Agentic artificial intelligence (AI) systems capable of autonomous planning, reasoning, and learning have reached a level of maturity that will fundamentally reshape the operating model of global securities and custody services. Historically, these functions have relied on human judgment, procedural discipline, and deeply embedded institutional expertise to safeguard client assets and uphold fiduciary responsibility. As agentic AI increasingly orchestrates complex workflows such as reconciliation, asset servicing, and risk monitoring, companies face a critical challenge that extends beyond technology adoption: the modernisation of the talent architecture that underpins trust and control. This paper argues that success in the agentic era will depend less on technology selection and more on human-centred transformation. Drawing on case examples from BNY Mellon, Citi, State Street, Northern Trust, and Clearstream, it proposes a practical threepillar framework for talent strategy: retaining and evolving institutional knowledge, upskilling and reskilling for hybrid human and AI collaboration, and attracting bridge capabilities that connect advanced technology with fiduciary accountability. The paper further examines governance models, performance metrics, and sequencing practices that enable innovation while reinforcing operational integrity. Ultimately, the findings suggest that sustainable advantage in securities and custody operations will hinge on a culture that treats learning as infrastructure and governance as a source of innovation. In an environment where trust remains the industry’s core currency, the institutions that design AI around people rather than people around AI will define the next decade of leadership. This article is also included in The Business & Management Collection which can be accessed at https://hstalks.com/ business/.
Shwetha Venkataramaiah (Mon,) studied this question.