Sustainable and Responsible Workforce Management in the Digital Era: Implications of Artificial Intelligence and Digital Platforms
DOI:
https://doi.org/10.64882/ijrt.v14.iS1.962Keywords:
Workforce Management, Artificial Intelligence, Digital Platforms, Responsible Management, SustainabilityAbstract
Artificial intelligence and digital platforms have become increasingly embedded in organizational systems, fundamentally redefining how work is organized, monitored, and controlled. If their proponents’ claims are true, and if these technologies can indeed forestall dystopian futures, many of the questions they raise are about responsibility, sustainability, and ethics for technology to be worthwhile in the long term, it must support rather than detract from our well-being as a workforce. Drawing on the review literature, this concept paper contributes to our understanding of how artificial intelligence and platform-based systems are shaping managerial accountability and sustainable workforce practices in digitally transformed organisations. Referring to recent literature from management, organizational ethics, and digitalization research, the paper develops major themes concerning algorithmic decision-making, workforce surveillance, restructuring of work, skills, and employment, as well as governance challenges. The review raises tensions between efficiency-led digitalisation and the requirement for responsible workforce practices that manage with dignity, fairness, and inclusion for employees. According to the paper, sustainable and responsible management of people in the workforce needs a human touch that precedes technology advancement with ethical underpinning, transparency, and creating value over the long term. The theoretical lenses are integrated as they provide unique, complementary aspects of the phenomenon, and together, these provide an integrated understanding. The study offers a synthesised view on workforce responsibility in the digital age and suggests implications for further research and for practice.
References
Ball, K. (2010). Workplace surveillance: An overview. Labor History, 51(1), 87–106. https://doi.org/10.1080/00236561003654776
Brock, J. K. U., & von Wangenheim, F. (2019). Demystifying artificial intelligence: What digital transformation leaders can teach you about realistic AI. California Management Review, 61(4), 110–134. https://doi.org/10.1177/0008125619869916
Budhwar, P., Varma, A., Malhotra, N., & Mukherjee, A. (2019). Insights into human resource management practices in India. Human Resource Management Review, 29(3), 100–112. https://doi.org/10.1016/j.hrmr.2018.02.001
Chakraborty, S. K. (2001). Ethics in management: Vedantic perspectives. Oxford University Press India. https://global.oup.com/academic/product/ethics-in-management-9780195659312
De Stefano, V. (2016). The rise of the “just-in-time workforce”: On-demand work and labour protection. Comparative Labor Law & Policy Journal, 37(3), 471–504. https://cllpj.law.illinois.edu/archive/vol_37/issue_3/DeStefano471.pdf
Dubey, Vandana, Shikha Singh, Priti Kumari, Kavita Patel, Tasneem Jahan, and Sonam Dubey. "AI-Driven Business Systems: Pioneering Innovation and Transformation." In Integrating AI and Machine Learning into Business and Management Education, pp. 297-332. IGI Global Scientific Publishing, 2026.
Ehnert, I. (2009). Sustainable human resource management: A conceptual and exploratory analysis from a paradox perspective. Springer. https://doi.org/10.1007/978-3-7908-2188-8
Floridi, L., Cowls, J., Beltrametti, M., et al. (2018). AI4People—An ethical framework for a good AI society. Minds and Machines, 28(4), 689–707. https://doi.org/10.1007/s11023-018-9482-5
Gour, Khushbu, and Charu Agarwal. "Analyzing the role of green tech marketing in advancing sustainable development goals." Available at SSRN 4690011 (2024).
Jobin, A., Ienca, M., & Vayena, E. (2019). The global landscape of AI ethics guidelines. Nature Machine Intelligence, 1, 389–399. https://doi.org/10.1038/s42256-019-0088-2
Kässi, O., & Lehdonvirta, V. (2018). Online labour index: Measuring the online gig economy. Technological Forecasting and Social Change, 137, 241–248. https://doi.org/10.1016/j.techfore.2018.07.056
Kellogg, K. C., Valentine, M. A., & Christin, A. (2020). Algorithms at work: The new contested terrain of control. Academy of Management Annals, 14(1), 366–410. https://doi.org/10.5465/annals.2018.0174
Mehrotra, S., & Ghosh, S. (2021). Skill development and training in India. Springer. https://doi.org/10.1007/978-981-15-9816-6
NITI Aayog. (2018). National strategy for artificial intelligence: #AIForAll. Government of India. https://www.niti.gov.in/sites/default/files/2019-01/NationalStrategy-for-AI-Discussion-Paper.pdf
Pak, K., & Ploeger, A. (2019). When human decision-making is replaced by artificial intelligence: Implications for responsibility. AI & Society, 34(4), 823–831. https://doi.org/10.1007/s00146-018-0866-2
Pfeffer, J. (2010). Building sustainable organizations: The human factor. Academy of Management Perspectives, 24(1), 34–45. https://doi.org/10.5465/amp.24.1.34
Shrivastava, S., Bannerjee, S., Srivastava, M., Khalid, S. and Nishad, D.K., 2024. Advancements in Humanoid Robotics: Designing an Artificial Neural Network-based Speech Recognition Robot for Tactical Deployment.
Siddiqui, N.N., 2024. Understanding Work-Life Balance in the Aviation Industry: A Comparative Analysis of Jet Airways and Indigo. In New Innovations in AI, Aviation, and Air Traffic Technology (pp. 247-271). IGI Global Scientific Publishing.
Wood, A. J., Graham, M., Lehdonvirta, V., & Hjorth, I. (2019). Good gig, bad gig: Autonomy and algorithmic control in the global gig economy. Work, Employment and Society, 33(1), 56–75. https://doi.org/10.1177/0950017018785616
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