Artificial Intelligence Driven Business Innovation and AI Governance A Systematic Literature Review

Dwi Andayani; Wisnu Wira Atmadja  Effendi; Luiz Rubio

doi:10.34306/ajri.v8i1.1604

Authors

Dwi Andayani Muhammadiyah University of Jakarta https://orcid.org/0009-0007-1095-4093
Wisnu Wira Atmadja Effendi Zhejiang University https://orcid.org/0009-0001-8412-7003
Luiz Rubio Ilearning Incorporation https://orcid.org/0009-0003-6543-5179

DOI:

https://doi.org/10.34306/ajri.v8i1.1604

Keywords:

Artificial Intelligence, Business Innovation, AI Governance, Digital Transformation, Systematic Literature Review

Abstract

The rapid advancement of Artificial Intelligence (AI) has significantly transformed modern business environments by enhancing operational efficiency, supporting data-driven decision-making, and enabling the development of innovative business models. However, the widespread adoption of AI also introduces governance-related challenges, including issues of transparency, accountability, ethics, privacy, and regulatory compliance, making AI governance an increasingly important area of concern. This study aims to systematically review the existing literature on AI-driven business innovation and AI governance to identify current research trends, major themes, opportunities, and challenges in the field. A Systematic Literature Review (SLR) methodology was employed by collecting and analyzing relevant scholarly articles from major academic databases based on predefined inclusion and exclusion criteria. The results reveal that AI contributes substantially to business innovation through process automation, predictive analytics, enhanced customer engagement, and strategic decision-making, while effective AI governance frameworks facilitate responsible AI adoption, strengthen stakeholder trust, and support sustainable digital transformation. The review further highlights that organizations achieving a balance between technological innovation and governance practices are better positioned to maximize the benefits of AI while mitigating potential risks. In conclusion, AI-driven business innovation and AI governance are mutually reinforcing factors that play a critical role in promoting sustainable business growth and long-term organizational competitiveness in the digital era.

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References

[1] I. Austin and G. A. Jones, Governance of higher education: Global perspectives, theories, and practices. Taylor & Francis, 2024.

[2] R. Raman, A. Iyer, and P. Nedungadi, “Forecasting artificial general intelligence for sustainable development goals: a data-driven analysis of research trends,” Sustainability, vol. 17, no. 16, p. 7347, 2025.

[3] Q. Aini, D. Manongga, U. Rahardja, I. Sembiring, and Y.-M. Li, “Understanding behavioral intention to use of air quality monitoring solutions with emphasis on technology readiness,” International Journal of Human–Computer Interaction, pp. 1–21, 2024.

[4] M. Usman, N. Khan, and A. Omri, “Environmental policy stringency, ict, and technological innovation for achieving sustainable development: Assessing the importance of governance and infrastructure,” Journal of environmental management, vol. 365, p. 121581, 2024.

[5] R. Machucho and D. Ortiz, “The impacts of artificial intelligence on business innovation: A comprehensive review of applications, organizational challenges, and ethical considerations,” Systems, vol. 13, no. 4, p. 264, 2025.

[6] U. Rahardja, Q. Aini, A. S. Bist, S. Maulana, and S. Millah, “Examining the interplay of technology readiness and behavioural intentions in health detection safe entry station,” JDM (Jurnal Dinamika Manajemen), vol. 15, no. 1, pp. 125–143, 2024.

[7] P. Radanliev, “Privacy, ethics, transparency, and accountability in ai systems for wearable devices,” Frontiers in Digital Health, vol. 7, p. 1431246, 2025.

[8] D. K. Das, “Exploring the symbiotic relationship between digital transformation, infrastructure, service delivery, and governance for smart sustainable cities,” Smart cities, vol. 7, no. 2, pp. 806–835, 2024.

[9] T. Hidayat, D. Manongga, Y. Nataliani, S. Wijono, S. Y. Prasetyo, E. Maria, U. Raharja, I. Sembiring et al., “Performance prediction using cross validation (gridsearchcv) for stunting prevalence,” in 2024 IEEE International Conference on Artificial Intelligence and Mechatronics Systems (AIMS). IEEE, 2024, pp. 1–6.

[10] S. Chandwani, “Ai-orchestrated enterprise integration platforms for intelligent automation,” AI- Orchestrated Enterprise Integration Platforms for Intelligent Automation Frontiers in Computer Sci- ence and Artificial Intelligence, 2025.

[11] J. Torres and M. L´opez, “Impact of innovation on the business model on organizational quality and competitiveness,” National Journal of Quality, Innovation, and Business Excellence, vol. 1, no. 1, pp. 1–6, 2024.

[12] S. Haque, N. Mohammad, A. Mambetaliev, A. Karshiboev, K. Y. Lucky, M. T. H. Khan, and H. Islam, “Artificial intelligence-driven business analytics for it strategy: Advancing decision-making, real-time insights, and organizational agility through intelligent automation and data integration,” Journal of Posthumanism, vol. 5, no. 6, pp. 1848–1863, 2025.

[13] C. Larabi, “The role of innovation capability and strategic orientation to achieve competitive advantage: the mediating effect of strategic renewal in smes,” Journal of Strategy and Management, vol. 18, no. 4, pp. 821–848, 2025.

[14] M. D. T. P. Nasution, Y. Rossanty, R. Harahap, A. R. Tanjung, and T. A. M. Nasution, “Technology-driven resource utilization and integration to enhance firm performance,” Aptisi Transactions on Technopreneurship (ATT), vol. 8, no. 1, pp. 268–283, 2026.

[15] P. Soto-Acosta, S. Popa, and A. D. Ros-Galvez, “How ai integrators translate ai regulation into innovation: a qualitative study,” European Journal of Innovation Management, vol. 29, no. 6, pp. 1891–1921, 2026.

[16] A. A. Setyawan, E. Setyawati, and J. S. P. Tyoso, “Digital resilience framework for msme development in facing global market volatility,” Aptisi Transactions on Technopreneurship (ATT), vol. 8, no. 1, pp. 239–252, 2026.

[17] M. Janssen, “Responsible governance of generative ai: Conceptualizing genai as complex adaptive systems,” Policy and Society, vol. 44, no. 1, pp. 38–51, 2025.

[18] D. W. S. Rahayu, B. Septiawan, A. D. S. Hamidah, and R. F. Terizla, “Tourism expectation as moderator of promotion objectives and promotion mix on tourist interest,” Aptisi Transactions on Technopreneurship (ATT), vol. 8, no. 1, pp. 166–176, 2026.

[19] C. Zhou, “Toward human-ai collaboration for sustainable development: Unveiling the drives of artificial intelligence adoption in environmental governance,” Sustainable Development, 2026

[20] D. Vrontis, A. Thrassou, L. Efthymiou, and M. Bozat, “Business in a turbulent era: Organisations, industries and markets,” in Business in a Turbulent Era, Volume I: Organisations, Industries and Markets. Springer, 2025, pp. 1–23.

[21] G. Kydyrbayeva, D. Makhmetova, G. Kulzhanbekova, R. Anayatova, A. Otetileuova, and Z. Tashenova, “The initial state of educating future primary school teachers in a multilingual context,” Aptisi Transactions on Technopreneurship (ATT), vol. 8, no. 1, pp. 152–165, 2026.

[22] A. Tripathi and V. Kumar, “Ethical practices of artificial intelligence: A management framework for responsible ai deployment in businesses,” AI and Ethics, vol. 5, no. 4, pp. 3845–3856, 2025.

[23] J.-Y. Lin and C.-C. Chen, “Driving innovation through customer relationship management a data-driven approach,” Sustainability, vol. 17, no. 8, p. 3663, 2025.

[24] E. Erika, R. T. H. Safariningsih, D. Cahyono, and N. Rangi, “Strategic integration of cloud cybersecurity for resilient digital business transformation,” ADI Journal on Recent Innovation, vol. 7, no. 1, pp. 112– 124, 2025.

[25] H. Gamal, “Technological integration and innovative strategies harnessing artificial intelligence for operational excellence,” in Building business knowledge for complex modern business environments. IGI Global Scientific Publishing, 2025, pp. 237–270.

[26] R. A. Sunarjo, A. Andika, N. Lutfiani, and R. Evans, “Ai enabled cybersecurity framework for multi cloud business environments,” ADI Journal on Recent Innovation, vol. 7, no. 1, pp. 100–111, 2025.

[27] G. Marzi, M. Balzano, A. Caputo, and M. M. Pellegrini, “Guidelines for bibliometric-systematic literature reviews: 10 steps to combine analysis, synthesis and theory development,” International Journal of Management Reviews, vol. 27, no. 1, pp. 81–103, 2025.

[28] B. Birdayanthi, Y. Yusriadi, and I. Ikmal, “Accountability and transparency in public administration for improved service delivery,” Journal Social Civilecial, vol. 3, no. 1, pp. 34–47, 2025.

[29] M. Mulyati, S. Zebua, D. Apriani, F. P. Oganda, A. Fitriani, S. V. Sihotang, and N. A. Santoso, “Optimiza- tion of community entrepreneurship through diversification and digitalization of locally based chocolate beverages,” ADI Journal on Recent Innovation, vol. 7, no. 1, pp. 88–99, 2025.

[30] A. Batool, D. Zowghi, and M. Bano, “Ai governance: a systematic literature review,” AI and Ethics, vol. 5, no. 3, pp. 3265–3279, 2025.

[31] L. H. Aziz, R. A. Sunarjo, M. Ramdani, Q. Aini, E. A. Natalia, and L. Maria, “Implemetation of rop in stock control to minimize losses due to expiry,” ADI Bisnis Digital Interdisiplin Jurnal, vol. 6, no. 2, pp. 220–232, 2025.

[32] P. Pujari, G. Behl, A. H. Rizvi, K. Kakde, S. Suryawanshi, and S. Dingankar, “Bibliometric mapping of artificial intelligence applications in healthcare: A sciencedirect and scopus-based analysis,” Asia Pacific Journal of Health Management, vol. 20, no. 2, pp. 1–18, 2025.

[33] Trisnawati, “Artificial intelligence governance and regulation: A roadmap to developing legal policies for artificial intelligence deployment,” Journal of Governance and Administrative Reform, vol. 5, no. 2, Dec. 2024. [Online]. Available: https://garuda.kemdiktisaintek.go.id/documents/detail/4665333

[34] R. Nezameslami, A. Nezameslami, B. Mehdikhani, A. Mosavi-Jarrahi, A. Shahbazi, A. Rahmani, A. Masoudi, M. Yeganegi, R. Akhondzardaini, M. Bahrami et al., “Adapting prisma guidelines to enhance reporting quality in genetic association studies: A framework proposal,” Asian Pacific Journal of Cancer Prevention: APJCP, vol. 26, no. 5, p. 1641, 2025.

[35] C. S. Bangun, S. Solahudin, A. Sutarman, and S. Dlamini, “The role of application programming interface in transforming restaurant delivery operations,” Startupreneur Business Digital (SABDA Journal), vol. 5, no. 1, pp. 88–95, 2026

[36] G. Bosco, V. Riccardi, A. Sciarrone, R. D’Amore, and A. Visvizi, “Ai-driven innovation in smart city governance: achieving human-centric and sustainable outcomes,” Transforming Government: People, Process and Policy, vol. 20, no. 1, pp. 98–123, 2026.

[37] D. Manongga, I. Kovac et al., “Cyberpreneurial mindset as a driver of digital startup success in emerging digital economies,” Startupreneur Business Digital (SABDA Journal), vol. 5, no. 1, pp. 67–77, 2026.

[38] E. Susetyono, D. S. Priyarsono, A. Sukmawati, and P. Nurhayati, “Improving risk management maturity in ultra micro soe holding companies,” Aptisi Transactions on Technopreneurship (ATT), vol. 8, no. 1, pp. 310–324, 2026.

[39] D. Abbas, A. Simanjuntak, and T. S. Goh, “Integrating broadcasting data mining and visualizationfor effective big data decision support,” Bridging of Emerging AI and Media Broadcasting (BEAM), vol. 1, no. 2 May, pp. 99–110, 2026.