HomeJournal of Interdisciplinary Perspectivesvol. 3 no. 6 (2025)

AI Transformation in the Workplace: A Comprehensive Review of Trends and Future Directions

Beberly T. Calugan | Irene P. Tanyag | Romer D. Tanyag | Anderson G. Dawigi

Discipline: others in technology

 

Abstract:

This study examines the multifaceted impacts of emerging artificial intelligence (AI) advancements on the global workforce, striking a balance between worker equity and AI-driven efficiency. The primary objectives are to examine the impacts of AI on automation, skill requirements, job displacement, and ethical concerns, and to propose suitable AI integration techniques. This study identifies key trends and their effects by employing a comprehensive literature review of academic research, industry reports, and policy documents. The main findings show that while AI increases productivity through automation and skill augmentation, it also necessitates significant workforce reskilling and presents serious ethical challenges regarding bias, privacy, and job security. This study highlights the importance of flexible regulatory frameworks and the growing significance of lifelong learning programs. Key discoveries in ethical AI research, precise algorithms, fair labor standards, and a human-centered approach to AI integration are highlighted. Moreover, this research underscores the need for collaboration among governments, businesses, and universities to ensure a just and sustainable AI-driven workforce. Based on this research, proactive reskilling and rigorous ethical standards are essential for managing the transformative impacts of AI on the labor force.



References:

  1. Abedin, J., Jamwal, A., Brahmchari, R. K., & Kumar, A. (2022). Applications of artificial intelligence and machine learning in fisheries. Vigyan Varta, 3(8), 127-130. https://tinyurl.com/ycxnmmfa
  2. Alaran, M., Lawal, S. K., Jiya, M. H., Egya, S. A., Ahmed, M. M., Abdulsalam, A., Haruna, U. A., Musa, M. K., & Lucero‐Prisno, D. E. (2025). Challenges and opportunities of artificial intelligence in African health space. Digital Health, 11. SAGE Publishing. https://doi.org/10.1177/20552076241305915
  3. Aldoseri, A., Al‐Khalifa, K. N., & Hamouda, A. M. S. (2024). Methodological approach to assessing the current state of organizations for ai-based digital transformation. Applied System Innovation, 7(1), 14. https://doi.org/10.3390/asi7010014
  4. Alghizzawi, M., Ahmed, E., Ezmigna, I., Ezmigna, A. A. R., & Omeish, F. (2024). The relationship between artificial intelligence and digital marketing in business companies. In B. Awwad (Ed.), The AI Revolution: Driving Business Innovation and Research (Vol. 525, pp. 885–895). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-54383-8_67
  5. Aksoy, L., Allerstorfer, P., Cadet, F., Cook, P., Keiningham, T., & Koser, M. (2020). Building service businesses in Africa: Introducing the business builder model. Thunderbird International Business Review, 62(1), 5-16. https://doi.org/10.1002/tie.22094
  6. Ayanponle, L. O., Elufioye, O. A., Asuzu, O. F., Ndubuisi, N. L., Awonuga, K. F., & Daraojimba, R. E. (2024). The future of work and human resources: A review of emerging trends and HR’s evolving role. International Journal of Science and Research Archive, 11(2), 113-124. https://doi.org/10.30574/ijsra.2024.11.2.0151
  7. Bobitan, N., Dumitrescu, D., Popa, A. F., Sahlian, D. N., & Turlea, I. C. (2024). Shaping tomorrow: Anticipating skills requirements based on the integration of artificial intelligence in business organizations—a foresight analysis using the scenario method. Electronics, 13(11), 2198. https://doi.org/10.3390/electronics13112198
  8. Bozkurt, A., Xiao, J., Farrow, R., Bai, J. Y. H., Nerantzi, C., Moore, S., Dron, J., Stracke, C. M., Singh, L., Crompton, H., Koutropoulos, A., Terentev, E., Pazurek, A., Nichols, M., Sidorkin, A. M., Costello, E., Watson, S., Mulligan, D., Honeychurch, S., … Asino, T. I. (2024). The manifesto for teaching and learning in a time of generative ai: A critical collective stance to better navigate the future. Open Praxis, 16(4), 487–513. https://doi.org/10.55982/openpraxis.16.4.777
  9. Capraro, V., Lentsch, A., Acemoglu, D., Akgun, S., Akhmedova, A., Bilancini, E., Bonnefon, J.-F., Brañas-Garza, P., Butera, L., Douglas, K. M., Everett, J. A. C., Gigerenzer, G., Greenhow, C., Hashimoto, D. A., Holt-Lunstad, J., Jetten, J., Johnson, S., Kunz, W. H., Longoni, C., ... Viale, R. (2024). The impact of generative artificial intelligence on socioeconomic inequalities and policy making. PNAS Nexus, 3(6), Article pgae191. https://doi.org/10.1093/pnasnexus/pgae191
  10. Cazzaniga, M., Jaumotte, F., Li, L., Melina, G., Panton, A. J., Pizzinelli, C., Rockall, E. J., & Mendes Tavares, M. (2024). Gen-AI: Artificial intelligence and the future of work (Staff Discussion Note No. 2024/001). International Monetary Fund. https://doi.org/10.5089/9798400262548.006
  11. Chiu, Y. T., Zhu, Y. Q., & Corbett, J. (2021). In the hearts and minds of employees: A model of pre-adoptive appraisal toward artificial intelligence in organizations. International Journal of Information Management, 60, 102379. https://doi.org/10.1016/j.ijinfomgt.2021.102379
  12. Chou, D. (2024). Transformative impact of AI and automation in revolutionizing supply chain management (Master’s seminar research paper). University of Wisconsin–Platteville. https://tinyurl.com/35wt5bs8
  13. Dey, D. N. C. (2025). Enhancing educational tools through artificial intelligence in perspective of need of AI. https://doi.org/10.2139/ssrn.5031275
  14. Dilmegani, C. (2025). AI in government: Examples & challenges in 2025. AIMultiple. Retrieved from https://research.aimultiple.com/ai-government/
  15. Epstein, Z., Hertzmann, A., Herman, L., Mahari, R., Frank, M. R., Groh, M., Schroeder, H., Smith, A., Akten, M., Fjeld, J., Farid, H., Leach, N., Pentland, A., & Russakovsky, O. (2023). Art and the science of generative AI: A deeper dive. https://doi.org/10.48550/ARXIV.2306.04141
  16. Espinosa, J. C., Sánchez, L. M., & Pereira, M. A. (2023). Benefits of Artificial Intelligence in human talent management. Multidisciplinar (Montevideo), 1, 14. https://doi.org/10.62486/agmu202314
  17. Farayola, O. A., Abdul, A. A., Irabor, B. O., & Okeleke, E. C. (2023). Innovative business models driven by AI technologies: A review. Computer Science & IT Research Journal, 4(2), 85-110. https://doi.org/10.51594/csitrj.v4i2.608
  18. Frank, M. R., Autor, D., Bessen, J. E., Brynjolfsson, E., Cebrian, M., Deming, D. J., Feldman, M., Groh, M., Lobo, J., Moro, E., Wang, D., Youn, H., & Rahwan, I. (2019). Toward understanding the impact of artificial intelligence on labor. Proceedings of the National Academy of Sciences, 116(14), 6531–6539. https://doi.org/10.1073/pnas.1900949116
  19. Gartner. (2024). AI in government. Retrieved from https://tinyurl.com/385x26xf
  20. Gerlich, M. (2024). Public anxieties about AI: Implications for corporate strategy and societal impact. Administrative Sciences, 14(11), 288. https://doi.org/10.3390/admsci14110288
  21. IntelliStride. (2024). How Singapore’s smart traffic system is redefining urban mobility. Retrieved from https://tinyurl.com/yc7ek287
  22. Kumar, P., Choubey, D., Amosu, O. R., & Ogunsuji, Y. M. (2024). AI-enhanced inventory and demand forecasting: Using AI to optimize inventory management and predict customer demand. World Journal of Advanced Research and Reviews, 23(01), 1931–1944. https://doi.org/10.30574/wjarr.2024.23.1.2173
  23. Lee, J., Suh, T., Roy, D., & Baucus, M. (2019). Emerging technology and business model innovation: the case of artificial intelligence. Journal of Open Innovation: Technology, Market, and Complexity, 5(3), 44. https://doi.org/10.3390/joitmc5030044
  24. Malhotra, K., Wong, B. N. X., Lee, S., Franco, H., Singh, C., Cabrera Silva, L. A., Iraqi, H., Sinha, A., Burger, S., Breedt, D. S., Goyal, K., Dagli, M. M., & Bawa, A. (2023). Role of artificial intelligence in global surgery: A review of opportunities and challenges. Cureus. https://doi.org/10.7759/cureus.43192
  25. Manthena, S. R. L. (2021). Impact of Artificial Intelligence on Recruitment and its Benefits. International Journal of Innovative Research in Engineering & Multidisciplinary Physical Sciences, 9(5), 1-1. https://doi.org/10.37082/ijirmps.2021.v09si05.013
  26. 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: The International Journal of an Emerging Transdiscipline, 26, 039–068. https://doi.org/10.28945/5078
  27. Morley, J., Elhalal, A., Garcia, F., Kinsey, L., Mökander, J., & Floridi, L. (2021). Ethics as a service: A pragmatic operationalisation of AI ethics. Minds and Machines, 31(2), 239–256. https://doi.org/10.1007/s11023-021-09563-w
  28. Nasir, S., Khan, R. A., & Bai, S. (2024). Ethical framework for harnessing the power of AI in healthcare and beyond. IEEE Access, 12, 31014-31035. https://doi.org/10.1109/access.2024.3369912
  29. National University. (2024). 131 AI statistics and trends for 2024. Retrieved from https://www.nu.edu/blog/ai-statistics-trends/
  30. OECD. (2024). Fostering an inclusive digital transformation as AI spreads among firms. Retrieved from https://doi.org/10.1787/5876200c-en
  31. OECD. (2024). Using AI in the workplace: Opportunities, risks and policy responses. The Organisation for Economic Co-operation and Development. Retrieved from https://tinyurl.com/mr3n4sbp
  32. OECD. (2022). AI in the public sector: Policy implications and best practices. The Organisation for Economic Co-operation and Development. Retrieved from https://tinyurl.com/mrweh9u7
  33. Pachegowda, C. (2024). The global impact of AI-artificial intelligence: Recent advances and future directions, a review. arXiv. https://doi.org/10.48550/ARXIV.2401.12223
  34. Patil, D. (2024). Impact of artificial intelligence on employment and workforce development: Risks, opportunities, and socioeconomic implications. https://doi.org/10.2139/ssrn.5010441
  35. Pavashe, A. S., Kadam, P. D., Zirange, V. B., & Katkar, R. D. (2023). The impact of artificial intelligence on employment and workforce trends in the post-pandemic era. International Journal for Research in Applied Science and Engineering Technology, 11(11), 154–157. https://doi.org/10.22214/ijraset.2023.56418
  36. Prasanth, A., Densy, J. V., Surendran, P., & Bindhya, T. (2023). Role of artificial intelligence and business decision making. International Journal of Advanced Computer Science and Applications, 14(6). https://doi.org/10.14569/ijacsa.2023.01406103
  37. Route Fifty. (2025). May be a major year for generative AI adoption across government. Retrieved from https://tinyurl.com/2etfrv6v
  38. Saint-Martin, A. (2021). The impact of artificial intelligence on the labour market: What do we know so far? Retrieved from https://tinyurl.com/mpyanyjr
  39. Sharma, R. K. (2025). Ethics in AI: Balancing innovation and responsibility. International Journal of Science and Research Archive, 14(1), 544–551. https://doi.org/10.30574/ijsra.2025.14.1.0122
  40. Slimi, Z., & Carballido, B. V. (2023). Navigating the ethical challenges of artificial intelligence in higher education: An analysis of seven global AI ethics policies. TEM Journal, 590–602. https://doi.org/10.18421/TEM122-02
  41. Talmage-Rostron, M. (2024). How will artificial intelligence affect jobs 2024-2030. Nexford University. Retrieved from https://www.nexford.edu/insights/how-will-ai-affect-jobs
  42. Tiwari, R. (2023). The impact of AI and machine learning on job displacement and employment opportunities. International Journal of Engineering Technologies and Management Research, 7(1), 1-9. https://doi.10.55041/IJSREM17506
  43. Vemuri, N., Thaneeru, N., & Tatikonda, V. M. (2023). Artificial intelligence -driven adaptive infrastructure for urban mobility. International Journal of Development Research, 13(12), 64509-64513. https://doi.org/10.37118/ijdr.27837.12.2023
  44. Vo, T. T. E., Ko, H., Huh, J. H., & Kim, Y. (2021). Overview of smart aquaculture system: Focusing on applications of machine learning and computer vision. Electronics, 10(22), 2882. https://doi.org/10.3390/electronics10222882
  45. van der Vorst, T., & Jelicic, N. (2019). Artificial intelligence in education: Can AI bring the full potential of personalized learning to education? Paper presented at the 30th European Regional Conference of the International Telecommunications Society (ITS), Helsinki, Finland, June 16–19, 2019. International Telecommunications Society. https://hdl.handle.net/10419/205222
  46. Walter, S. (2023). AI impacts on supply chain performance: A manufacturing use case study. Discover Artificial Intelligence, 3(1), 18. https://doi.org/10.1007/s44163-023-00061-9
  47. Wijayati, D. T., Rahman, Z., Rahman, M. F. W., Arifah, I. D. C., & Kautsar, A. (2022). A study of artificial intelligence on employee performance and work engagement: The moderating role of change leadership. International Journal of Manpower, 43(2), 486-512. https://doi.org/10.1108/ijm-07-2021-0423
  48. Zaman, K. (2022). Transformation of marketing decisions through artificial intelligence and digital marketing. Journal of Marketing Strategies, 4(2), 353-364. https://doi.org/10.52633/jms.v4i2.210
  49. Ziakis, C., & Vlachopoulou, M. (2023). Artificial intelligence in digital marketing: Insights from a comprehensive review. Information, 14(12), 664. https://doi.org/10.3390/info14120664