{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,5]],"date-time":"2026-10-05T12:51:48Z","timestamp":1791204708141,"version":"4.2.0"},"reference-count":43,"publisher":"International Journal of Innovative Science and Research Technology","issue":"9","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["International Journal of Innovative Science and Research Technology (IJISRT)"],"abstract":"<jats:p>This study examines responsible AI adoption in small and medium-sized enterprises through a system dynamics approach, focusing on how ethical readiness and risk governance shape sustainable business performance.The research uses a sequential mixed-method design based on primary data. It combines SME surveys, semi-structured interviews, expert validation, and system dynamics simulation. The model connects ethical readiness, risk governance capability, responsible AI adoption quality, AI risk exposure, and sustainable business performance. The study shows that AI adoption alone does not guarantee long-term business value. SMEs achieve stronger performance when AI tools are adopted with human oversight, documentation, vendor checks, employee training, and continuous monitoring. Rapid adoption with weak governance may create early efficiency gains, but accumulated risks such as privacy leakage, misinformation, bias, vendor lock-in, employee resistance, and trust loss can reduce performance over time. The research highlights that responsible AI should be treated as a managerial capability rather than a simple technology purchase.<\/jats:p>","DOI":"10.38124\/ijisrt\/26sep1326","type":"journal-article","created":{"date-parts":[[2026,10,5]],"date-time":"2026-10-05T12:01:15Z","timestamp":1791201675000},"page":"2869","source":"Crossref","is-referenced-by-count":0,"title":["Responsible AI Adoption in SMEs: A System Dynamics Approach to Risk Governance, Ethical Readiness and Sustainable Business Performance"],"prefix":"10.38124","volume":"11","author":[{"given":"Osman Angeles","family":"Conteh","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alimamy","family":"Kamara","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"23876","published-online":{"date-parts":[[2026,10,5]]},"reference":[{"key":"ref0","unstructured":"[1.]\tAyinaddis, S. G. (2025). Artificial intelligence adoption dynamics and knowledge in SMEs and large firms: A systematic review and bibliometric analysis. Journal of Innovation & Knowledge, 10, 100682. https:\/\/doi.org\/10.1016\/j.jik.2025.100682"},{"key":"ref1","unstructured":"[2.]\tBadghish, S., Soomro, Y. A., Ghumro, I. A., & Jamali, R. H. (2024). Artificial intelligence adoption by SMEs to achieve sustainable business performance: Application of technology-organization-environment framework. Sustainability, 16(5), 1864. https:\/\/doi.org\/10.3390\/su16051864"},{"key":"ref2","unstructured":"[3.]\tBansal, P., & DesJardine, M. R. (2014). Business sustainability: It is about time. Strategic Organization, 12(1), 70-78."},{"key":"ref3","unstructured":"[4.]\tBarney, J. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1), 99-120."},{"key":"ref4","unstructured":"[5.]\tBorges, A. F. S., Laurindo, F. J. B., Sp\u00ednola, M. M., Gon\u00e7alves, R. F., & Mattos, C. A. (2021). The strategic use of artificial intelligence in the digital era: Systematic literature review and future research directions. International Journal of Information Management, 57, 102225."},{"key":"ref5","unstructured":"[6.]\tBraun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77-101."},{"key":"ref6","unstructured":"[7.]\tDavenport, T. H., & Ronanki, R. (2018). Artificial intelligence for the real world. Harvard Business Review, 96(1), 108-116."},{"key":"ref7","unstructured":"[8.]\tDeLone, W. H., & McLean, E. R. (2003). The DeLone and McLean model of information systems success: A ten-year update. Journal of Management Information Systems, 19(4), 9-30."},{"key":"ref8","unstructured":"[9.]\tDrydakis, N. (2022). Artificial intelligence and reduced SMEs' business risks: A dynamic capabilities analysis during the COVID-19 pandemic. Information Systems Frontiers, 24, 1223-1247. https:\/\/doi.org\/10.1007\/s10796-022-10249-6"},{"key":"ref9","unstructured":"[10.]\tDwivedi, Y. K., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., Duan, Y., Dwivedi, R., Edwards, J., Eirug, A., Galanos, V., Ilavarasan, P. V., Janssen, M., Jones, P., Kar, A. K., Kizgin, H., Kronemann, B., Lal, B., Lucini, B., ... Williams, M. D. (2021). Artificial intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. International Journal of Information Management, 57, 101994."},{"key":"ref10","unstructured":"[11.]\tElkington, J. (1997). Cannibals with forks: The triple bottom line of 21st century business. Capstone."},{"key":"ref11","unstructured":"[12.]\tEnholm, I. M., Papagiannidis, E., Mikalef, P., & Krogstie, J. (2022). Artificial intelligence and business value: A literature review. Information Systems Frontiers, 24, 1709-1734."},{"key":"ref12","unstructured":"[13.]\tEuropean Parliament and Council of the European Union. (2024). Regulation (EU) 2024\/1689 laying down harmonised rules on artificial intelligence (Artificial Intelligence Act). Official Journal of the European Union."},{"key":"ref13","unstructured":"[14.]\tFloridi, L., Cowls, J., Beltrametti, M., Chatila, R., Chazerand, P., Dignum, V., Luetge, C., Madelin, R., Pagallo, U., Rossi, F., Schafer, B., Valcke, P., & Vayena, E. (2018). AI4People - An ethical framework for a good AI society: Opportunities, risks, principles, and recommendations. Minds and Machines, 28, 689-707."},{"key":"ref14","unstructured":"[15.]\tForrester, J. W. (1961). Industrial dynamics. MIT Press."},{"key":"ref15","unstructured":"[16.]\tFreeman, R. E. (1984). Strategic management: A stakeholder approach. Pitman."},{"key":"ref16","unstructured":"[17.]\tHair, J. F., Hult, G. T. M., Ringle, C. M., Sarstedt, M., Danks, N. P., & Ray, S. (2021). Partial least squares structural equation modeling (PLS-SEM) using R. Springer."},{"key":"ref17","unstructured":"[18.]\tHenseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43, 115-135."},{"key":"ref18","unstructured":"[19.]\tISO\/IEC. (2023). ISO\/IEC 42001:2023 Information technology - Artificial intelligence - Management system. International Organization for Standardization."},{"key":"ref19","unstructured":"[20.]\tJ\u00f6hnk, J., Wei\u00dfert, M., & Wyrtki, K. (2021). Ready or not, AI comes - An interview study of organizational AI readiness factors. Business & Information Systems Engineering, 63(1), 5-20. https:\/\/doi.org\/10.1007\/s12599-020-00676-7"},{"key":"ref20","unstructured":"[21.]\tJobin, A., Ienca, M., & Vayena, E. (2019). The global landscape of AI ethics guidelines. Nature Machine Intelligence, 1, 389-399."},{"key":"ref21","unstructured":"[22.]\tMeadows, D. H. (2008). Thinking in systems: A primer. Chelsea Green Publishing."},{"key":"ref22","unstructured":"[23.]\tMikalef, 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."},{"key":"ref23","unstructured":"[24.]\tMittelstadt, B. (2019). Principles alone cannot guarantee ethical AI. Nature Machine Intelligence, 1, 501-507."},{"key":"ref24","unstructured":"[25.]\tMorley, J., Floridi, L., Kinsey, L., & Elhalal, A. (2020). From what to how: An initial review of publicly available AI ethics tools, methods and research to translate principles into practices. Science and Engineering Ethics, 26, 2141-2168."},{"key":"ref25","unstructured":"[26.]\tNational Institute of Standards and Technology. (2023). Artificial intelligence risk management framework (AI RMF 1.0) (NIST AI 100-1). U.S. Department of Commerce. https:\/\/doi.org\/10.6028\/NIST.AI.100-1"},{"key":"ref26","unstructured":"[27.]\tNational Institute of Standards and Technology. (2024). Artificial intelligence risk management framework: Generative artificial intelligence profile (NIST AI 600-1). U.S. Department of Commerce. https:\/\/doi.org\/10.6028\/NIST.AI.600-1"},{"key":"ref27","unstructured":"[28.]\tOECD. (2024). Recommendation of the Council on Artificial Intelligence. Organisation for Economic Co-operation and Development."},{"key":"ref28","unstructured":"[29.]\tOECD. (2025). AI adoption by small and medium-sized enterprises. Organisation for Economic Co-operation and Development."},{"key":"ref29","unstructured":"[30.]\tPodsakoff, P. M., MacKenzie, S. B., Lee, J. Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879-903."},{"key":"ref30","unstructured":"[31.]\tRaisch, S., & Krakowski, S. (2021). Artificial intelligence and management: The automation-augmentation paradox. Academy of Management Review, 46(1), 192-210."},{"key":"ref31","unstructured":"[32.]\tRaji, I. D., Smart, A., White, R. N., Mitchell, M., Gebru, T., Hutchinson, B., Smith-Loud, J., Theron, D., & Barnes, P. (2020). Closing the AI accountability gap: Defining an end-to-end framework for internal algorithmic auditing. Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency, 33-44."},{"key":"ref32","unstructured":"[33.]\tRichardson, G. P. (1991). Feedback thought in social science and systems theory. University of Pennsylvania Press."},{"key":"ref33","unstructured":"[34.]\tRogers, E. M. (2003). Diffusion of innovations (5th ed.). Free Press."},{"key":"ref34","unstructured":"[35.]\tRussell, S., Dewey, D., & Tegmark, M. (2015). Research priorities for robust and beneficial artificial intelligence. AI Magazine, 36(4), 105-114."},{"key":"ref35","unstructured":"[36.]\tS\u00e1nchez, E., Moreira, A. C., & Ferreira, J. J. (2025). Artificial intelligence adoption in SMEs: Survey based on TOE-DOI framework, primary methodology and challenges. Applied Sciences, 15(12), 6465. https:\/\/doi.org\/10.3390\/app15126465"},{"key":"ref36","unstructured":"[37.]\tSterman, J. D. (2000). Business dynamics: Systems thinking and modeling for a complex world. Irwin\/McGraw-Hill."},{"key":"ref37","unstructured":"[38.]\tTeece, D. J. (2007). Explicating dynamic capabilities: The nature and microfoundations of sustainable enterprise performance. Strategic Management Journal, 28(13), 1319-1350."},{"key":"ref38","unstructured":"[39.]\tTornatzky, L. G., & Fleischer, M. (1990). The processes of technological innovation. Lexington Books."},{"key":"ref39","unstructured":"[40.]\tVennix, J. A. M. (1996). Group model building: Facilitating team learning using system dynamics. Wiley."},{"key":"ref40","unstructured":"[41.]\tVial, G. (2019). Understanding digital transformation: A review and a research agenda. Journal of Strategic Information Systems, 28(2), 118-144."},{"key":"ref41","unstructured":"[42.]\tWamba-Taguimdje, S. L., Wamba, S. F., Kamdjoug, J. R. K., & Wanko, C. E. T. (2020). Influence of artificial intelligence on firm performance: The business value of AI-based transformation projects. Business Process Management Journal, 26(7), 1893-1924. https:\/\/doi.org\/10.1108\/BPMJ-10-2019-0411"},{"key":"ref42","unstructured":"[43.]\tYin, R. K. (2018). Case study research and applications: Design and methods (6th ed.). 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