Acceptance of artificial intelligence in selected manufacturing industries in San Pablo City: An input on human resource plan
Mara Grace G. Maraver & Preciosa D. Villacruel
Abstract
This study focuses on developing a human resource (HR) plan for integrating Artificial Intelligence (AI) in HR management across selected manufacturing companies. It evaluated the AI literacy of HR employees, their perceptions of AI's usefulness and ease of use, the challenges they face with AI integration, and how AI is being developed within HR management. Employing a mixed-method design, the study gathered data from forty-eight (48) HR employees using a validated questionnaire and conducted thematic analysis on interviews with 10 selected participants. The findings revealed that HR employees are generally literate in AI and believe it enhances their work productivity and performance. Interestingly, their general knowledge of AI did not significantly affect their perceptions of its usefulness or ease of use. The main challenges identified included the cost of technology, integration difficulties, data privacy and security issues, and the need for further capacity building. The study resulted in a comprehensive HR plan designed to guide the integration of AI into HR practices. The plan is recommended for broader implementation, with suggestions for evaluating its effectiveness, engaging in partnerships, conducting cost-benefit analyses, and formulating continuous learning plans. It advises companies to develop their own AI strategies that prioritize ethical practices, continuous learning, and a culture of innovation and security.
Keywords
artificial intelligence, compensation management, employee relationships, responsible artificial intelligence usage, usefulness and ease of use
Author information & Contribution
Mara Grace G. Maraver. Master of Business Administration, Pamantasan ng Lunsod ng San Pablo (PLSP). Email: maramaraver@gmail.com
Preciosa D. Villacruel. Doctor of Philosophy, Pamantasan ng Lungsod ng San Pablo (PLSP), Graduate School Dean.
“All authors equally contributed to the conception, design, preparation, data gathering and analysis, and writing of the manuscript. All authors read and approved the final manuscript.”
Disclosure statement
No potential conflict of interest was reported by the author(s).
Funding
This work was not supported by any funding.
AI Declaration
Notes
This paper is presented in 5th International Conference on Multidisciplinary Industry and Academic Research (ICMIAR)
Acknowledgement
References
Acemoglu, D. (2022). Conversation with Daron Acemoglu on AI, automation and skills. In In-ternational Conference on AI in Work, Productivity and Skills (AI-WIPS). OECD, Berlin, Germany. https://www.oecd-events.org/2022-ai-wips/session/f0a87214-4d83-ec11-a507-a04a5e7d20d9
Albassam, W. (2023). The power of artificial intelligence in recruitment: An analytical review of current ai-based recruitment strategies. International Journal of Professional Business Review. 8 (6). https://doi.org/10.26668/businessreview/2023.v8i6.2089
Arasa, D. (2023). AI’s impact on the Philippines: Today, BPOs. Tomorrow, other sectors. Inquirer, Artificial Intelligence. https://technology.inquirer.net/125497/
Aron, S. (2024). Responsible and ethical use of AI in organizations. https://www.financialexpress.com/opinion/responsible-and-ethical-use-of-ai-in-organizations/3413539/
Basyal, D. K., & Wan, P. D. J. (2020). Employees’ resistance to change and technology acceptance in Nepal. South Asian Studies, 32(2), 351 – 365.
Benhamou, S. (2020). Artificial intelligence and the future of work. Revue d’économie industrielle, 169, 57-88. https://doi.org/10.4000/rei.8727
Chen, J., Ramanathan, L., & Alazab, M. (2021). Holistic big data integrated artificial intelligent modeling to improve privacy and security in data management of smart cities. Microprocessors and Microsystems, 81, 103722. https://doi.org/10.1016/j.micpro.2020.103722
Chuang, S. (2022). Indispensable skills for human employees in the age of robots and AI. European Journal of Training and Development 48 (1/2), 179-195. https://doi.org/10.1108/EJTD-06-2022-0062
Crews, J. (2023). AI’s dark side: The potential misuses of artificial intelligence & why you should be concerned. https://www.linkedin.com/
Crismundo, K. (2021). AI processing seen as next BPO for PH. https://www.pna.gov.ph/articles/1151550
Dalcher, D. (2022). Rediscovering innovation in project management: A post-crisis perspective. PM World Journal 9 (4), 1-4.
Daugherty, P. & Wilson, H. (2019). Using AI to make knowledge workers more effective. Harvard Business Review. https://hbr.org/2019/04/using-ai-to-make-knowledge-workers-more-effective
Davenport, T. H., Guha, A., Grewal, D., & Bressgott, T. (2020). How artificial intelligence will change the future of marketing. Journal of the Academy of Marketing Science, 48(1), 24-42. https://doi.org/10.1007/s11747-019-00672-z
Davenport, T. H., Harris, J., & Shapiro, J. (2018). Competing on talent analytics. Harvard Business Review, 96(5), 52-63.
Davenport, T. H., & Ronanki, R. (2018). Artificial intelligence for the real world. Harvard Business Review, 96(1), 107–116.
Dhamija, P., Gupta, S., & Bag, S. (2019). Measuring of job satisfaction: The use of quality of work life factors. Benchmarking: An International Journal, 26, 871-892. https://doi.org/10.1108/BIJ-06-2018-0155
Floridi, L., Cowls, J. & Beltrametti, M. (2018). AI4People—An ethical framework for a good AI society: Opportunities, risks, principles, and recommendations. Minds & Machines 28, 689–707. https://doi.org/10.1007/s11023-018-9482-5
Fountaine, T., McCarthy, B., & Saleh, T. (2019). Building the AI-powered organization. Harvard Business Review, 97(4), 62-73.
Davis, F. D. (1987). User acceptance of information systems: the technology acceptance model (TAM). https://deepblue.lib.umich.edu/bitstream/handle/2027.42/35547/b1409190.0001.001.pdf
Gonzales, S.M. & Villacruel, P.D. (2024). Exploring students’ experiences in the dynamic learning program model. International Journal of Educational Management and Development Studies, 5 (2), 1-26. https://doi.org/10.53378/353051
Hancock, J. T., Naaman, M., & Levy, K. (2020). AI-mediated communication: Definition, research agenda, and ethical considerations. Journal of Computer-Mediated Communication, 25(1), 89-100. https://doi.org/10.1093/jcmc/zmz022
Jaiswal, A., Arun, C. J., & Varma, A. (2022). Rebooting employees: Upskilling for artificial intelligence in multi-national corporations. International Journal of Human Resource Management, 33(6), 1179-1208. https://doi.org/10.1080/09585192.2021.1891114
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
Kelley, S. (2022). Employee perceptions of the effective adoption of AI principles. J Bus Ethics 178, 871–893. https://doi.org/10.1007/s10551-022-05051-y
Leinen, P., Esders, M., Schütt, K. T., Wagner, C., Müller, K. R., & Tautz, F. S. (2020). Autonomous robotic nanofabrication with reinforcement learning. Science Advances, 6 (36), eabb6987. https://doi.org/10.1126/sciadv.abb6987
Marr, B. (2024). The biggest challenges and pitfalls of data-driven, AI-Enabled HR. https://www.forbes.com/sites/bernardmarr/2024/01/12/the-biggest-challenges-and-pitfalls-of-data-driven-ai-enabled-hr/?sh=1004ba8c777f
Malik, A., De Silva, M. T., Budhwar, P., & Srikanth, N. R. (2021). Elevating talents’ experience through innovative artificial intelligence-mediated knowledge sharing: Evidence from an IT-multinational enterprise. Journal of International Management, 27(4), 100871. https://doi.org/10.1016/j.intman.2021.100871
Mcghee, R. (2022). How to implement new technology training. https://unboxedtechnology.com/
Morandini, S., Fraboni, F., De Angelis, M., Puzzo, G., Giusino, D., & Pietrantoni, L. (2023). The impact of artificial intelligence on workers’ skills: Upskilling and reskilling in organisations. Informing Science, 26, 39-68. https://cris.unibo.it/handle/11585/917132
OECD (2021). Artificial intelligence and employment. https://www.oecd.org/en/topics/policy-issues/future-of-work.html
Ogolodom, M.P., Mbaba, A.N., Johnson, J., Chiegwu, H.U., Ordu, K.S. & Okej, M.C. (2023). Knowledge and perception of healthcare workers towards the adoption of artificial intelligence in healthcare service delivery in Nigeria. AG Salud 1 (16).
Palos-Sánchez, P.R., Baena-Luna, P., Badicu, A. & Infante-Moro, J.C. (2023) Artificial intelligence and human resources management: A bibliometric analysis. Applied Artificial Intelligence, 36:1. https://doi.org/10.1080/08839514.2022.2145631
Pestano, T. (2018). How technology is changing the Filipino workplace. Manila Recruitment. https://manilarecruitment.com/manila-recruitment-articles-advice/technology-changing-filipino-workplace/
PWC Report (2021). Artificial intelligence in HR: a No-brainer. https://www.pwc.nl/nl/assets/documents/artificial-intelligence-in-hr-a-no-brainer.pdf
Sanyaolu, E. & Atsaboghena, R. (2022). Role of artificial intelligence in human resource management: Overview of its benefits and challenges. http://dx.doi.org/10.13140/RG.2.2.22297.29283
Schwaeke, J., Peters, A., Kanbach, D. K., Kraus, S., & Jones, P. (2024). The new normal: The status quo of AI adoption in SMEs. Journal of Small Business Management, 1–35. https://doi.org/10.1080/00472778.2024.2379999
Shirota, Y., Fujimaki, M., Tsujiura, E., Morita, M., & Machuca, J. A. D. (2021). A SHAP value-based approach to stock price evaluation of manufacturing companies. In 2021 4th International Conference on Artificial Intelligence for Industries (AI4I) (pp. 75-78). IEEE. https://doi.org/10.1109/AI4I51902.2021.00026
Skil AI (2020). AI recruiter Bot for candidate acquisition. Chatbots Life. https://chatbotslife.com/ai-recruiter-bot-for-candidate-acquisition-467812712262
Stanke, B. (2023). How AI can help develop a strategic plan. https://www.bobstanke.com/blog/ai-for-strategic-planning
Sucipto, H. (2024). The impact of artificial intelligence (AI) on human resource management practices. Management Studies and Business Journal (PRODUCTIVITY), 1(1), 138-145. https://doi.org/10.62207/xey9mx18
Thames, L., & Schaefer, D. (2016). Software-defined cloud manufacturing for industry 4.0. Procedia cirp, 52, 12-17. https://doi.org/10.1016/j.procir.2016.07.041
Wang, B., Rau, P., & Yuan, T. (2022). Measuring user competence in using artificial intelligence: validity and reliability of artificial intelligence literacy scale. Behaviour & Information Technology. https://doi.org/10.1080/0144929X.2022.2072768
Wisetsri, W., Donthu, S., Mehbodniya, A., Vyas, S., Quiñonez-Choquecota, J., & Neware, R. (2022). An investigation on the impact of digital revolution and machine learning in supply chain management. Materials Today: Proceedings, 56, 3207-3210. http://dx.doi.org/10.1016/j.matpr.2021.09.367
World Economic Forum. (2019). World Economic Forum Annual Meeting [Conference session]. https://www.wefo-rum.org/events/world-economic-forum-annual-meeting-202
Wylde, V., Rawindaran, N., Lawrence, J., Balasubramanian, R., Prakash, E., Jayal, A., & Platts, J. (2022). Cybersecurity, data privacy and blockchain: A review. SN computer science, 3(2), 127. https://doi.org/10.1007/s42979-022-01020-4
Zhang, L. (2023). How to use AI to improve employee performance and engagement? Fastcompany. https://www.fastcompany.com/90834773/how-to-use-ai-to-improve-employee-performance-and-engagement
Zirar, A., Ali, S. I., & Islam, N. (2023). Worker and workplace Artificial Intelligence (AI) coexistence: Emerging themes and research agenda. Technovation, 124, 102747. https://doi.org/10.1016/j.technovation.2023.102747
Cite this article:
Maraver, M.G. & Villacruel, P.D. (2024). Acceptance of artificial intelligence in selected manufacturing industries in San Pablo City: An input on human resource plan. Industry and Academic Research Review, 2(1), 72-96. https://doi.org/10.53378/iarr.924.121
License:
This work is licensed under a Creative Commons Attribution (CC BY 4.0) International License.
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