DAMPAK ADOPSI KECERDASAN BUATAN TERHADAP INOVASI MODEL BISNIS PERUSAHAAN DIGITAL: PERAN KAPABILITAS DINAMIS
DOI:
https://doi.org/10.58268/eb.v5i2.337Kata Kunci:
artificial intelligence; AI capability; business model innovation; dynamic capabilities; digital companies, : Artificial Intelligence; AI Capability; Business Model Innovation; Dynamic Capabilities; Digital CompaniesAbstrak
Adopsi kecerdasan buatan atau artificial intelligence (AI) mengubah cara perusahaan digital menciptakan, menyampaikan, dan menangkap nilai, tetapi dampaknya terhadap inovasi model bisnis tidak terjadi secara otomatis maupun seragam. Penelitian ini bertujuan menjelaskan mekanisme adopsi AI dalam mendorong inovasi model bisnis perusahaan digital. Penelitian menggunakan kajian literatur konseptual dengan desain sintesis teori terhadap 23 artikel jurnal bereputasi terbitan 2017–2024 mengenai AI capability, inovasi model bisnis, transformasi digital, dan dynamic capabilities. Hasil sintesis menunjukkan bahwa AI memengaruhi keempat dimensi model bisnis: mempersonalisasi value proposition, memadukan otomatisasi dan augmentasi dalam value creation, mengotomatisasi serta memperluas skala value delivery, dan membuka mekanisme pendapatan serta efisiensi biaya berbasis data pada value capture. Dampak tersebut muncul ketika adopsi AI diubah menjadi AI capability dan diorkestrasi melalui kemampuan sensing, seizing, dan reconfiguring, sedangkan tata kelola data yang lemah, kesenjangan keterampilan, dan hambatan organisasi pada level mikro dapat menghambatnya. Penelitian ini menghasilkan kerangka konseptual integratif dan lima proposisi penelitian. Perusahaan digital disarankan menilai investasi AI berdasarkan kontribusinya terhadap perubahan model bisnis serta membangun tata kelola data, talenta, dan koordinasi lintas fungsi secara bersamaan.
Referensi
Burström, T., Parida, V., Lahti, T., & Wincent, J. (2021). AI-enabled business-model innovation and transformation in industrial ecosystems: A framework, model and outline for further research. Journal of Business Research, 127, 85–95. https://doi.org/10.1016/j.jbusres.2021.01.016
Chen, D., Esperança, J. P., & Wang, S. (2022). The impact of artificial intelligence on firm performance: An application of the resource-based view to e-commerce firms. Frontiers in Psychology, 13, 884830. https://doi.org/10.3389/fpsyg.2022.884830
Enholm, I. M., Papagiannidis, E., Mikalef, P., & Krogstie, J. (2022). Artificial intelligence and business value: A literature review. Information Systems Frontiers, 24(5), 1709–1734. https://doi.org/10.1007/s10796-021-10186-w
Fang, T. M., Ahmad, N. H., Halim, H. A., Iqbal, Q., & Ramayah, T. (2024). Pathway towards SME competitiveness: Digital capability and digital business model innovation. Technology in Society, 79, 102728. https://doi.org/10.1016/j.techsoc.2024.102728
Foss, N. J., & Saebi, T. (2017). Fifteen years of research on business model innovation: How far have we come, and where should we go? Journal of Management, 43(1), 200–227. https://doi.org/10.1177/0149206316675927
Haefner, N., Wincent, J., Parida, V., & Gassmann, O. (2021). Artificial intelligence and innovation management: A review, framework, and research agenda. Technological Forecasting and Social Change, 162, 120392. https://doi.org/10.1016/j.techfore.2020.120392
Jaakkola, E. (2020). Designing conceptual articles: Four approaches. AMS Review, 10(1), 18–26. https://doi.org/10.1007/s13162-020-00161-0
Jacobides, M. G., Cennamo, C., & Gawer, A. (2018). Towards a theory of ecosystems. Strategic Management Journal, 39(8), 2255–2276. https://doi.org/10.1002/smj.2904
Jorzik, P., Klein, S. P., Kanbach, D. K., & Kraus, S. (2024). AI-driven business model innovation: A systematic review and research agenda. Journal of Business Research, 182, 114764. https://doi.org/10.1016/j.jbusres.2024.114764
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
Liu, L., Cui, L., Han, Q., & Zhang, C. (2024). The impact of digital capabilities and dynamic capabilities on business model innovation: The moderating effect of organizational inertia. Humanities and Social Sciences Communications, 11, 420. https://doi.org/10.1057/s41599-024-02910-z
Madanaguli, A., Sjödin, D., Parida, V., & Mikalef, P. (2024). Artificial intelligence capabilities for circular business models: Research synthesis and future agenda. Technological Forecasting and Social Change, 200, 123189. https://doi.org/10.1016/j.techfore.2023.123189
Mariani, M. M., Machado, I., Magrelli, V., & Dwivedi, Y. K. (2023). Artificial intelligence in innovation research: A systematic review, conceptual framework, and future research directions. Technovation, 122, 102623. https://doi.org/10.1016/j.technovation.2022.102623
Mikalef, P., & Gupta, M. (2021). Artificial intelligence capability: Conceptualization, measurement calibration, and empirical study on its impact on organizational creativity and firm performance. Information & Management, 58(3), 103434. https://doi.org/10.1016/j.im.2021.103434
Raisch, S., & Krakowski, S. (2021). Artificial intelligence and management: The automation–augmentation paradox. Academy of Management Review, 46(1), 192–210. https://doi.org/10.5465/amr.2018.0072
Shrestha, Y. R., Ben-Menahem, S. M., & von Krogh, G. (2019). Organizational decision-making structures in the age of artificial intelligence. California Management Review, 61(4), 66–83. https://doi.org/10.1177/0008125619862257
Sjödin, D., Parida, V., & Kohtamäki, M. (2023). Artificial intelligence enabling circular business model innovation in digital servitization: Conceptualizing dynamic capabilities, AI capacities, business models and effects. Technological Forecasting and Social Change, 197, 122903. https://doi.org/10.1016/j.techfore.2023.122903
Sjödin, D., Parida, V., Palmié, M., & Wincent, J. (2021). How AI capabilities enable business model innovation: Scaling AI through co-evolutionary processes and feedback loops. Journal of Business Research, 134, 574–587. https://doi.org/10.1016/j.jbusres.2021.05.009
Snyder, H. (2019). Literature review as a research methodology: An overview and guidelines. Journal of Business Research, 104, 333–339. https://doi.org/10.1016/j.jbusres.2019.07.039
Teece, D. J. (2018). Business models and dynamic capabilities. Long Range Planning, 51(1), 40–49. https://doi.org/10.1016/j.lrp.2017.06.007
Teece, D. J., & Linden, G. (2017). Business models, value capture, and the digital enterprise. Journal of Organization Design, 6, 8. https://doi.org/10.1186/s41469-017-0018-x
Verhoef, P. C., Broekhuizen, T., Bart, Y., Bhattacharya, A., Dong, J. Q., Fabian, N., & Haenlein, M. (2021). Digital transformation: A multidisciplinary reflection and research agenda. Journal of Business Research, 122, 889–901. https://doi.org/10.1016/j.jbusres.2019.09.022
Vial, G. (2019). Understanding digital transformation: A review and a research agenda. The Journal of Strategic Information Systems, 28(2), 118–144. https://doi.org/10.1016/j.jsis.2019.01.003
Warner, K. S. R., & Wäger, M. (2019). Building dynamic capabilities for digital transformation: An ongoing process of strategic renewal. Long Range Planning, 52(3), 326–349. https://doi.org/10.1016/j.lrp.2018.12.001
Witschel, D., Müller, J. M., & Voigt, K.-I. (2023). What takes the wind out of their sails? A micro-foundational perspective of challenges for building dynamic capabilities towards digital business model innovation. Schmalenbach Journal of Business Research, 75, 345–388. https://doi.org/10.1007/s41471-023-00163-1
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