The Role of AI Enablement in Organizational Change: A Systematic Review of Challenges and Opportunities
DOI:
https://doi.org/10.66635/ed7mr214Keywords:
Entrepreneurship, Sustainable Transformation, SMEs, Innovation, Emerging EconomiesAbstract
The way organizations operate is being transformed by artificial intelligence (AI). It is transforming the structures, decision-making and value creation of companies. One of the most significant advantages of AI is enhanced efficiency and innovation, although the technology also has issues to do with ethics, governance, and change management. It is essential to know the advantages and obstacles to effective use of AI and technology. This paper will discuss the opportunities and challenges of applying AI and related technologies to transform organizations. We have examined research articles published in the last five years (2019-2026) in large academic databases, including Scopus and Web of Science. These results show that there are a number of challenges in transforming with AI: low quality of data, lack of skills among workers, worker resistance and difficulty in adapting, ethical issues, transparency problems, and effective leadership are required. Meanwhile, AI opens valuable prospects: enhanced processes, more informed decisions made with data, enhanced learning, increased innovation, and higher stakeholder value. The review is especially applicable to entrepreneurial firms, SMEs, and organizations in emerging economies aiming to apply AI to innovate, gain competitive advantage, and create sustainable values.
References
1.K. Tamilmani, N. P. Rana, S. F. Wamba, and R. Dwivedi, “The extended Unified Theory of Acceptance and Use of Technology (UTAUT2): A systematic literature review and theory evaluation,” International Journal of Information Management, vol. 57, p. 102269, 2021.
2.G. Vial, “Understanding digital transformation: A review and a research agenda,” Journal of Strategic Information Systems, vol. 28, no. 2, pp. 118–144, 2019, doi: 10.1016/j.jsis.2019.01.003.
3.Y. K. Dwivedi, L. Hughes, E. Ismagilova, et al., “Artificial intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy,” International Journal of Information Management, vol. 57, p. 102269, 2021, doi: 10.1016/j.ijinfomgt.2020.102269.
4.P. C. Verhoef, T. Broekhuizen, Y. Bart, et al., “Digital transformation: A multidisciplinary reflection and research agenda,” Journal of Business Research, vol. 122, pp. 889–901, 2021, doi: 10.1016/j.jbusres.2019.09.022.
5.S. Raisch and S. Krakowski, “Artificial intelligence and management: The automation–augmentation paradox,” Academy of Management Review, vol. 46, no. 1, pp. 192–210, 2021, doi: 10.5465/amr.2018.0072.
6.J. Bughin, J. Seong, J. Manyika, M. Chui, and R. Joshi, Notes from the AI Frontier: Modeling the Impact of AI on the World Economy. McKinsey Global Institute, 2018.
7.S. Ransbotham, D. Kiron, P. Gerbert, and M. Reeves, “Reshaping business with artificial intelligence,” MIT Sloan Management Review, vol. 61, no. 4, pp. 1–17, 2020.
8.A. F. S. Borges, F. J. B. Laurindo, M. M. Spínola, R. F. Gonçalves, and C. A. Mattos, “The strategic use of artificial intelligence in the digital transformation of organizations,” International Journal of Information Management, vol. 57, p. 102225, 2021, doi: 10.1016/j.ijinfomgt.2020.102225.
9.D. Susanti, P. W. Handayani, and F. Azzahro, “Artificial intelligence readiness in digital transformation: A systematic literature review,” Procedia Computer Science, vol. 219, pp. 103–110, 2023, doi: 10.1016/j.procs.2023.01.276.
10.M. H. Jarrahi, “Artificial intelligence and the future of work: Human–AI symbiosis in organizational decision making,” Business Horizons, vol. 61, no. 4, pp. 577–586, 2018, doi: 10.1016/j.bushor.2018.03.007.
11.P. Mikalef, S. O. Fjørtoft, and H. Y. Torvatn, “Developing an artificial intelligence capability: A theoretical framework for business value,” Information & Management, vol. 56, no. 6, p. 103226, 2019, doi: 10.1016/j.im.2019.02.002.
12.N. Haefner, J. Wincent, V. Parida, and O. Gassmann, “Artificial intelligence and innovation management: A review, framework, and research agenda,” Technological Forecasting and Social Change, vol. 162, p. 120392, 2021, doi: 10.1016/j.techfore.2020.120392.
13.Y. K. Dwivedi, N. P. Rana, A. Jeyaraj, M. Clement, and M. D. Williams, “Re-examining the unified theory of acceptance and use of technology (UTAUT): Towards a revised theoretical model,” Information Systems Frontiers, vol. 21, pp. 719–734, 2019, doi: 10.1007/s10796-017-9774-y.
14.S. A. Abasaheb and R. Subashini, “Maneuvering of digital transformation: Role of artificial intelligence in empowering leadership – An empirical overview,” Journal of Law and Sustainable Development, vol. 11, no. 9, p. e1667, 2023.
15.A. Horlacher and T. Hess, “What does a chief digital officer do? Managerial tasks and roles of a new C-level position in the context of digital transformation,” in Proceedings of the 49th Hawaii International Conference on System Sciences, 2016, pp. 5126–5135.
16.O. T. Murire, “Artificial intelligence and its role in shaping organizational work practices and culture,” Administrative Sciences, vol. 14, no. 12, p. 316, 2024, doi: 10.3390/admsci14120316.
17.L. Babashahi, C. E. Barbosa, Y. Lima, A. Lyra, H. Salazar, M. Argôlo, M. A. d. Almeida, and J. M. d. Souza, “AI in the workplace: A systematic review of skill transformation in the industry,” Administrative Sciences, vol. 14, no. 6, p. 127, 2024, doi: 10.3390/admsci14060127.
18.A. Aakula, V. Saini, and T. Ahmad, “The impact of AI on organizational change in digital transformation,” IoT and Edge Computing Journal, vol. 4, no. 1, pp. 75–115, 2024.
19.T. Nguyen and A. Elbanna, “Understanding human–AI augmentation in the workplace: A review and a future research agenda,” Information Systems Frontiers, 2025.
20.S. Ocen, J. Elasu, S. M. Aarakit, and C. Olupot, “Artificial intelligence in higher education institutions: Review of innovations, opportunities and challenges,” Frontiers in Education, vol. 10, p. 1530247, 2025.
21.S. A. Khairullah, S. Harris, H. J. Hadi, R. A. Sandhu, N. Ahmad, and M. A. Alshara, “Implementing artificial intelligence in academic and administrative processes through responsible strategic leadership in higher education institutions,” Frontiers in Education, vol. 10, p. 1548104, 2025.
22.Z. Gering, K. Feher, V. Harmat, and R. Tamassy, “Strategic organisational responses to generative AI-driven digital transformation in leading higher education institutions,” International Journal of Organizational Analysis, vol. 33, no. 12, pp. 132–152, 2025.
23.T. Gelashvili-Luik, P. Vihma, and I. Pappel, “Navigating the AI revolution: Challenges and opportunities for integrating emerging technologies into knowledge management systems. Systematic literature review,” Frontiers in Artificial Intelligence, vol. 8, p. 1595930, 2025.
24.A. S. Pinto, A. Abreu, M. P. Cota, and J. Paiva, “A meta analysis of TOE factors driving organizational adoption of artificial intelligence across industries,” Discover Artificial Intelligence, 2025.
25.S. Gottumukkala and S. S. Prasad, “Decoding the organisational AI adoption: What do theories and frameworks reveal?,” Journal of International Commercial Law and Technology, vol. 6, pp. 744–754, 2025.
26.F. Kitsios and M. Kamariotou, “Artificial intelligence and business strategy towards digital transformation: A research agenda,” Sustainability, vol. 13, no. 4, p. 2025, 2021.
27.S. Zhang, R. C. W. Kwok, P. B. Lowry, Z. Liu, and J. Wu, “The influence of role stress on self-disclosure on social networking sites: A conservation of resources perspective,” Information & Management, vol. 56, no. 7, p. 103147, 2019.
28.P. Mikalef and M. Gupta, “Artificial intelligence capability: Conceptualization, measurement calibration, and empirical study on its impact on organizational creativity and firm performance,” Information & Management, vol. 58, no. 3, p. 103434, 2021.
29.I. M. Enholm, E. Papagiannidis, P. Mikalef, and J. Krogstie, “Artificial intelligence and business value: A literature review,” Information Systems Frontiers, vol. 24, no. 5, pp. 1709–1734, 2022.
30.H. Benbya, S. Pachidi, and S. Jarvenpaa, “Special issue editorial: Artificial intelligence in organizations: Implications for information systems research,” Journal of the Association for Information Systems, vol. 22, no. 2, p. 10, 2021.
31.S. A. Hirtranusi, B. Ranti, W. S. Nugroho, and W. Jatmiko, “A systematic literature review on organizational readiness for artificial intelligence adoption based on the TOE framework,” International Journal of Advanced Computer Science and Applications, vol. 17, no. 1, pp. 491–503, 2026.
32.X. Parent-Rocheleau and S. K. Parker, “Algorithms as work designers: How algorithmic management influences the design of jobs,” Human Resource Management Review, vol. 32, no. 3, p. 100838, 2022.
33.K. C. Kellogg, M. A. Valentine, and A. Christin, “Algorithms at work: The new contested terrain of control,” Academy of Management Annals, vol. 14, no. 1, pp. 366–410, 2020.
34.S. K. Parker and G. Grote, “Automation, algorithms, and beyond: Why work design matters more than ever in a digital world,” Applied Psychology, vol. 71, no. 4, pp. 1171–1204, 2022.
35.S. Bankins and P. Formosa, “The ethical implications of artificial intelligence (AI) for meaningful work,” Journal of Business Ethics, vol. 185, no. 4, pp. 725–740, 2023.
36.S. Chatterjee, N. P. Rana, K. Tamilmani, and A. Sharma, “The effect of AI-based CRM on organization performance and competitive advantage: An empirical analysis in the B2B context,” Industrial Marketing Management, vol. 97, pp. 205–219, 2021.
37.S. L. Wamba-Taguimdje, S. Fosso Wamba, J. R. Kala Kamdjoug, and C. E. Tchatchouang Wanko, “Influence of artificial intelligence (AI) on firm performance: The business value of AI-based transformation projects,” Business Process Management Journal, vol. 26, no. 7, pp. 1893–1924, 2020.
38.L. C. M. Miranda and T. Devezas, “On the global time evolution of the COVID-19 pandemic: Logistic modeling,” Technological Forecasting and Social Change, vol. 175, p. 121387, 2022.
39.V. Kolbjørnsrud, “Designing the intelligent organization: Six principles for human-AI collaboration,” California Management Review, vol. 66, no. 2, pp. 44–64, 2024.
40.A. Malik, P. Budhwar, C. Patel, and N. R. Srikanth, “May the bots be with you! Delivering HR cost-effectiveness and individualised employee experiences in an MNE,” in Artificial Intelligence and International HRM, Routledge, 2023, pp. 83–113.
41.E. Glikson and A. W. Woolley, “Human trust in artificial intelligence: Review of empirical research,” Academy of Management Annals, vol. 14, no. 2, pp. 627–660, 2020.
42.A. Kaplan and M. Haenlein, “Siri, Siri, in my hand: Who’s the fairest in the land? On the interpretations, illustrations, and implications of artificial intelligence,” Business Horizons, vol. 62, no. 1, pp. 15–25, 2019.
43.A. Di Vaio, R. Palladino, R. Hassan, and O. Escobar, “Artificial intelligence and business models in the sustainable development goals perspective: A systematic literature review,” Journal of Business Research, vol. 121, pp. 283–314, 2020.
44.E. Prem, “Artificial intelligence for innovation in Austria,” Technology Innovation Management Review, vol. 9, no. 12, 2019.
45.M. Minkkinen, J. Laine, and M. Mäntymäki, “Continuous auditing of artificial intelligence: A conceptualization and assessment of tools and frameworks,” Digital Society, vol. 1, no. 3, p. 21, 2022.
46.M. Schmitt, “Automated machine learning: AI-driven decision making in business analytics,” Intelligent Systems with Applications, vol. 18, p. 200188, 2023.
47.M. Mäntymäki, M. Minkkinen, T. Birkstedt, and M. Viljanen, “Defining organizational AI governance,” AI and Ethics, vol. 2, no. 4, pp. 603–609, 2022.
48.A. Batool, D. Zowghi, and M. Bano, “AI governance: A systematic literature review,” AI and Ethics, vol. 5, no. 3, pp. 3265–3279, 2025.
49.B. Rakova, J. Yang, H. Cramer, and R. Chowdhury, “Where responsible AI meets reality: Practitioner perspectives on enablers for shifting organizational practices,” Proceedings of the ACM on Human-Computer Interaction, vol. 5, no. CSCW1, pp. 1–23, 2021.
50.M. A. Madaio, L. Stark, J. Wortman Vaughan, and H. Wallach, “Co-designing checklists to understand organizational challenges and opportunities around fairness in AI,” in Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, 2020, pp. 1–14.
51.M. Madanchian and H. Taherdoost, “Ethical theories, governance models, and strategic frameworks for responsible AI adoption and organizational success,” Frontiers in Artificial Intelligence, vol. 8, p. 1619029, 2025.
52.J. Morley, L. Floridi, L. Kinsey, and A. Elhalal, “From what to how: An initial review of publicly available AI ethics tools, methods and research to translate principles into practices,” in Ethics, Governance, and Policies in Artificial Intelligence, Cham, Switzerland: Springer International Publishing, 2021, pp. 153–183.
53.A. Nadeem, O. Marjanovic, and B. Abedin, “Gender bias in AI-based decision-making systems: A systematic literature review,” Australasian Journal of Information Systems, vol. 26, 2022.
54.A. Hanelt, R. Bohnsack, D. Marz, and C. Antunes Marante, “A systematic review of the literature on digital transformation: Insights and implications for strategy and organizational change,” Journal of Management Studies, vol. 58, no. 5, pp. 1159–1197, 2021.
55.A. Tursunbayeva and H. C. B. Gal, “Adoption of artificial intelligence: A TOP framework-based checklist for digital leaders,” Business Horizons, vol. 67, no. 4, pp. 357–368, 2024.
56.E. Papagiannidis, P. Mikalef, and K. Conboy, “Responsible artificial intelligence governance: A review and research framework,” Journal of Strategic Information Systems, vol. 34, no. 2, p. 101885, 2025.
57.N. A. Perifanis and F. Kitsios, “Investigating the influence of artificial intelligence on business value in the digital era of strategy: A literature review,” Information, vol. 14, no. 2, p. 85, 2023.
