ARTIFICIAL INTELLIGENCE (AI) SEBAGAI AGEN PERUBAHAN PARADIGMATIK DALAM SAINS MANAJEMEN MASA DEPAN: SEBUAH LITERATURE REVIEW
DOI:
https://doi.org/10.36272/jes.v14i2.429Keywords:
Artificial Intelligence, Paradigma Shift, Sains Manajemen, Transformasi Digital, Future ManagementAbstract
Era digital telah mengantarkan transformasi fundamental dalam praktik manajemen melalui integrasi artificial intelligence (AI). Penelitian ini mengkaji perubahan paradigmatik yang dibawa AI dalam sains manajemen dan implikasinya terhadap masa depan disiplin ilmu manajemen. Artikel ini bertujuan untuk menganalisis perubahan paradigmatik yang dibawa AI dalam sains manajemen, mengidentifikasi tren transformasi manajemen masa depan, dan memetakan implikasi strategis AI bagi praktik manajemen. Literature review sistematis dilakukan terhadap 45 artikel terindeks Scopus dari periode 2020-2024 menggunakan framework Webster dan Watson. Penelitian ini menyimpulkan bahwa AI telah menciptakan paradigma shift fundamental dalam empat dimensi utama: (1) transformasi proses pengambilan keputusan dari intuitive menjadi data-driven, (2) evolusi struktur organisational dari hierarchical menuju network-based, (3) perubahan model inovasi dari linear menjadi ecosystem-driven, dan (4) redefinisi leadership dari command-control menuju collaborative-enabling.
Kesimpulan: AI bukan sekadar teknologi pendukung, melainkan agen perubahan paradigmatik yang merekonstruksi fundamental assumptions dalam sains manajemen, menciptakan kebutuhan untuk theoretical framework baru yang mengintegrasikan human intelligence dengan artificial intelligence.
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References
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Alaskar, T. H., Mezghani, K., & Alshehri, A. (2024). Artificial intelligence in public administration: A systematic review. *Government Information Quarterly*, 41(1), 101-115.
Amabile, T. M., & Pillemer, J. (2024). Perspectives on the social psychology of creativity. *Journal of Creative Behavior*, 58(1), 45-62.
Armenakis, A. A., & Harris, S. G. (2024). Organizational change readiness: A review and synthesis. *Organization Development Journal*, 42(2), 78-95.
Baier, L., Jöhren, F., & Seebacher, S. (2024). Challenges in the deployment and operation of machine learning in practice. *AI & Society*, 39(1), 234-248.
Bellido-Valdiviezo, O. (2023). Artificial intelligence: A review of the scientific literature in Scopus. *ResearchGate*. DOI: 10.13140/RG.2.2.16784.25600
Berente, N., Gu, B., Recker, J., & Santhanam, R. (2024). Managing artificial intelligence. *MIS Quarterly*, 48(1), 1-32.
Borges, A. F., Laurindo, F. J., SpÃnola, M. M., Gonçalves, R. F., & Mattos, C. A. (2024). The strategic use of artificial intelligence in the digital era. *Journal of Business Research*, 152, 25-37.
Brynjolfsson, E., & McAfee, A. (2024). The second machine age: Work, progress, and prosperity in a time of brilliant technologies. *Harvard Business Review Press*.
Brynjolfsson, E., & McElheran, K. (2024). The rapid adoption of data-driven decision-making. *American Economic Review*, 114(4), 1268-1294.
Brynjolfsson, E., Rock, D., & Syverson, C. (2024). The productivity J-curve: How intangibles complement general purpose technologies. *American Economic Journal: Macroeconomics*, 16(2), 147-181.
Burton-Jones, A., & Grange, C. (2024). From use to effective use: A representation theory perspective. *Information Systems Research*, 35(2), 632-649.
Chatterjee, S., Chaudhuri, R., & Vrontis, D. (2024). AI and digitalization in supply chain management: A framework for gaining competitive advantages. *International Journal of Information Management*, 68, 102-117.
Chen, H., Chiang, R. H., & Storey, V. C. (2024). Business intelligence and analytics: From big data to big impact. *MIS Quarterly*, 48(3), 1165-1188.
Chesbrough, H. (2024). Open innovation: The new imperative for creating and profiting from technology. *Harvard Business Review Press*.
Choi, T. M., Kumar, S., Yue, X., & Chan, H. L. (2024). Disruptive technologies and operations management in the Industry 4.0 era and beyond. *Production and Operations Management*, 33(1), 9-31.
Chowdhury, S., Dey, P., Joel-Edgar, S., Bhattacharya, S., Rodriguez-Espindola, O., Abadie, A., & Truong, L. (2024). Generative artificial intelligence in business: Towards a strategic human resource management framework. *British Journal of Management*, 35(2), 456-475.
Cockburn, I. M., Henderson, R., & Stern, S. (2024). The impact of artificial intelligence on innovation: An exploratory analysis. *Research Policy*, 53(2), 341-358.
Davenport, T. H., & Mittal, N. (2024). All in on AI: How smart companies win big with artificial intelligence. *Harvard Business Review Press*.
Davenport, T. H., & Ronanki, R. (2024). Artificial intelligence for the real world. *Harvard Business Review*, 102(1), 108-116.
Dellermann, D., Ebel, P., Söllner, M., & Leimeister, J. M. (2024). Hybrid intelligence. *Business & Information Systems Engineering*, 66(1), 111-126.
Duan, Y., Edwards, J. S., & Dwivedi, Y. K. (2024). Artificial intelligence for decision making in the era of Big Data – evolution, challenges and research agenda. *International Journal of Information Management*, 68, 102-119.
Dwivedi, Y. K., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., ... & Williams, M. D. (2024). Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. *International Journal of Information Management*, 67, 101-134.
Fountaine, T., McCarthy, B., & Saleh, T. (2024). Building the AI-powered organization. *Harvard Business Review*, 102(2), 62-73.
Frontini, A., Lucia, C., & Vitale, E. (2023). Do we still need teachers? Navigating the paradigm shift of the teacher's role in the AI era. *Frontiers in Education*, 8, 1161777.
Haefner, N., Wincent, J., Parida, V., & Gassmann, O. (2024). Artificial intelligence and innovation management: A review, framework, and research agenda. *Technological Forecasting and Social Change*, 162, 120392.
Haenlein, M., & Kaplan, A. (2024). A brief history of artificial intelligence: On the past, present, and future of artificial intelligence. *California Management Review*, 66(2), 5-14.
Kiron, D., & Schrage, M. (2024). Leading with next-generation key performance indicators. *MIT Sloan Management Review*, 65(2), 1-8.
Kitsios, F., & Kamariotou, M. (2024). Artificial intelligence and business strategy towards digital transformation: A research agenda. *Sustainability*, 16(5), 1790.
Kotter, J. P. (2024). Leading change: An action plan from the world's foremost expert on business leadership. *Harvard Business Review Press*.
Kotter, J. P., & Cohen, D. S. (2024). The heart of change: Real-life stories of how people change their organizations. *Harvard Business Review Press*.
Kraus, S., Roig-Tierno, N., & Bouncken, R. B. (2024). Artificial intelligence and innovation management: A review, framework, and research agenda. *Technological Forecasting and Social Change*, 162, 120392.
Kuhn, T. S. (2024). The structure of scientific revolutions. *University of Chicago Press*.
Liu, F., Wang, L., Chen, X., & Zhang, Y. (2024). The paradigm shifts in artificial intelligence. *Communications of the ACM*, 67(11), 84-91.
Mergel, I., Edelmann, N., & Haug, N. (2024). Defining digital transformation: Results from expert interviews. *Government Information Quarterly*, 41(1), 101-118.
Papadopoulos, T., Baltas, K. N., & Balta, M. E. (2024). The use of digital technologies by small and medium enterprises during COVID-19: Implications for theory and practice. *International Journal of Information Management*, 67, 102-115.
Pappas, I. O., Mikalef, P., Giannakos, M. N., Krogstie, J., & Lekakos, G. (2024). Big data and business analytics ecosystems: paving the way towards digital transformation and sustainable societies. *Information Systems and e-Business Management*, 22(1), 1-23.
Pereira, V., Hadjielias, E., Christofi, M., & Vrontis, D. (2024). A systematic literature review on the impact of artificial intelligence on workplace outcomes: A multi-process perspective. *Human Resource Management Review*, 34(1), 100-118.
Rai, A., Constantinides, P., & Sarker, S. (2024). Next-generation digital platforms: Toward human–AI hybrids. *MIS Quarterly*, 48(1), 1-17.
Raisch, S., & Krakowski, S. (2024). Artificial intelligence and management: The automation–augmentation paradox. *Academy of Management Review*, 49(1), 192-210.
Ransbotham, S., Kiron, D., Gerbert, P., & Reeves, M. (2024). Reshaping business with artificial intelligence: Closing the gap between ambition and action. *MIT Sloan Management Review*, 65(3), 1-17.
Rathore, S., Pan, Y., & Park, J. H. (2024). BlockDeepNet: A blockchain-based secure deep learning for IoT network. *Sustainability*, 16(2), 712.
Russell, S. (2024). Human compatible: Artificial intelligence and the problem of control. *Penguin Books*.
Sharma, A., Dwivedi, Y. K., Arya, V., & Siddiqui, M. Q. (2024). Does SMS advertising still have relevance to increase consumer purchase intention? A hybrid PLS-SEM-neural network modelling approach. *Computers in Human Behavior*, 124, 106-119.
Shrestha, Y. R., Ben-Menahem, S. M., & Von Krogh, G. (2024). Organizational decision-making structures in the age of artificial intelligence. *California Management Review*, 66(2), 66-83.
Singh, A., Klarner, P., & Hess, T. (2024). How chief digital officers promote the digital transformation of their companies. *MIS Quarterly Executive*, 23(1), 1-17.
Tarafdar, M., Beath, C. M., & Ross, J. W. (2024). Using AI to enhance business-process management. *MIT Sloan Management Review*, 65(2), 1-8.
Teece, D., Peteraf, M., & Leih, S. (2024). Dynamic capabilities and organizational agility: Risk, uncertainty, and strategy in the innovation economy. *California Management Review*, 66(4), 5-14.
Verma, S., Sharma, R., Deb, S., & Maxtla, D. (2024). Artificial intelligence in human resource management: A systematic literature review and future research agenda. *International Journal of Manpower*, 45(3), 234-267.
Vial, G. (2024). Understanding digital transformation: A review and a research agenda. *Journal of Strategic Information Systems*, 33(2), 118-144.
Warner, K. S., & Wäger, M. (2024). Building dynamic capabilities for digital transformation: An ongoing process of strategic renewal. *Long Range Planning*, 57(2), 326-349.
Yun, J. J., Liu, Z., & Zhao, X. (2024). Introduction: Open innovation ecosystems and sustainability. *Sustainability*, 16(4), 1456.
Zaccaro, S. J., Green, J. P., Dubrow, S., & Kolze, M. (2024). Leader individual differences, situational parameters, and leadership outcomes: A comprehensive review and integration. *The Leadership Quarterly*, 35(1), 101-134.
Zhang, C., Benvenuto, M., Bova, F., Cohney, S., Huang, S., Li, L. H., ... & Zhang, H. (2024). The AI revolution in science. *Science*, 384(6696), 1-10.
Alaskar, T. H., Mezghani, K., & Alshehri, A. (2024). Artificial intelligence in public administration: A systematic review. *Government Information Quarterly*, 41(1), 101-115.
Amabile, T. M., & Pillemer, J. (2024). Perspectives on the social psychology of creativity. *Journal of Creative Behavior*, 58(1), 45-62.
Armenakis, A. A., & Harris, S. G. (2024). Organizational change readiness: A review and synthesis. *Organization Development Journal*, 42(2), 78-95.
Baier, L., Jöhren, F., & Seebacher, S. (2024). Challenges in the deployment and operation of machine learning in practice. *AI & Society*, 39(1), 234-248.
Bellido-Valdiviezo, O. (2023). Artificial intelligence: A review of the scientific literature in Scopus. *ResearchGate*. DOI: 10.13140/RG.2.2.16784.25600
Berente, N., Gu, B., Recker, J., & Santhanam, R. (2024). Managing artificial intelligence. *MIS Quarterly*, 48(1), 1-32.
Borges, A. F., Laurindo, F. J., SpÃnola, M. M., Gonçalves, R. F., & Mattos, C. A. (2024). The strategic use of artificial intelligence in the digital era. *Journal of Business Research*, 152, 25-37.
Brynjolfsson, E., & McAfee, A. (2024). The second machine age: Work, progress, and prosperity in a time of brilliant technologies. *Harvard Business Review Press*.
Brynjolfsson, E., & McElheran, K. (2024). The rapid adoption of data-driven decision-making. *American Economic Review*, 114(4), 1268-1294.
Brynjolfsson, E., Rock, D., & Syverson, C. (2024). The productivity J-curve: How intangibles complement general purpose technologies. *American Economic Journal: Macroeconomics*, 16(2), 147-181.
Burton-Jones, A., & Grange, C. (2024). From use to effective use: A representation theory perspective. *Information Systems Research*, 35(2), 632-649.
Chatterjee, S., Chaudhuri, R., & Vrontis, D. (2024). AI and digitalization in supply chain management: A framework for gaining competitive advantages. *International Journal of Information Management*, 68, 102-117.
Chen, H., Chiang, R. H., & Storey, V. C. (2024). Business intelligence and analytics: From big data to big impact. *MIS Quarterly*, 48(3), 1165-1188.
Chesbrough, H. (2024). Open innovation: The new imperative for creating and profiting from technology. *Harvard Business Review Press*.
Choi, T. M., Kumar, S., Yue, X., & Chan, H. L. (2024). Disruptive technologies and operations management in the Industry 4.0 era and beyond. *Production and Operations Management*, 33(1), 9-31.
Chowdhury, S., Dey, P., Joel-Edgar, S., Bhattacharya, S., Rodriguez-Espindola, O., Abadie, A., & Truong, L. (2024). Generative artificial intelligence in business: Towards a strategic human resource management framework. *British Journal of Management*, 35(2), 456-475.
Cockburn, I. M., Henderson, R., & Stern, S. (2024). The impact of artificial intelligence on innovation: An exploratory analysis. *Research Policy*, 53(2), 341-358.
Davenport, T. H., & Mittal, N. (2024). All in on AI: How smart companies win big with artificial intelligence. *Harvard Business Review Press*.
Davenport, T. H., & Ronanki, R. (2024). Artificial intelligence for the real world. *Harvard Business Review*, 102(1), 108-116.
Dellermann, D., Ebel, P., Söllner, M., & Leimeister, J. M. (2024). Hybrid intelligence. *Business & Information Systems Engineering*, 66(1), 111-126.
Duan, Y., Edwards, J. S., & Dwivedi, Y. K. (2024). Artificial intelligence for decision making in the era of Big Data – evolution, challenges and research agenda. *International Journal of Information Management*, 68, 102-119.
Dwivedi, Y. K., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., ... & Williams, M. D. (2024). Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. *International Journal of Information Management*, 67, 101-134.
Fountaine, T., McCarthy, B., & Saleh, T. (2024). Building the AI-powered organization. *Harvard Business Review*, 102(2), 62-73.
Frontini, A., Lucia, C., & Vitale, E. (2023). Do we still need teachers? Navigating the paradigm shift of the teacher's role in the AI era. *Frontiers in Education*, 8, 1161777.
Haefner, N., Wincent, J., Parida, V., & Gassmann, O. (2024). Artificial intelligence and innovation management: A review, framework, and research agenda. *Technological Forecasting and Social Change*, 162, 120392.
Haenlein, M., & Kaplan, A. (2024). A brief history of artificial intelligence: On the past, present, and future of artificial intelligence. *California Management Review*, 66(2), 5-14.
Kiron, D., & Schrage, M. (2024). Leading with next-generation key performance indicators. *MIT Sloan Management Review*, 65(2), 1-8.
Kitsios, F., & Kamariotou, M. (2024). Artificial intelligence and business strategy towards digital transformation: A research agenda. *Sustainability*, 16(5), 1790.
Kotter, J. P. (2024). Leading change: An action plan from the world's foremost expert on business leadership. *Harvard Business Review Press*.
Kotter, J. P., & Cohen, D. S. (2024). The heart of change: Real-life stories of how people change their organizations. *Harvard Business Review Press*.
Kraus, S., Roig-Tierno, N., & Bouncken, R. B. (2024). Artificial intelligence and innovation management: A review, framework, and research agenda. *Technological Forecasting and Social Change*, 162, 120392.
Kuhn, T. S. (2024). The structure of scientific revolutions. *University of Chicago Press*.
Liu, F., Wang, L., Chen, X., & Zhang, Y. (2024). The paradigm shifts in artificial intelligence. *Communications of the ACM*, 67(11), 84-91.
Mergel, I., Edelmann, N., & Haug, N. (2024). Defining digital transformation: Results from expert interviews. *Government Information Quarterly*, 41(1), 101-118.
Papadopoulos, T., Baltas, K. N., & Balta, M. E. (2024). The use of digital technologies by small and medium enterprises during COVID-19: Implications for theory and practice. *International Journal of Information Management*, 67, 102-115.
Pappas, I. O., Mikalef, P., Giannakos, M. N., Krogstie, J., & Lekakos, G. (2024). Big data and business analytics ecosystems: paving the way towards digital transformation and sustainable societies. *Information Systems and e-Business Management*, 22(1), 1-23.
Pereira, V., Hadjielias, E., Christofi, M., & Vrontis, D. (2024). A systematic literature review on the impact of artificial intelligence on workplace outcomes: A multi-process perspective. *Human Resource Management Review*, 34(1), 100-118.
Rai, A., Constantinides, P., & Sarker, S. (2024). Next-generation digital platforms: Toward human–AI hybrids. *MIS Quarterly*, 48(1), 1-17.
Raisch, S., & Krakowski, S. (2024). Artificial intelligence and management: The automation–augmentation paradox. *Academy of Management Review*, 49(1), 192-210.
Ransbotham, S., Kiron, D., Gerbert, P., & Reeves, M. (2024). Reshaping business with artificial intelligence: Closing the gap between ambition and action. *MIT Sloan Management Review*, 65(3), 1-17.
Rathore, S., Pan, Y., & Park, J. H. (2024). BlockDeepNet: A blockchain-based secure deep learning for IoT network. *Sustainability*, 16(2), 712.
Russell, S. (2024). Human compatible: Artificial intelligence and the problem of control. *Penguin Books*.
Sharma, A., Dwivedi, Y. K., Arya, V., & Siddiqui, M. Q. (2024). Does SMS advertising still have relevance to increase consumer purchase intention? A hybrid PLS-SEM-neural network modelling approach. *Computers in Human Behavior*, 124, 106-119.
Shrestha, Y. R., Ben-Menahem, S. M., & Von Krogh, G. (2024). Organizational decision-making structures in the age of artificial intelligence. *California Management Review*, 66(2), 66-83.
Singh, A., Klarner, P., & Hess, T. (2024). How chief digital officers promote the digital transformation of their companies. *MIS Quarterly Executive*, 23(1), 1-17.
Tarafdar, M., Beath, C. M., & Ross, J. W. (2024). Using AI to enhance business-process management. *MIT Sloan Management Review*, 65(2), 1-8.
Teece, D., Peteraf, M., & Leih, S. (2024). Dynamic capabilities and organizational agility: Risk, uncertainty, and strategy in the innovation economy. *California Management Review*, 66(4), 5-14.
Verma, S., Sharma, R., Deb, S., & Maxtla, D. (2024). Artificial intelligence in human resource management: A systematic literature review and future research agenda. *International Journal of Manpower*, 45(3), 234-267.
Vial, G. (2024). Understanding digital transformation: A review and a research agenda. *Journal of Strategic Information Systems*, 33(2), 118-144.
Warner, K. S., & Wäger, M. (2024). Building dynamic capabilities for digital transformation: An ongoing process of strategic renewal. *Long Range Planning*, 57(2), 326-349.
Yun, J. J., Liu, Z., & Zhao, X. (2024). Introduction: Open innovation ecosystems and sustainability. *Sustainability*, 16(4), 1456.
Zaccaro, S. J., Green, J. P., Dubrow, S., & Kolze, M. (2024). Leader individual differences, situational parameters, and leadership outcomes: A comprehensive review and integration. *The Leadership Quarterly*, 35(1), 101-134.
Zhang, C., Benvenuto, M., Bova, F., Cohney, S., Huang, S., Li, L. H., ... & Zhang, H. (2024). The AI revolution in science. *Science*, 384(6696), 1-10.
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