Senior Associate/Assistant Vice President, AI Fluency - Adoption and Change Management Specialist

Introduction

Enterprise Agentic AI adoption does not happen through tool deployment alone — it is a sustained organisational behaviour change that requires deliberate design, measurement, and iteration. The Adoption and Change Management Specialist is the driving force behind Temasek's effort to move employees from AI awareness to embedded, productive AI habits at scale. 

This role sits within the AI Automation & Fluency function and is responsible for designing and executing structured change programmes that embed new AI ways of working across Temasek's investment, operations, and support teams. In the agentic AI era, this includes building employee capability not just to build AI agents themselves, but to confidently delegate tasks to AI agents, design multi-step workflows, and exercise appropriate oversight of autonomous AI processes. This role will sit very close to actual business users, coach them to achieve all of the above. 

Responsibilities

Enterprise AI adoption leadership 

• Own end-to-end change management for major AI capability deployments - from initial stakeholder mapping and impact assessment through to sustained adoption tracking and continuous improvement.
• Design and execute adoption campaigns that move employee populations through awareness, activation, and embedded habit formation, with clear milestones and accountability at each stage.
• Build and manage a network of AI champions embedded within business units - investment teams, operations, finance, legal, and HR - who serve as peer advocates and first-line enablement support.
• Partner with senior leadership across Technology, Investment, and Operations to secure visible sponsorship for AI adoption initiatives and align change programmes with business unit priorities.
• Lead cross-functional working groups to identify and remove systemic blockers to adoption - whether tool friction, policy gaps, cultural resistance, or insufficient enablement support. 

Change management depth 

• Apply structured change management methodologies adapted to the fast-moving context of enterprise AI deployment, where tooling and use cases evolve rapidly.
• Design role-based AI learning journeys tailored to distinct employee personas - investment professionals, operations staff, and functional specialists and also across levels (Associate, VP, Director, MD) - reflecting the different AI use cases, risk profiles, and workflow contexts each group faces.
• Develop a cohesive internal communications strategy for AI fluency: including executive briefings, team-level messaging, intranet content, and showcase events that maintain momentum and surface success stories.
• Build and operate a structured feedback collection mechanism - surveys, focus groups, embedded team sessions — that generates actionable insight on adoption barriers and programme effectiveness, feeding directly into programme iteration.
• In the agentic AI era specifically, design change programmes that address the new behaviours required: how to delegate to AI agents appropriately, how to review and verify agentic outputs, and how to maintain meaningful human oversight as AI takes on more complex, multi-step tasks. 

Requirements

Experience and background 

• 5–8 years of experience in change management, organisational capability building, or enterprise technology adoption roles - with a strong preference for candidates who have led AI or digital transformation programmes in financial institutions or professional services.
• Demonstrated success driving large-scale AI or digital adoption programmes beyond pilots into sustained, measurable usage - ideally across diverse employee populations including senior professionals and non-technical staff.
• Sufficient technical literacy to understand and credibly explain AI capabilities - generative AI, agentic workflows - to non-technical audiences without requiring deep engineering expertise yourself. 

Skills and capabilities 

• Exceptional communication and storytelling ability: able to craft compelling narratives for audiences ranging from Board-level executives to frontline staff, making the value and mechanics of AI adoption tangible and motivating.
• Strong programme management discipline: able to run multiple concurrent change workstreams across different business units with clear milestones, stakeholder accountability, and documented outcomes.
• Data-driven and rigorous: comfortable designing measurement frameworks, interpreting adoption analytics, and using data to make programme decisions rather than relying on anecdote.
• Influential without authority: skilled at building trust and momentum across teams where you have no direct reporting line - the AI champion network, business unit heads, and platform engineering peers.
• Resilient and iterative: enterprise AI adoption encounters resistance, setbacks, and shifting priorities; you approach these with curiosity rather than frustration, and adapt programmes based on what you learn.