As the Associate Director, Institutional AI Governance in our Data Impact & Governance department, you will lead the governance processes that safeguard patient trust, ensure responsible AI innovation, and prepare the institution for the rapidly evolving regulatory landscape. This is a high‑impact leadership role where your expertise will influence enterprise‑wide decisions across clinical care, research, education, and operations.

We offer a unique opportunity to build and operationalize one of the most advanced AI governance models in healthcare—working at the intersection of ethics, technology, policy, risk management, and institutional strategy.

What’s in it for you?

• Exceptional Benefits Package: MD Anderson provides paid medical benefits, generous PTO, and highly competitive retirement plans, supporting your health, stability, and long-term financial planning.
• Strategic Leadership Impact: Directly shape institutional standards, governance models, and decision frameworks that guide safe, ethical, and scalable AI deployment.
• Career Advancement & Visibility: Collaborate with executive leadership, institution-wide governance councils, and multidisciplinary experts across AI, clinical care, research, and compliance.
• Mission‑Driven Work: Your leadership ensures AI enhances patient outcomes, strengthens research integrity, and supports MD Anderson’s mission to end cancer.
• Growth & Innovation: Work in a forward‑thinking environment that invests in emerging technology, responsible AI, and continuous institutional improvement.

Summary

The Associate Director, Institutional AI Governance is responsible for defining, operating, and continuously improving the institution’s AI governance framework. This role ensures governance decisions are executed effectively, risks are identified early, AI lifecycle processes are followed consistently, and the institution remains compliant and audit‑ready as AI adoption grows. The role orchestrates cross‑functional participation, manages governance workflows and documentation, and ensures that oversight policies translate into repeatable and scalable operational processes.

Success requires expertise in AI governance, regulatory interpretation, risk assessment, communication strategy, and institutional alignment across complex academic medical center environments.

Major Work Activities

1. AI Governance Framework & Operating Model

• Lead and evolve the institutional AI governance framework, including policies, standards, and operating procedures.
• Define and maintain governance checkpoints across the AI lifecycle (intake, review, approval, monitoring, retirement).
• Design and operate the AI governance operating model, including workflows, documentation standards, and decision processes.
• Coordinate cross-functional engagement to ensure governance execution without duplicating operational ownership.
• Provide oversight for governance tooling, AI inventory management, and reporting standards.
• Monitor emerging AI regulations, ethics guidance, and best practices; translate insights into governance actions.
• Continuously improve governance effectiveness, efficiency, stakeholder experience, and scalability.

2. Execution & Orchestration of Institutional AI Governance

• Operate the centralized AI governance process supporting the Institutional AI Governance Council and related committees.
• Oversee governance intake, triage, and review activities across clinical, research, operational, and enterprise AI initiatives.
• Ensure governance reviews include appropriate evidence on use cases, risks, controls, performance, impact, and value.
• Maintain an authoritative institution‑wide AI inventory with complete lifecycle traceability.
• Document, communicate, and track governance decisions, required controls, and approval conditions.
• Produce governance reporting on AI risks, safety, performance, and institutional impact for executive oversight.
• Serve as the escalation point for governance process issues, exceptions, and questions.

3. Stakeholder Engagement & Institutional Alignment

• Facilitate collaboration among clinical, research, technical, legal, compliance, privacy, and security stakeholders.
• Provide clear guidance on governance requirements, expected evidence, and lifecycle obligations.
• Communicate AI governance requirements and decisions in a timely, clear, and actionable manner.
• Support governance bodies by framing tradeoffs, risks, and decision paths in complex and time‑sensitive contexts.

Competencies

Technical Expertise

• Applied understanding of AI/ML systems in healthcare to evaluate risks, controls, and intended use.
• Experience implementing and operating AI governance platforms and automated workflows.
• Strong knowledge of regulatory, legal, and ethical requirements for AI in healthcare.
• Ability to define governance expectations for AI monitoring, re‑review, change management, and retirement.

Analytical Expertise

• Translate regulatory or policy requirements into enforceable standards and review criteria.
• Assess AI systems against governance requirements and recommend defensible decisions.
• Identify, prioritize, and communicate AI risk across clinical, operational, and regulatory domains.
• Evaluate AI impact and safety using measurable indicators.
• Convert governance decisions into actionable control requirements and conditions.

Oral & Written Communication

• Create standardized governance communication templates, intake guidance, and reporting formats.
• Communicate decisions, rationale, and control requirements clearly to a variety of audiences.
• Prepare audit‑ready governance documentation and exception justifications.
• Facilitate difficult governance discussions and communicate decisions under time pressure and regulatory scrutiny.