The ongoing fourth industrial revolution has undoubtedly had a significant impact on virtually all aspects of society and business, and in this disruptive digital landscape. This study investigates the critical internal capabilities that enable small and medium enterprises to effectively adopt AI-driven innovations in the South African context. By examining key factors such as AI readiness, organizational learning capacity, strategic flexibility, and data management capabilities, the research provides a comprehensive analysis of their impact on AI-powered innovation performance. Using structural equation modelling to analyse data from SME owners and managers, the findings reveal significant positive correlations between these internal capabilities and innovation success. The results highlight the importance of investing in technological infrastructure, fostering a learning-oriented culture, and enhancing data management systems to ensure sustained competitiveness in the rapidly evolving AI landscape. These insights are crucial for SMEs aiming to leverage AI technologies for business growth and for policymakers seeking to support technology-driven sector development in emerging markets.

artificial intelligence; innovation; disruptive digital landscape; innovation performance

Agolla, J. E. (2018). Human capital in the smart manufacturing and industry 4.0 revolution. Digital transformation in smart manufacturing, 2, 41-58. https://doi.org/10.5772/intechopen.73575 Agrawal, A., Gans, J., & Goldfarb, A. (2018). Prediction machines: The simple economics of artificial intelligence. Harvard Business Review Press. Alhashmi, A., Yorks, L., Rotatori, J., Sung, C., & Justice, J. (2019). AI-driven decision-making models for businesses: A strategic roadmap. Journal of Business Strategy and Development, 15(2), 89-104. https://doi.org/10.1016/j.jbsd.2019.03.009 Alsheibani, S., Cheung, Y., & Messom, C. (2018a). AI readiness: A multi-dimensional framework for assessing AI adoption in organizations. Journal of Information Systems and Technology Management, 15(3), 299-318. https://doi.org/10.1590/1807-17752018v15n3e2905 Alsheibani, S., Cheung, Y., & Messom, C. (2018b). Artificial intelligence adoption: AI-readiness at firm-level. PACIS 2018 Proceedings, 37. https://aisel.aisnet.org/pacis2018/37 Bogers, M., Chesbrough, H., & Moedas, C. (2018). Open innovation: Research, practices, and policies. Research Policy, 47(5), 835-841. https://doi.org/10.1016/j.respol.2018.04.010 Cabrilo, S., & Dahms, S. (2020). How strategic knowledge management drives intellectual capital to superior innovation and market performance. Journal of Business Research, 110, 456-475. https://doi.org/10.1016/j.jbusres.2020.01.063 Cadden, T., Dennehy, D., Mantymaki, M., & Treacy, R. (2022). Understanding the influential and mediating role of cultural enablers of AI integration to supply chain. International Journal of Production Research, 60(14), 4592-4620. https://doi.org/10.1080/00207543.2021.1946614 Chauhan, A., Dwivedi, Y. K., & Jeyaraj, A. (2022). Emerging issues in the adoption, use, and governance of AI technologies. Journal of Business Research, 148, 315-322. https://doi.org/10.1016/j.jbusres.2022.05.005 Chauhan, S., Bansal, S., & Jain, S. (2022). AI-powered business models for sustainability in SMEs. Journal of Business Innovation, 12(3), 250-275. https://doi.org/10.1108/JBI-03-2022-0145 Cooper, D. (2023). The role of artificial intelligence in driving innovation in product development. Innovation Management Journal, 29(2), 245-257. https://doi.org/10.1080/10438599.2023.1893023 Cooper, R. (2023). Early AI adopters: A review of firms reaping the rewards of artificial intelligence. Journal of Technology Management, 45(1), 55-67. https://doi.org/10.1016/j.jtechman.2023.01.005 Crupi, A., Esposito, D., Giardino, P., & Malefani, M. (2022). The diffusion of 4IR technologies: Challenges and strategies. Technological Forecasting and Social Change, 178, 121007. https://doi.org/10.1016/j.techfore.2022.121007 Dai, L., Maksimov, V., Gilbert, B. A., & Fernhaber, S. A. (2021). Entrepreneurial orientation and international scope: The differential roles of innovativeness, proactiveness, and risk-taking. Journal of Business Venturing, 36(4), 106014. https://doi.org/10.1016/j.jbusvent.2020.106014 Dai, Y., Goodale, J. C., Byun, G., & Ding, F. (2021). Strategic learning and firm innovation: The moderating role of environmental dynamism. Journal of Business Research, 124, 278-289. https://doi.org/10.1016/j.jbusres.2020.11.063 Ferraris, A., Mazzoleni, A., Devalle, A., & Couturier, J. (2019). Big data analytics capabilities and knowledge management: impact on firm performance. Management Decision, 57(8), 1923-1936. https://doi.org/10.1108/MD-07-2018-0825 Fountaine, T., McCarthy, B., & Saleh, T. (2019). Building the AI-powered organization. Harvard Business Review, 97(4), 62-73. Gonese, N., & Ngepah, N. (2024). The impact of 4IR technologies on economic productivity in South Africa. Journal of African Development Studies, 9(2), 198-213. https://doi.org/10.1177/097569232024002 Hair, F. J., Sarstedt, M., Ringle, C. M., & Gudergan, S. P. (2017). Advanced issues in partial least squares structural equation modeling. Thousand Oaks, CA: SAGE Publications. Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis: A global perspective. Pearson. Hofmann, P., Betzing, J. H., Röglinger, M., & Kees, A. (2020). Digital Maturity: The development of a conceptual framework and managerial measurement instrument. Journal of the Association for Information Systems, 21(6), 1476-1507. https://doi.org/10.17705/1jais.00645 Hofmann, P., Probst, M., Baccarella, C. V., & Voigt, K.-I. (2020). AI readiness: Conceptualization and measurement. Technological Forecasting and Social Change, 156, 120047. https://doi.org/10.1016/j.techfore.2020.120047 Iansiti, M., & Lakhani, K. R. (2020). Competing in the age of AI: Strategy and leadership when algorithms and networks run the world. Harvard Business Review Press. Jarrahi, M. H. (2018). Artificial intelligence and the future of work: Human-AI symbiosis in organizational decision-making. Business Horizons, 61(4), 577-586. https://doi.org/10.1016/j.bushor.2018.03.007 Jarrahi, M. H., Newell, S., & Merali, Y. (2023). Human-AI collaboration in organizational decision-making: Synergies and tensions. Journal of Business Strategy, 44(2), 134-152. https://doi.org/10.1108/JBS-02-2023-0041 Jasimuddin, S. M., & Naqshbandi, M. M. (2019). Knowledge sharing in organizations: A critical review. Journal of Knowledge Management, 23(5), 947-965. https://doi.org/10.1108/JKM-02-2019-0093 Kraus, S., Palmer, C., Kailer, N., Kallinger, F. L., & Spitzer, J. (2020). Digital transformation in SMEs: A systematic review of drivers and barriers. Journal of Small Business Management, 58(2), 115-139. https://doi.org/10.1080/00472778.2019.1709382 Kruse, L. C., Wunderlich, N. V., & Beck, R. (2019). Artificial intelligence for the real-time transformation of customer services: Opportunities and challenges at the example of chatbots. Proceedings of the 52nd Hawaii International Conference on System Sciences, 2019, 3436-3445. https://doi.org/10.24251/HICSS.2019.414 Lu, Y., Papagiannidis, S., & Alamanos, E. (2022). Organizational learning capacity, innovation, and performance: The moderating role of digital transformation. Journal of Business Research, 141, 117-128. https://doi.org/10.1016/j.jbusres.2021.12.003 Lu, Y., Shen, J., & Zhan, Y. (2022). How organizational learning affects AI adoption and business value creation. Technovation, 118, 102552. https://doi.org/10.1016/j.technovation.2022.102552 Makridakis, S. (2018). Forecasting the impact of artificial intelligence, Part 3 of 4: The potential effects of AI on businesses, manufacturing, and commerce. Foresight: The International Journal of Applied Forecasting, (49), 18-27. https://doi.org/10.13140/RG.2.2.20088.01284 Mishra, N., & Tripathi, S. (2020). Artificial intelligence in business models: A transformative role for Uber and Airbnb. Journal of Strategic Innovation, 6(1), 22-40. https://doi.org/10.1016/j.jsi.2020.03.002 Olaitan, I. O., Bannister, F., & Sutcliffe, P. (2021). Employment generation and technological adoption in African SMEs: A review of South African policy. Development Economics Journal, 35(1), 45-67. https://doi.org/10.1080/10101477.2021.1746890 Pumplun, L., Reitsperger, W. D., & Sonnenberg, C. (2019). AI readiness and business impact: A conceptual framework. Business & Information Systems Engineering, 61(6), 709-720. https://doi.org/10.1007/s12599-019-00600-1 Pumplun, L., Tauchert, C., & Heidt, M. (2019). A new organizational chassis for artificial intelligence: The role of data readiness. Proceedings of the 27th European Conference on Information Systems (ECIS), 2019. https://aisel.aisnet.org/ecis2019_rp/102 Sharma, R., Gunasekaran, A., & Subramanian, N. (2024). Dynamic capabilities and AI-driven innovation in the supply chain: An empirical investigation. International Journal of Operations & Production Management, 44(3), 423-442. https://doi.org/10.1108/IJOPM-02-2024-0079 Shen, L., Zhang, X., & Liu, H. (2022). Digital technology adoption, digital dynamic capability, and digital transformation performance of the textile industry: Moderating role of digital innovation orientation. Managerial and Decision Economics, 43(6), 2038-2054. https://doi.org/10.1002/mde.3564 Sjödin, D., Parida, V., & Wincent, J. (2021). AI and digital business model innovation in industrial ecosystems: A framework for navigating AI business model development. Industrial Marketing Management, 95, 298-308. https://doi.org/10.1016/j.indmarman.2021.04.006 Sony, M., Antony, J., & McDermott, O. (2023a). Implementation of artificial intelligence (AI) in manufacturing: A multi-level conceptual framework for SMEs. Technovation, 118, 102546. https://doi.org/10.1016/j.technovation.2023.102546 Sony, M., Antony, J., & McDermott, O. (2023b). Internal capabilities for successful technology adoption in small businesses. Journal of Technology and Innovation, 18(1), 35-56. https://doi.org/10.1016/j.jti.2023.102365 Teece, D. J. (2018). Dynamic capabilities as (workable) management systems theory. Journal of Management & Organization, 24(3), 359-368. https://doi.org/10.1017/jmo.2017.75 Teece, D. J., Peteraf, M., & Leih, S. (2016). Dynamic capabilities and organizational agility: Risk, uncertainty, and strategy in the innovation economy. California Management Review, 58(4), 13-35. https://doi.org/10.1525/cmr.2016.58.4.13 Teoh, M. F., Ahmad, N. H., Abdul‐Halim, H., & Kan, W. H. (2023). Digital business model innovation among small and medium‐sized enterprises (SMEs). Global Business and Organizational Excellence, 42(6), 5-18. https://doi.org/10.1002/joe.22147 Troise, C., Sestino, A., & Viassone, M. (2022). Artificial intelligence and its role in transforming the business ecosystem. Technology in Society, 69, 101922. https://doi.org/10.1016/j.techsoc.2022.101922 Yorks, L., Rotatori, J., Sung, C., & Justice, J. (2020). Leveraging AI for business growth: A practical guide to AI applications in modern enterprises. Journal of Applied Business Research, 36(3), 45-60. https://doi.org/10.19030/jabr.v36i3.10324