AI Transformation & Enablement Director

This role sits within DP&I (Development Operations Platforms & Innovation), part of Development Global Clinical Operations at GSK. DP&I is building the capability to deploy AI at scale across clinical operations and the wider Development Operations function, with a mandate to help reshape how GSK plans, delivers, and continuously improves clinical trials.

DP&I develops and deploys scalable, AI-native capabilities, shared foundations, and new ways of working across Development Operations. Working across clinical operations, technology, product, data, and external partners, the team builds the platforms, products, and partnerships needed to turn innovation into measurable value.

As AI Transformation and Enablement Director, you will drive how agentic AI becomes the way all people across Development Operations deliver high quality work, and you will own what that means for how the function works. You will define the strategy and its multi-year roadmap, and build and defend the investment behind it. You will own what adoption, and exponentially increasing machine capability, mean for how work evolves across Development Operations and for the operating model: where work sits, which roles change, and which processes get fundamentally reinvented rather than automated as they stand. You will set the bar on what gets taken from ground-up build into production, and hold the view on which agentic tooling the function should be using, from the frontier labs through to open-weight and locally run models. You will be Development Operations' voice into the R&D-wide and enterprise agentic AI agenda. This role reports into the Head of Asset Acceleration and AI.

You will shape how GSK uses AI to measurably improve clinical development delivery and improve outcomes for patients.

Strategy, roadmap and investment

• Drive the agentic AI transformation and enablement strategy for Development Operations, its multi-year roadmap and the prioritisation across it, anchored to measurable clinical trial outcomes.
• Build and defend the investment case for transformation at scale, with clear ROI and payback logic, and enforce stage-gate discipline, including the call to stop or reshape what does not demonstrate value.

How the work itself changes

• Own what widespread agentic adoption and exponentially increasing machine capability mean for how Development Operations is organised: where work sits, which roles change, and how the function operates.
• Define which processes get fundamentally reinvented rather than automated as they stand.
• Carry those changes with functional leaders as their peer, so that adoption changes how the work is actually done.

Agentic tooling across Development Operations

• Hold the view on which agentic tooling Development Operations should be using, across frontier labs, open-weight and locally run models, judged on adoption, enablement, cost, output quality and compliant deployment.
• Keep that view current against a fast-moving landscape, and influence central decision making so that Development Operations ends up with appropriate, effective usage, with the evidence and the experiments behind it.

Capability and adoption at scale

• Make frontier agentic tools routine practice across every group, and set the direction for the learning and capability teams and the Champion Network that deliver it.
• Hold the function accountable for adoption: who is using what, how deeply, where uptake has stalled, and what changes as a result.
• Set the quality bar for ground-up build, and decide what gets productionised and what stays as local self-serve tooling.

Enterprise alignment and delivery

• Act as Development Operations' named counterpart into the R&D-wide and enterprise agentic AI agenda, securing the sponsorship that scaled deployment needs and setting the deployment approach with the enterprise teams behind it.
• Lead a team, and hold the delivery of the Development Operations AI portfolio through it, including how the value of both ground-up and top-down efforts is attributed.

Stakeholder Management:

• Leaders across Development Operations and R&D: shape strategy and priorities, secure sponsorship, and agree what changes in the operating model as adoption lands.
• Frontline users and the Champion Network across Development Operations: make sure what gets built solves real problems, and that the strongest ground-up work is found and scaled.
• Central AI, enterprise technology, security, regulatory and quality teams, plus the frontier labs and providers: influence central decisions, enable compliant deployment at scale, and keep a first-hand read on each option.

• Bachelor's degree in Life Sciences, Engineering, Computer Science, Business, or a related field.
• Strong and proven experience in Pharma strategy, applied AI or technology, or transformation, gained at a top-tier strategy consultancy, a leading technology or AI consultancy, or a comparable venture build or applied-AI environment.
• Deep understanding of pharmaceutical clinical development, gained in industry, consulting or other relevant settings.
• Technical understanding of how agentic systems work and where they break: context, memory, tool use, orchestration, multi-agent patterns, evaluation and reliability, plus a read on which limits are temporary and how fast that is moving.
• Frameworks for testing what an agentic system is worth on a given piece of work, and hands-on experience running those experiments against a baseline.
• Daily, self-directed use of frontier agentic development tools on real work (e.g. Claude Code, Codex), rapid prototyping and directing agents, plus open-weight and locally run models and the cost, latency and control trade-offs.
• Taking a new way of working from a handful of early adopters to routine practice across a distributed function.
• Turning technology adoption into operating model, process or role design change, with a clear view of what AI is displacing, augmenting and creating in knowledge work.
• Building and defending business cases for enterprise-scale capability, and delivering the measurable outcomes behind them.
• Experience delivering in a regulated environment, and applying compliance requirements in practice.
• Exceptional written and verbal communication, with the ability to translate complex strategic and technical topics for senior, non-technical audiences.

• Advanced degree (PhD, MBA, MSc, or equivalent) in a relevant discipline.
• A record of self-initiated builds outside the day job, whether skills, agents, tools or prototypes.
• Experience leading and developing a team, directly or through a matrix.
• Hands-on clinical operations experience, in study delivery, start-up, monitoring, data management or the trial master file, and the GxP expectations that come with deploying AI into it.

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Skills

Why GSK?

Uniting science, technology and talent to get ahead of disease together.

GSK is a global biopharma company with a purpose to unite science, technology and talent to get ahead of disease together. We aim to positively impact the health of 2.5 billion people by the end of the decade, as a successful, growing company where people can thrive.

We get ahead of disease by preventing and treating it with innovation in specialty medicines and vaccines. We focus on four therapeutic areas: respiratory, immunology and inflammation; oncology; HIV; and infectious diseases - to impact health at scale.

People and patients around the world count on the medicines and vaccines we make, so we're committed to creating an environment where our people can thrive and focus on what matters most. Our culture of being ambitious for patients, accountable for impact and doing the right thing is the foundation for how, together, we deliver for patients, shareholders and our people.

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