programs that help HR professionals adapt to the integration of AI tools. This ensures that job displacement is not perceived as a threat but as an opportunity for career development in new roles that AI cannot replace (Microsoft, 2021).

Another example comes from the Healthcare Sector, where AI has been increasingly used for administrative tasks such as scheduling and patient record management. The Change Curve model (Kubler-Ross, 1969) shows that employees typically go through stages of shock, denial, and acceptance during transitions. HR departments in healthcare organizations use this model to provide the necessary support and guidance as AI is introduced, helping employees understand how they can coexist with technology rather than be displaced by it.

5. Theories on Employee Well-being and Ethical Implications

The Social Exchange Theory (Blau, 1964) suggests that employees expect fair treatment and reciprocity in return for their work. The ethical implications of AI-induced job displacement must be considered, as employees may feel alienated or undervalued if their roles are automated without adequate support. Ethical theories in HRM advocate for the humane treatment of employees, especially in terms of layoffs and job displacement.

In practice, many organizations are providing clear communication and transparent decision-making processes when implementing AI. For example, Accenture uses AI to automate many back-office functions but simultaneously ensures that employees are given the opportunity to reskill for higher-level roles (Accenture, 2020). This highlights the importance of employee well-being theories, which suggest that job displacement can be minimized by offering retraining and career development options to those affected.

Conclusion

AI-induced job displacement within HRM is a multifaceted issue that requires a nuanced approach grounded in current HRM theories and real-world practices. Concepts like job design, HR analytics, and strategic workforce planning provide frameworks for understanding how AI can both enhance efficiency and displace jobs. Emerging theories of change management and employee well-being highlight the importance of managing the transition to AI while ensuring ethical treatment of employees.

HRM practices in companies like Google, Microsoft, and Accenture demonstrate the potential for organizations to balance AI implementation with employee development, ensuring that job displacement is minimized and the workforce is empowered to adapt to new technologies.

References

• Accenture. (2020). How Accenture is Reskilling its Workforce for the Future. Accenture. Available at: https://www.accenture.com/reskilling-workforce [Accessed 30 Mar. 2025].
• Blau, P.M. (1964). Exchange and Power in Social Life. New York: Wiley.
• Cognizant. (2020). Using HR Analytics for Strategic Workforce Planning. Cognizant. Available at: https://www.cognizant.com/hr-analytics [Accessed 30 Mar. 2025].
• Hackman, J.R., & Oldham, G.R. (1976). Motivation Through the Design of Work: Test of a Theory. Organizational Behavior and Human Performance, 16(2), pp.250-279.
• IBM. (2019). AI for HR: A Guide to Transforming HR with Artificial Intelligence. IBM. Available at: https://www.ibm.com/blogs/ai-for-hr-guide [Accessed 30 Mar. 2025].
• Kotter, J.P. (1996). Leading Change. Boston: Harvard Business Review Press.
• Kubler-Ross, E. (1969). On Death and Dying. New York: Macmillan.
• Microsoft. (2021). Transforming HR with AI and Change Management. Microsoft. Available at: https://www.microsoft.com/hr-ai-transformation [Accessed 30 Mar. 2025].
• Salesforce. (2020). How Salesforce is Using AI in Human Resources. Salesforce. Available at: https://www.salesforce.com/hr-ai [Accessed 30 Mar. 2025].
• Unilever. (2020). How Unilever Uses AI in HR for Recruitment and Talent Management. Unilever. Available at: https://www.unilever.com/ai-recruitment [Accessed 30 Mar. 2025].
• Bhardwaj, R. (2023) Is Artificial Intelligence Taking Over Jobs?. Available at: https://theblazerrhs.com/7716/opinion/is-artificial-intelligence-taking-over-jobs-2/ (Accessed 30 March 2025).