DBS: How AI Is Redesigning Banking Roles, Reskilling and Redeployment

DBS provides an enterprise-scale case of connecting artificial intelligence to the redesign of work, roles, skills and organizational structures. This Evidence Brief examines the bank's Operating Model Transformation framework, its reported completion of nine transformations in 2025, and its approach to identifying affected job functions before defining future roles and learning pathways. It traces changes in customer service, relationship management, operations, technology and credit preparation, including documented movement into relationship and wealth-planning roles.

The report distinguishes DBS's more than 11,000 employees identified for deeper upskilling or reskilling, of whom 96% had commenced training at the 2025 Sustainability Report reporting point, from later reporting of more than 12,000 employees. It also separates bank-wide AI/ML economic value from workforce-transition outcomes. Training participation does not prove completion or successful redeployment, and workflow efficiency gains do not establish equivalent headcount reductions.

For CHROs, transformation leaders and policymakers, the case shows why AI workforce strategy needs to connect workflow design, destination roles, domain and human capabilities, career guidance and internal mobility. The evidence also raises questions about future hiring into affected roles, worker agency and the measurement of transition outcomes as AI moves toward agentic execution.