Navigating regulatory risk across the artificial intelligence programme life cycle

Abstract

Artificial intelligence (AI) is rapidly becoming embedded within the operating models of financial institutions, reshaping activities such as credit decisioning, fraud detection and customer engagement. This increased adoption is accompanied by heightened regulatory scrutiny and growing expectations around governance, accountability and risk management. This paper presents a leadership-focused perspective on managing AI as a regulated life cycle rather than a standalone technology initiative. The study argues that organisations must align AI strategy with risk appetite and regulatory obligations, supported by clear governance frameworks that integrate business, risk, compliance and technology functions. The paper outlines a structured life-cycle approach, from strategic definition through to development, implementation, monitoring and audit, highlighting the importance of embedding controls at each stage. It emphasises crucial factors, including data governance, model risk management, third party oversight and continuous performance monitoring. Drawing on current regulatory developments and industry practice, the paper illustrates how organisations can operationalise responsible AI while maintaining innovation momentum. Practical guidance is provided for senior leaders seeking to balance speed of innovation with regulatory discipline. The paper concludes that organisations adopting a life cycle–based, risk-led approach to AI governance will be better positioned to innovate sustainably while meeting evolving regulatory expectations. This article is also included in The Business & Management Collection which can be accessed at https://hstalks.com/business/.