Using AI and Machine Learning to Edify HRM’s Operational Efficiency: Insights from London-Based Fintech Companies
Abstract:
Thriving in the fintech world where usage of more advanced Fourth Industrial Revolution (4IR) technologies is increasingly becoming the norm requires Fintech Companies to explore all the best possible ways of attaining superior competitive advantage. As part of such quest, this study used a qualitative research approach to examine how usage of AI and machine learning technologies by most of the selected London-based Fintech Companies would enhance HRM operational efficiency. Insights from managers purposively sampled from a cross-section of Fintech Companies operating across the thirty-two London Boroughs indicated AI and machine learning usage to bolster a firm’s HRM operational efficiency. This unlocks cost and differentiation advantages to spawn the fintech’s overall competitiveness. In the increasingly disruptive 4IR Era, this improves a firm’s capability to excel and achieve the best. However, even though fintech companies are known for using more advanced 4IR technologies, findings indicated most London-based Fintech companies had not yet embraced the full use of AI and machine learning applications in their daily HR management activities. There is still a strong belief that, as compared to HR management, which requires manual processes, usage of AI and machine learning tends to be more suitable for just automating marketing, operational and other management processes. When it comes to personnel recruitment, usage of manual approach is construed as more suitable. By directly engaging with potential candidates on a one-on-one physical basis, some fintech executives feel that they can recruit and deploy the best. Such unsupportive business philosophy was found to be further exacerbated by lack of an appropriate strategy for AI and ML usage in HRM, and poor investment in proper AI, big data and machine learning technologies. To respond such challenges, findings imply that if fintech companies and other forms of businesses are to thrive, it is essential to adopt a framework analogous to Leeway-Hertz’s “Model for AI usage in HRM.”
KeyWords:
Artificial Intelligence; Machine Learning; HRM; Operational Efficiency; Fintech Companies; Competitiveness
References:
- Aggarwal, S., & Kathuria, P. (2023). Impact of Artificial Intelligence on Human Resource Management: A Review of Literature. Journal of International Academic Research for Multidisciplinary, 11(4), 2320-5083.
- Ariwala, P. (2024). Machine Learning Algorithms: Obstacles with Implementation Complexities in Deploying Machine Learning Solutions. New Delhi: Maruti-TechLabs.
- Basnet, S. (2024). Artificial Intelligence and Machine Learning in Human Resource Management: Prospect and Future Trends. International Journal of Research Publication and Reviews, 5(1), 281-287.
- Batho, B., & Kathryn Davis, K. (2024). How Artificial Intelligence is Transforming Human Resources and the Workforce. London: Health Solutions.
- Berryman, D. R. (2019). Ontology, Epistemology, Methodology, and Methods: Information for Librarian Researchers. Medical Reference Services Quarterly, 38(3), 271-279.
- Bresciani, S., Ferraris, A., Del-Giudice, M., & Papa, A. (2018). The role of digital technologies in HRM: Opportunities and challenges. International Journal of Human Resource Management, 29(10), 13-53.
- Buzko, I., Maurer, V., & Zotov, V. (2016). AI in human resource management: A review of applications and impact. Journal of Business Research, 69(5), 1830-1835.
- Creswell, J. W., & Creswell, J. D. (2020). Research design: Qualitative, quantitative, and mixed methods approaches (5th ed.). Sage Publications.
- Denzin, N. K., & Lincoln, Y. S. (2021). The SAGE handbook of qualitative research (5th ed.). Sage Publications.
- Ekuma, K. (2024). Artificial Intelligence and Automation in Human Resource Development: A Systematic Review. Human Resource Development Review, 23(2), 199-229.
- Evseeva, S., Evseeva, O., Burmistrov, A., & Siniavina, M. (2021). Application of artificial intelligence in human resource management in the agricultural sector. In E3S Web of Conferences (Vol. 258, p. 01010). EDP Sciences.
- Fakhar Manesh, M., Pellegrini, M. M., Marzi, G., & Dabić, M. (2021). Knowledge management in the fourth industrial revolution: Mapping the literature and scoping future avenues. IEEE Transactions on Engineering Management, 68(1), 289-300.
- Flick, U. (2022). An introduction to qualitative research (7th ed.). Sage Publications.
- Gadekar, B., & Hiwarkar, T. (2023). A Critical Evaluation of Business Improvement through Machine Learning: Challenges, Opportunities, and Best Practices. International Journal on Recent and Innovation Trends in Computing and Communication, 11(10s), 264-276.
- Ghasemi Parvin, B., Mohammadiyeh, S. A., & Ghasemi Parvin, L. (2023). Artificial Intelligence and Machine Learning in Business: Opportunities and Challenges. Presented at The First Applied Humanities Research Conference in Management, Industrial Engineering, Economics and Accounting, Leeds, England.
- George, G., & Thomas, M. R. (2019). Integration of Artificial Intelligence in Human Resource. International Journal of Innovative Technology and Exploring Engineering, 9(2), 2278-3075.
- Giraud, L., Zaher, A., Hernandez, S., & Akram, A. A. (2022). The impacts of artificial intelligence on managerial skills. Journal of Decision Systems, 32(3), 566-599.
- Harrison, P., Nichol, L., & Gold, J. (2020). Redefining HRD roles and practice in the machine learning revolution. In The Future of HRD, Volume I: Innovation and Technology (pp. 143-166). Springer Nature.
- Hennink, M., Hutter, I., & Bailey, A. (2020). Qualitative research methods (2nd ed.). Sage Publications.
- Hwang, G. (2019). Challenges for innovative HRD in the era of the 4th industrial revolution. Asian Journal of Innovation & Policy, 8(2), 288-301.
- Jain, R. (2023). The Impact of Artificial Intelligence on Business: Opportunities and Challenges. SSRN.
- Jaiswal, A., Arun, C. J., & Varma, A. (2022). Rebooting employees: Upskilling for artificial intelligence in multinational corporations. International Journal of Human Resource Management, 33(6), 1179-1208.
- Jędrzejowska, M. (2024). AI in HR tech – Explore key trends shaping the HR sector. London: SpyroSoft.
- Jose, S. (2019). Innovation in recruitment and talent acquisition: A study on technologies and strategies adopted for talent management in IT sector. International Journal of Marketing & Human Resource Management, 10(3), 1-8.
- Kim, S. (2022). Working with robots: Human resource development considerations in human-robot interaction. Human Resource Development Review, 21(1), 48-74.
- Leeway-Hertz. (2024). AI in HR: Transforming how human capital is utilized and valued in modern workplaces. London: Hacket Group Company.
- Malik, N., Tripathi, S. N., Kar, A. K., & Gupta, S. (2022). Impact of artificial intelligence on employees working in industry 4.0 led organizations. International Journal of Manpower, 43(2), 334-354.
- Martínez-Morán, P. C., Urgoiti, J. M. F.-R., Díez, F., & Solabarrieta, J. (2021). The digital transformation of the talent management process: A Spanish business case. Sustainability, 13(4), 2264.
- Mazurchenko, A., & Maršíková, K. (2019). Digitally-powered human resource management: Skills and roles in the digital era. Acta Informatica Pragensia, 8(2), 72-87.
- Merlin, P. R., & Jayam, R. (2018). Artificial Intelligence in Human Resource Management. International Journal of Pure and Applied Mathematics, 119(17), 1891-1895.
- Odugbesan, J. A., Aghazadeh, S., Al Qaralleh, R. E., & Sogeke, O. S. (2023). Green talent management and employees’ innovative work behavior: The roles of artificial intelligence and transformational leadership. Journal of Knowledge Management, 27(3), 696-716.
- Panda, A., Pasumarti, S. S., & Hiremath, S. (2023). Adoption of artificial intelligence in HR practices: An empirical analysis. In The adoption and effect of artificial intelligence on human resources management (pp. 65-92).
- Pandey, S., & Khaskel, P. (2019). Application of AI in human resource management and Gen Y’s reaction. International Journal of Recent Technology and Engineering (IJRTE), 8(4), 2277-3878.
- 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), 1-28.
- Patton, M. (2014). Qualitative Research and Evaluation Methods: Integrating Theory and Practice (4th ed.). SAGE Publications.
- Pervin, N., & Mokhtar, M. (2022). The Interpretivist Research Paradigm: A Subjective Notion of a Social Context. International Journal of Academic Research in Progressive Education and Development, 11(2), 419-428.
- 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.
- Ravitch, S. M., & Carl, N. M. (2021). Qualitative research: Bridging the conceptual, theoretical, and methodological. Sage Publications.
- Roller, M. R., & Lavrakas, P. J. (2021). Applied qualitative research design: A total quality framework approach (2nd ed.). Guilford Press.
- Roy, S. (2022). Impact of Artificial Intelligence on Human Resource Management. International Journal of Research Publication and Reviews, (1), 1948-1952.
- Ryan, G. (2018). Introduction to positivism, interpretivism, and critical theory. Nursing Research & Marketing, 25(4), 14-20.
- Savin-Baden, M., & Major, C. H. (2023). Qualitative research: The essential guide to theory and practice (2nd ed.). Routledge.
- Saxena, A. (2020). The Growing Role of Artificial Intelligence in Human Resource. EPRA International Journal of Multidisciplinary Research, 6(8), 152-158.
- Singh, A., & Shaurya, A. (2021). Impact of Artificial Intelligence on HR practices in the UAE. Humanities and Social Sciences Communications, 8(1), 1-9.
- Smith, J. A. (Ed.). (2022). Qualitative psychology: A practical guide to research methods (4th ed.). Sage Publications.
- Stryker, C., & Kavlakoglu, E. (2024). What is artificial intelligence (AI)? New York: IBM.
- Swaminathan, R., & Mulvihill, T. M. (2022). Collaborative qualitative research. Guilford Press.
- Tracy, S. J. (2020). Qualitative research methods: Collecting evidence, crafting analysis, communicating impact (2nd ed.). Wiley-Blackwell.
- Wilhelmy, A., & Köhler, T. (2022). Qualitative Research in Work and Organizational Psychology Journals: Practices and Future Opportunities. European Journal of Work and Organizational Psychology, 31(2), 161-185.