1 Institute of Public Enterprise, Hyderabad, Telangana, India
Creative Commons Non Commercial CC BY-NC: This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (http://www.creativecommons.org/licenses/by-nc/4.0/) which permits non-Commercial use, reproduction and distribution of the work without further permission provided the original work is attributed.
Coexistence of technology and business dates back to the late 18th century when the first ever use of a computer was for recording the census by the US government in 1890. The use of technology in business can be ascribed to different organisations in the different nations on the parallel lines of time. It includes invention of cash machines and their use by Barclays in England in the early 1960s, the induction of telephone-based modems for order management by Baxter Pharmaceuticals and use of small desktop computing device called Minitel for processing customer orders in France were the other notable developments in the history of coexistence of technology and business. Increasing operations in the business functions have created an urge for the technological innovation in the industry to handle the operations electronically. Figueiredo and Cohen (2019) say that technology has become an indispensable component of every business function by delivering ease in operations and productivity. The end of the 20th century had witnessed the leaping progress in computing in the form of artificial intelligence (AI) performing the tasks that were unimaginable to comprehend a decade back in time. Developments in the technological research and development prove that organisations have started inducting AI into as many fields as possible at a considerable pace. As a part of the shifting technological dynamics in the industry HR function has also transformed digitally. Tools like enterprise applications have forayed intensely into the operations of human resources management (HRM). These enterprise resource planning (ERP) tools remain to primarily serve the integration of HRM to the other functions. However, enterprise tools could not serve the purpose of supporting decisiveness in the areas of HR planning, workforce design and performance management at large. However, Tuck (2019) argues that AI is assuming increased responsibilities in the different sections of the society and business including the HRM function. At present, the amount of knowledge on the status quo of the role of AI in the HRM functions is scarcely available. Literature related to this disruptive technology in the HR function is still at the nascent stage. This study will examine the role of AI as a key component in the HRM function, which is regarded to be highly human-driven.
Human resources management, artificial intelligence, digital selection and recruitment, automation in performance management, intelligent systems
Abdeldayem, M. M., & Aldulaimi, S. H. (2020). Trend and opportunities of artificial intelligence in human resources management: Aspirations for public sector in Bahrain. International Journal of Scientific and Technology Research, 9(1), 3867–3871.
Almeida, F. (2022). Methods for identifying and evaluating disruptive technologies in university spinoffs. The International Journal of Entrepreneurship and Innovation, 23(4), 240–252. https://doi.org/10.1177/14657503211050806
Anohya, R. (2017). The history of artificial intelligence. Harvard Business School https://sitn.hms.harvard.edu/flash/2017/history-artificial-intelligence/
Arrieta, A. B., Díaz-Rodríguez, N., Del Ser, J., Bennetot, A., Tabik, S., Barbado, A., Garcia, S., Gil-Lopez, S., Molina, D., Benjamins, R., Chatila., R., & Herrera, F. (2020). Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI. Information fusion, 58, 82–115.
Awan, S. H., Habib, N., Shoaib Akhtar, C., &Naveed, S. (2020). Effectiveness of performance management system for employee performance through engagement. SAGE Open, 10(4). https://doi.org/10.1177/2158244020969383
Bentley, K. A., Omer, T. C., & Sharp, N. Y. (2013). Business strategy, financial reporting irregularities, and audit effort. Contemporary accounting research, 30(2), 780–817.
Bodendorf, F., & Zimmermann, R. (2005). Proactive supply-chain event management with agent technology. International Journal of Electronic Commerce, 9(4), 57–89. http://www.jstor.org/stable/27751165
Buck, B., & Morrow, J. (2018). AI, performance management and engagement: Keeping your best their best. Strategic HR Review, 17 (5), 261–262.
ankovi, V. Š. (2015). The impact of employee selection on organisatinal performance. SEER: Journal for Labour and Social Affairs in Eastern Europe, 18(2), 217–230. http://www.jstor.org/stable/26379813
Chamorro-Premuzic, T., Winsborough, D., Sherman, R. A., & Hogan, R. (2016). New talent signals: Shiny new objects or a brave new world Industrial and Organizational Psychology, 9(3), 621–640.
Chen, H., Chiang, R. H. L., & Storey, V. C. (2012). Business intelligence and analytics: From big data to big impact. MIS Quarterly, 36(4), 1165–1188. https://doi.org/10.2307/41703503
Cox, A. M., & Mazumdar, S. (2022). Defining artificial intelligence for librarians. Journal of Librarianship and Information Science. Advance online publication. https://doi.org/10.1177/09610006221142029
Dattner, B., Chamorro-Premuzic, T., Buchband, R., & Schettler, L. (2019, April 25). The legal and ethical implications of using AI in hiring. Harvard Business Review. https://hbr.org/2019/04/the-legal-and-ethical-implications-of-using-ai-in-hiring
Davison, H. K., Maraist, C., & Bing, M. N. (2011). Friend or foe The promise and pitfalls of using social networking sites for HR decisions. Journal of Business and Psychology, 26(2), 153–159. http://www.jstor.org/stable/41474863
Doll, J. L. (2022). Developing workforce planning skills in human resource management courses: A data-driven exercise. Management Teaching Review, 7(1), 89–108. https://doi.org/10.1177/23792981211057227
Faix, A.-V. (2022). Qualitative innovation in the light of the normative: A minimal approach to promoting and measuring successful innovation in business. IMIB Journal of Innovation and Management, 2(1). https://doi.org/10.1177/ijim.221091004
Fernández-Martínez, C., & Fernández, A. (2020). AI and recruiting software: Ethical and legal implications. Paladyn, Journal of Behavioral Robotics, 11(1), 199–216. https://doi.org/10.1515/pjbr-2020-0030
Feuss, T. (2015). IBM Watson applied to intelligence problems. National Defense, 100(742), 15. https://www.jstor.org/stable/27020983
Figueiredo, P. N., & Cohen, M. (2019). Explaining early entry into path-creation technological catch-up in the forestry and pulp industry: Evidence from Brazil. Research Policy, 48(7), 1694–1713.
Fountaine, T., McCarthy, B., & Saleh, T. (2019). Building the AI-powered organization. (cover story). Harvard Business Review, 97(4), 62–73.
Heller, C. H. (2019). Near-term applications of artificial intelligence: Implementation opportunities from modern business practices. Naval War College Review, 72(4), 73–100. https://www.jstor.org/stable/26775520
Holland, J. H. (1992). Complex adaptive systems. Daedalus, 121(1), 17–30.
Huan, M.-J., Tsou, Y.-L., & Lee, S.-C. (2006). Integrating fuzzy data mining and fuzzy artificial neural networks for discovering implicit knowledge. Knowledge-Based Systems, 19(6), 396–403. https://doi.org/10.1016/j.knosys.2006.04.003
Hunkenschroer, A. L., & Luetge, C. (2022). Ethics of AI-enabled recruiting and selection: A review and research agenda. Journal of Business Ethics 178 (4), 977–1007. https://doi.org/10.1007/s10551-022-05049-6
Huselid, M. A., & Becker, B. E. (2011). Bridging micro and macro domains: Workforce differentiation and strategic human resource management. Journal of Management, 37(2), 421–428
Jeske, D., & Shultz, K. S. (2016). Using social media content for screening in recruitment and selection: Pros and cons. Work, Employment & Society, 30(3), 535–546. https://www.jstor.org/stable/26499476
Jeude, J. (2020). POINT: Artificial intelligence (AI) must be part of human capital management. Workforce Solutions Review, 11(2), 25–27.
Kaplan, A., & Haenlein, M. (2019). Siri, Siri, in my hand: Who’s the fairest in the land? On the interpretations, illustrations, and implications of artificial intelligence. Business Horizons, 62(1), 15–25. https://doi.org/10.1016/j.bushor.2018.08.004
Karimi, J., Somers, T. M., & Bhattacherjee, A. (2009). The role of ERP implementation in enabling digital options: A theoretical and empirical analysis. International Journal of Electronic Commerce, 13(3), 7–42. http://www.jstor.org/stable/27751295
Kaur, M., AG, R., & Vikas, S. (2021). Adoption of artificial intelligence in human resource management: A conceptual model. Indian Journal of Industrial Relations, 57(2), 331–342.
Kim, K. Y., Pathak, S., & Werner, S. (2015). When do international human capital enhancing practices benefit the bottom line? An ability, motivation, and opportunity perspective. Journal of International Business Studies, 46(7), 784–805. http://www.jstor.org/stable/43653775
Köchling, A., Riazy, S., Wehner, M. C., & Simbeck, K. (2021). Highly accurate, but still discriminatory. Business and Information Systems Engineering, 63, 39–54. https://doi.org/10.1007/s12599-020-00673-w
Kong, H., Yuan, Y., Baruch, Y., Bu, N., Jiang, X., & Wang, K. (2021). Influences of artificial intelligence (AI) awareness on career competency and job burnout. International Journal of Contemporary Hospitality Management, 33(2), 717–734. https://doi.org/10.1108/IJCHM-07-2020-0789
Kurniawaty, R., & Rosyadi, K. I. (2022). The role of human resource planning, demographic change and advances in information technology in management education (literature review thinking system). Dinasti International Journal of Digital Business Management (DIJDBM), 4(1), 36–45. https://doi.org/10.31933/dijdbm.v4i1
Linscott, M., & Raghuraman, A. (2020). Aligning India’s Data Governance Frameworks. Atlantic Council. http://www.jstor.org/stable/resrep25999
Maity, S. (2019). Identifying opportunities for artificial intelligence in the evolution of training and development practices. The Journal of Management Development, 38(8), 651–663. https://doi.org/10.1108/JMD-03-2019-0069
Manning, R. A. (2020). Emerging technologies: New challenges to global stability. Atlantic Council. http://www.jstor.org/stable/resrep26000
Maurya, A. M., Padval, B., Kumar, M., & Pant, A. (2023). To study and explore the adoption of green logistic practices and performance in manufacturing industries in India. IMIB Journal of Innovation and Management, 1(2), 207–232. https://doi.org/10.1177/ijim.221148882
McCarthy, J. (1956). Measures of the value of information. Proceedings of the National Academy of Sciences, 42(9), 654–655. https://doi.org/10.1073/pnas.42.9.654
Mearian, L. (2023, July 10). Q&A: How AI can help enterprise HR automate employee experiences. Computerworld. https://www.computerworld.com/article/1631024/qa-how-ai-can-help-enterprise-hr-automate-employee-experiences.html
Mehrotra, S., & Khanna, A. (2022). Recruitment through AI in selected Indian companies. Metamorphosis, 21(1), 31–39. https://doi.org/10.1177/09726225211066220
Minbaeva, D. (2021). Disrupted HR? Human Resource Management Review, 31(4), 100820. https://doi.org/10.1016/j.hrmr.2020.100820
Minsky, M. (1968). Semantic information processing. The MIT Press.
Murugesan, U., Subramanian, P., Srivastava, S., & Dwivedi, A. (2023). A study of artificial intelligence impacts on human resource digitalization in industry 4.0. Decision Analytics Journal, 7. https://doi.org/10.1016/j.dajour.2023.100249
Ong, K. (2019). Top 3 applications of AI in human resources. Women of Color Magazine, 19(2), 72–75. https://www.jstor.org/stable/26924279
Oswald, F. L., Behrend, T. S., Putka, D. J., & Sinar, E. (2020). Big data in industrial-organizational psychology and human resource management: Forward progress for organizational research and practice. Annual Review of Organizational Psychology and Organizational Behavior, 7, 505–533. https://doi.org/10.1146/annurev-orgpsych-032117-104553
Paesano, A. (2021). Artificial intelligence and creative activities inside organizational behavior. International Journal of Organizational Analysis, 31(5), 1694–1723. https://doi.org/10.1108/IJOA-09-2020-2421
Palos-Sánchez, P. R., Baena-Luna, P., Badicu, A., & Infante-Moro, J. C. (2022). Artificial intelligence and human resources management: A bibliometric analysis. Applied Artificial Intelligence, 36(1), Article 2145631. https://doi.org/10.1080/08839514.2022.2145631
Pearl, J. (1988). Probabilistic reasoning in intelligent systems: Networks of plausible inference. Morgan Kaufmann.
Pillai, R., & Sivathanu, B. (2020). Adoption of artificial intelligence (AI) for talent acquisition in IT/ITeS organizations. Benchmarking: An International Journal, 27(9), 2599–2629. https://doi.org/10.1108/BIJ-04-2020-0186
Prakash, A. S., Gupta, A. K., & Kaur, S. (2022). Economic aspect of implementing green HR practices for environmental sustainability. IMIB Journal of Innovation and Management, 1(1), 94–106. https://doi.org/10.1177/ijim.221109016
PR Newswire. (2023 June 21). AccountingSuite™ revolutionizes payroll management with new cloud payroll solution. PR Newswire US. https://www.prweb.com/releases/accountingsuite-tm-revolutionizes-payroll-management-with-new-cloud-payroll-solution-870756547.html
Quaquebeke, N. V., & Gerpott, F. H. (2023). The now, new, and next of digital leadership: How artificial intelligence (AI) will take over and change leadership as we know it. Journal of Leadership & Organizational Studies, 30(3), 265–275. https://doi.org/10.1177/15480518231181731
Rb-Kettler, K., & Lehnervp, B. (2019). Recruitment in the times of machine learning. Management Systems in Production Engineering, 27(2) 105–109. https://doi.org/10.1515/mspe-2019-0018
Russell, S. (2021). The history and future of AI. Oxford Review of Economic Policy, 37(3), 509–520. https://doi.org/10.1093/oxrep/grab013
Sahlin, J., & Angelis, J. (2019). Performance management systems: Reviewing the rise of dynamics and digitalization. Cogent Business & Management, 6(1), Article 1642293.
Salas, E., Tannenbaum, S. I., Kraiger, K., & Smith-Jentsch, K. A. (2012). The science of training and development in organizations: What matters in practice. Psychological Science in the Public Interest, 13(2), 74–101. http://www.jstor.org/stable/23484697
Schildt, H. (2017). Big data and organizational design the brave new world of algorithmic management and computer augmented transparency. Innovation, 19(1), 23–30. https://doi.org/10.1080/14479338.2016.1252043
Simbeck, K. (2019). HR analytics and ethics. IBM Journal of Research and Development, 63(4/5), 1–12
Srimannarayana, M. (2011). Measuring training and development. The Indian Journal of Industrial Relations, 47(1), 117–125.
Tambe, P., Cappelli, P., & Yakubovich, V. (2019). Artificial intelligence in human resources management: Challenges and a path forward. California Management Review, 61(4), 15–42. https://doi.org/10.1177/0008125619867910
Tuck, J. (2019). Mankind’s greatest challenge: Artificial intelligence. The Antioch Review, 77(3), 447–456. https://doi.org/10.7723/antiochreview.77.3.0447
Wang, Y. (2020). When artificial intelligence meets educational leaders’ data-informed decision making: A cautionary tale. Studies in Educational Evaluation, 69, 100872. Retrieved January 11, 2021, from https://doi.org/10.1016/j.stueduc.2020.100872
Wang, Y. (2021). Artificial intelligence in educational leadership: A symbiotic role of human-artificial intelligence decision-making. Journal of Educational Administration, 59(3), 256–270. https://doi.org/10.1108/JEA-10-2020-0216
Welsh, R. (2019). Defining artificial intelligence. SMPTE Motion Imaging Journal, 128(1), 26–32. https://doi.org/10.5594/JMI.2018.2880366
Yarger, L., Cobb Payton, F., &Neupane, B. (2020). Algorithmic equity in the hiring of underrepresented IT job candidates. Online Information Review, 44(2), 383–395. https://doi.org/10.1108/OIR-10-2018-0334
Zhang, J., Feng, Q., Wang, S., Zhang, X., & Wang, S. (2016). Estimation of CO2–brine interfacial tension using an artificial neural network. The Journal of Supercritical Fluids, 107, 31–37.
Zielinski, D. (2017). Robot recruiters. HR Magazine, 62(3), 64–65.