The accelerating velocity of software delivery in contemporary enterprises has generated unprecedented tension between agility and control within information technology change governance. Traditional Change Advisory Boards (CABs), historically designed to ensure stability, regulatory compliance, and operational continuity, are increasingly perceived as bottlenecks within DevOps and continuous delivery ecosystems. At the same time, the removal or radical dilution of CAB oversight has been associated with heightened operational risk, security exposure, and systemic fragility. This article advances the argument that predictive risk scoring powered by artificial intelligence offers a theoretically grounded and operationally viable mechanism to reconcile these competing demands. Drawing extensively upon the conceptual and empirical contributions of Varanasi (2025) alongside classical and modern frameworks of IT service management, agile governance, and DevOps culture, this study develops a comprehensive analytical model of AI-driven CAB decision-making.

The study contributes to academic knowledge by articulating a unified theoretical model that integrates AI risk scoring with agile governance and change management, thereby addressing a major gap in existing scholarship that has treated these domains in isolation. For practitioners, the article provides a conceptual blueprint for reimagining CABs as adaptive, intelligent governance platforms rather than static control bodies. Ultimately, the research positions predictive AI not as a replacement for human judgment but as an epistemic partner that restructures how risk, accountability, and organizational learning are produced in digital enterprises.

Change Advisory Board, Predictive Risk Scoring, DevOps Governance, IT Change Management

EduTech Wiki. Change management. 2010.

Humble, J., and Farley, D. Continuous Delivery: Reliable Software Releases through Build, Test, and Deployment Automation. Addison Wesley. 2010.

Varanasi, S. R. AI for CAB Decisions: Predictive Risk Scoring in Change Management. International Research Journal of Advanced Engineering and Technology, 2(06), 16 to 22. 2025. https://doi.org/10.55640/irjaet-v02i06-03

Davis, J. Modernizing Change Management in IT. Wiley. 2019.

Soomro, T. R., and Wahba, H. Y. Role of information technology infrastructure library in data warehouses. American Journal of Applied Science, 8, 1384 to 1387. 2011.

Brown, R., Smith, A., and Lee, T. Collaborative Approaches in IT Management. Journal of IT Best Practices, 45(3), 25 to 39. 2020.

BMC Software Inc. About BMC Software. 2011.

Johnson, K. Adopting Agile for Change Management. Agile Times Quarterly, 14(2), 11 to 19. 2020.

Sauve, J., Rebroucas, R., Moura, A., Bartolini, C., Boulmakoul, A., and Trastour, D. Business driven decision support for change management: planning and scheduling of changes. Hewlett Packard Development Company. 2006.

Anderson, P., and Martin, L. Streamlining IT Governance for Agile Success. TechWorld Press. 2020.

Addy, R. Effective IT Service Management: To ITIL and Beyond. Springer. 2007.

Chen, L., Wang, Y., and Liu, H. The impact of DevOps on the software development process. International Journal of Software Engineering and Applications, 10(1), 47 to 56. 2019.

Green, A. Avoiding Bottlenecks: Streamlining the Change Process in IT. Efficient Systems. 2020.

Davis, T. Change Management in IT: Bridging the Gap Between Procedures and Agility. Business Insights. 2019.

Smith, J. Understanding the Role of CABs in IT: Evolving Change Management. Tech Journal. 2020.

CA Inc. What are five questions every customer asks about CA Services. 2011.

Lwakatare, L. E., Karhu, K., and Oivo, M. The role of governance in DevOps: a case study. Journal of Software Evolution and Process, 31(5), e2162. 2019.

Petersen, K., Vinterbo, S. A., and Kare, M. Agile governance: Balancing agility and governance in a digital world. Journal of Systems and Software, 148, 118 to 127. 2019.