Impact of AI in HRM Practicing Job Satisfaction in Any other Hospital
Abstract
Artificial Intelligence (AI) is becoming more prevalent in organizations, presenting both opportunities and challenges for Human Resource Management (HRM). The integration of AI in HRM reflects the dual potential for advancement and complexities within organizational dynamics. Striking a balance in leveraging AI's benefits while addressing its challenges is crucial for effective HRM. In the medical field, Artificial Intelligence (AI) in hospitals involves the application of advanced computational algorithms and machine learning to improve various aspects of healthcare. From aiding in precise diagnostics through the analysis of medical imaging and patient data to facilitating personalized treatment plans based on genetic information and medical history, AI enhances clinical decision-making and overall patient care and employment. In the specific case of HRM in hospitals, AI has become increasingly relevant in recent years, so organizations must be prepared for pre-changes and post-changes. This study is to analyze and explore employee’s perception in hospital of AI on their job satisfaction. Considering employee suggestions will effectively navigate and mitigate the consequences of technological changes in organizations, fostering collaboration and enhancing overall satisfaction. This approach values diverse perspectives, promoting a shared responsibility for adapting to the evolving technological landscape. For that researcher, a questionnaire consists of 30 questions about their perception and impact of AI on their job satisfaction at a variety of levels in the organization. The personnel within the hospital comprise a diverse array of roles, including staff in healthcare delivery, customer care, and financial management. The research findings underscore a need for enhanced knowledge in structural and employee-related domains, particularly addressing job satisfaction challenges. The study suggests that both employees and employers should embark on a trajectory of continuous learning to stay abreast of technological advancements. This imperative aligns with the evolving landscape of the healthcare industry, emphasizing the significance of ongoing professional development to optimize organizational efficiency and employee contentment.
References
Aitken-fox, E., Coffey, J., Dayaram, K., McKenna, S., & Tian, A. (2021). The changing role of human resource management through crisis: From response to recovery. Call for Papers. Personnel Review.
Asar, A. (2020). Five ways AI can help revolutionize mental health. Retrieved from https://www.forbes.com/sites/forbestechcouncil/2020/08/19/five-ways-ai-can-help-revolutionize-mental-healthcare/?sh=69c416ee13ab
Bhatt, S. (2021, September 25). Investing in AI practices increases employee productivity and assures employee well-being: Experts – netherworld. Retrieved from https://hr.economictimes.india-times.com/news/hrtech/investing-in-ai-practices increasesemployee-productivity-and-assures-employee-wellbeing-experts/86501097. Accessed on November 8, 2021.
Bondarouk, T., & Brewster, C. (2016). Conceptualizing the future of HRM and technology research. The International Journal of Human Resource Management, 27(21), 2652–2671. doi:10.1080/09585192.2016.1232296
Brassey, J., Güntner, A., Isaak, K., & Silberzahn, T. (2021, July 28). Using digital tech to support employees’ mental health and resilience. Retrieved from
https://www.mckinsey.com/industries/life-sciences/our-insights/using-digital-tech-to-support-employees-mental-health-and-resil-ience. Accessed on November 9, 2021.
Carnevale, J. B., & Hatak, I. (2020). Employee adjustment and well-being in the era of COVID-19: Implications for human resource management. Journal of Business Research, 116, 183–187. doi:10.1016/j.jbusres.2020.05.037
Cascio, W. F. (2019). Training trends: Macro, micro, and policy issues. Human Resource Management Review, 29(2), 284–297
Chauhan, P. S., & Kshetri, N. (2022). The role of data and artificial intelligence in driving diversity, equity, and inclusion. Computer, 55(4), 88–93. doi:10.1109/MC.2022.3149017
Chen, Z. (2021). Influence of working from home during the COVID-19 crisis and HR practitioner response. Frontiers in Psychology, 12. doi:10.3389/fpsyg.2021.710517
Chen, Z. (2022). Artificial intelligence-virtual trainer: innovative didactics aimed at personalized training needs. Journal of the Knowledge Economy, 1–19. doi:10.1007/s13132-022-00985-0AI in HRM 53
Cibenko, T., Dunlop, A., & Kunkel, N. (2020). Human experience platforms. Deloitte Insights. Retrieved from https://www2.deloitte.com/us/en/insights/focus/tech-trends/2020/human-experience-platforms.html
Deloitte. (2022). State of AI in the Enterprise fifth edition uncovers four key actions to maximize AI value. Retrieved from https://www2.deloitte.com/us/en/pages/about-deloitte/articles/press-releases/deloitte-state-of-ai-fifth-edition-report.html
Dirani, K. M., Abadi, M., Alizadeh, A., Barhate, B., Garza, R. C., Gunasekara, N., … Majzun, Z. (2020). Leadership competencies and the essential role of human resource development in times of crisis: A response to Covid-19 pandemic. Human Resource Development International, 23(4), 380–394. doi:10.1080/13678868.2020.1780078
Faliagka, E., Iliadis, L., Karydis, I., Rigou, M., Sioutas, S., Tsakalidis, A., & Tzimas, G. (2014). Online consistent ranking on e-recruitment: Seeking the truth behind a well-formed CV. Artificial Intelligence Review, 42, 515–528. doi:10.1007/s10462-013-9414-y
Garg, S., Sinha, S., Kar, A. K., & Mani, M. (2021). A review of machine learning applications in human resource management. International Journal of Productivity and Performance Management, 71(5), 1590–1610.
Geetha, R., & Bhanu, S. R. D. (2018). Recruitment through artificial Intelligence: A conceptual study. International Journal of Mechanical Engineering and Technology, 9(7), 63–70.
Goasduff, L. (2018). Emotion AI will personalize interactions. Retrieved from https://www.gartner.com/smarterwithgartner/emotion-ai-will-personalize-interactions#:∼:text=How%20artificial%20intelligence%20is%20being,to%20human%20emotions%20and%20moods
Grima, S., Kizilkaya, M., Sood, K., & ErdemDelice, M. (2021). The perceived effectiveness of block-chain for digital operational risk resilience in the European Union insurance market sector. Journal of Risk and Financial Management, 14(8), 363. doi:10.3390/jrfm14080363
Guenole, N., & Feinzig, S. (2019). The business case for AI in HR. Retrieved from https://www.ibm.com/talent-management/ai-in-hr-business-case/
Hamouche, S. (2021). Human resource management and the Covid-19 crisis: Implications, challenges, opportunities, and future organizational characteristics. Journal of Management & Organization, 1–16. doi:10.1017/jmo.2021.15
Harter, J., & Adkins, A. (2015). What do great managers do to engage employees? Retrieved from https://hbr.org/2015/04/what-great-managers-do-to-engage-employees
He, E. (2018). Can artificial Intelligence make work more human? Strategic HR Review, 17(5), 263–264. doi:10.1108/SHR-10-2018-146
Huang, X., Yang, F., Zheng, J., Feng, C., & Zhang, L. (2023). Personalized human resource management via HR analytics and artificial intelligence: Theory and implications. Asia Pacific Management Review.
Hughes, C., Robert, L., Frady, K., & Arroyos, A. (2019). Artificial intelligence, employee engagement, fairness, and job outcomes. In Managing technology and middle- and low-skilled employees (pp. 61–68). Bingley: Emerland.
Jonsson, K., Mathiassen, L., & Holmstrom, J. (2018). Representation and mediation in €digitalized work: Evidence from maintenance of mining machinery. Journal of Information Technology, 33(3), 216–232. doi:10.1057/s41265-017-0050-x
Jordan, T. H. (2011). Moving from diversity to inclusion. Profiles in-Diversity Journal.
Kanten, S., & Sadullah, O. (2012). Empirical research on relationship quality of work life and work engagement. Procedia-Social and Behavioral Sciences, 62, 360–366. doi:10.1016/j.sbspro.2012.09.057
Kataria, A., Garg, P., & Rastogi, R. (2019). Do high-performance HR practices augment OCBs? The role of psychological climate and work engagement. International Journal of Productivity and Performance Management, 68(6), 1057–1077. doi:10.1108/IJPPM-02-2018-0057
Kelley, J. (2021). Why many people are turning toward robots and AI to help support their mental health and careers? Retrieved from www.forbes.com/sites/jackkelly/2021/10/26/why-many-people-are-turning-toward-robots-and-ai-to-help-support-their-mental-health-and-careers/?sh=7a8f2d6a77bf. Accessed on November 2, 2022.
Kent, J. (2021). What role could artificial intelligence play in mental healthcare? Retrieved from https://healthitanalytics.com/features/what-role-could-artificial-intelligence-play-in-mental-healthcare. Accessed on November 4, 202254 AKANSHA MER
Khan, F., & Mer, A. (2023). Embracing Artificial Intelligence Technology: Legal Implications with Special Reference to European Union Initiatives of Data Protection. In K. Sood, B.
Balusamy, S. Grima (Eds.), Digital Transformation, Strategic Resilience, Cyber Security and Risk Management (Contemporary Studies in Economic and Financial Analysis, Vol. 111C, pp. 119–141). Bingley: Emerald.
Lund, S., Madgavkar, A., Manyika J., & Smit, S. (2020). What’s next for remote work: An analysis of 2,000 tasks, 800 jobs, and nine countries. McKinsey Quarterly. Retrieved from https://www.mckin-sey.com/featured-insights/future-of-work/whats-next-forremote-work-an-analysis-of-2000-tasks-800-jobs-and-nine-countries
Mahto, M., Miller, D., Bodan, M., & Sniderman, B. (2022). AI for work relationships may be a great untapped opportunity. Retrieved from https://www2.deloitte.com/us/en/insights/
industry/public-sector/how-social-ai-is-transforming-the-workplace.html
Majumder, S., & Mondal, A. (2021). Are chatbots useful for human resource management? International Journal of Speech Technology, 24, 969–977.
Marcos-Pablos, S., & García-Peñalvo, F. J. (2021, September). Emotional intelligence in robotics: A scoping review. In International conference on disruptive technologies, tech ethics and artificial intelligence (pp. 66–75). Cham: Springer.
Martinez-Gil, J., Paoletti, A. L., & Pichler, M. (2020). A novel approach for learning how to automatically match job offers and candidate profiles. Information Systems Frontiers, 22(6), 1265–1274.
Mckinsey & Company (2021). Employees want more certainty about post-pandemic working arrangements—even if you don’t yet know what to tell them. Retrieved from https://www.mckinsey.com/capabilities/people-and -organizational-performance/our-insights/what-empl oyees-are-saying-about-the-future-of-remote-work. Assessed on October 20, 2022.
Mer, A. (2022). A study on antecedents and consequences of work engagement with special reference to NGOs in Uttarakhand. Ph.D. thesis, Banasthali Vidyapith, India. Shodhganga. Retrieved from http://hdl.handle.net/10603/359946
Mer, A., & Srivastava, A. (2023). Employee engagement in the new normal: Artificial intelligence as a buzzword or a game changer? In The adoption and effect of artificial intelligence on human resources management, Part 7A (pp. 15–46). Bingley: Emerald.
Mer, A., & Vijay, P. (2021). Towards enhancing work engagement in the service sector in India: A conceptual model. In Doing business in emerging markets (pp. 118–135). India: Routledge.
Mer, A., & Virdi, A. S. (2022). Artificial intelligence disruption is on the brink of revolutionizing HR and marketing functions. Impact of Artificial Intelligence on Organizational Transformation (pp.
–19).
Mer, A., & Virdi, A. S. (2023). Navigating the paradigm shift in HRM practices through the lens of artificial intelligence: A post-pandemic perspective. In The adoption and effect of artificial intelligence on human resources management, Part 7A (pp. 123–154). Bingley: Emerald.
Mer, A., Virdi, A. S., & Sengupta, S. (2022). Unleashing the antecedents and consequences of work engagement in NGOs through the lens of JD-R Model: Empirical evidence from India. VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations (pp. 1–13). doi:10.1007/s11266-022-00503-5
Moore, S. (2018). 13 Surprising uses for emotion AI technology. Retrieved from https://www.gartner.com/smarterwithgartner/13-surprising-uses-for-emotion-ai-technology
Olan, F., Arakpogun, E. O., Suklan, J., Nakpodia, F., Damij, N., & Jayawickrama, U. (2022). Artificial intelligence and knowledge sharing: Contributing factors to organizational performance. Journal of Business Research, 145, 605–615.
Oracle. (2020). AI@Work Study 2020 As uncertainty remains, anxiety and stress reach a tipping point at work artificial Intelligence fills the gaps in workplace mental health support. Retrieved from https://www.oracle.com/a/ocom/docs/oracle-hcm-ai-at-work.pdf
Ose, S. O., Færevik, H., Kaasbøll, J., Lindgren, M., T ,haulow, K., Antonsen, S., & Burkeland, O. (2019). Exploring the potential for use of virtual reality technology in the treatment of severe mental illness among adults in mid-Norway: Collaborative research between clinicians and researchers.
