Senior Director, Artificial Intelligence

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The Senior Director, Artificial Intelligence is accountable for establishing, scaling, and operating the enterprise AI capability as a core business function across the organisation. Reporting to the CIO, this role serves as the enterprise authority for AI strategy, operating model, governance, and value delivery. This leader bridges strategy, technology, regulatory compliance, and execution to ensure AI initiatives deliver measurable outcomes across R&D, Clinical, Manufacturing, Quality, Commercial, and Corporate functions. This role ensures that AI is deployed in a safe, compliant, and scalable manner within a highly regulated environment, embedding AI into core business processes without introducing regulatory, ethical, or operational risk.

The role owns the end-to-end enterprise AI lifecycle, including strategy, portfolio prioritisation, operating model design, platform enablement, governance frameworks, and organisational adoption.

Key Accountabilities

Enterprise Strategy & Value Delivery

• Define and maintain the enterprise AI strategy aligned with corporate objectives and long-term business priorities.
• Translate business challenges into a prioritized AI portfolio with clear value hypotheses, success metrics, and ROI tracking.
• Serve as the enterprise leader accountable for AI value realization, ensuring initiatives deliver measurable business impact.

Portfolio Governance & Decision Authority

• Chair the Enterprise AI Governance Council and own portfolio decision rights, including use-case prioritization, investment allocation, and progression from experimentation to production.
• Establish governance mechanisms to ensure disciplined investment and prevent non-value-generating AI initiatives.
• Act as the escalation point for enterprise-level AI decisions, balancing risk, value, and feasibility.

Operating Model & Delivery Accountability

• Own and continuously evolve the enterprise AI operating model, enabling federated delivery across business units while enforcing mandatory standards, tools, and processes.
• Ensure consistent, repeatable delivery patterns from proof-of-concept through validation, production deployment, monitoring, and lifecycle management (MLOps/LLMOps).
• Hold accountability for successful execution of AI initiatives across federated teams, ensuring adherence to enterprise standards.

Governance, Risk, and Compliance

• Design and operate AI governance frameworks covering model risk, data governance, ethics, privacy, and regulatory compliance.
• Ensure AI solutions comply with applicable regulatory frameworks (e.g. GxP, ICH GCP, 21 CFR Part 11, GDPR, and similar privacy regulations).
• Establish validation, auditability, and change control processes required for regulated AI deployments in clinical.