AI Governance Leader

Job Summary

The AI Governance Leader is responsible for establishing and leading the organization's AI governance framework, ensuring that all Artificial Intelligence, Generative AI, Machine Learning, automation, and advanced analytics initiatives are aligned with business objectives, regulatory requirements, security standards, and ethical principles.

This role serves as the central authority for AI governance, risk management, compliance, and policy oversight across enterprise technology, infrastructure operations, service delivery, security, cloud platforms, and data analytics functions. The AI Governance Leader will collaborate with executive leadership, architecture teams, legal and compliance stakeholders, security organizations, and operational teams to ensure AI solutions are deployed responsibly, securely, and transparently while maximizing business value and operational efficiency.

Key Responsibilities

AI Governance Strategy & Framework

• Develop and maintain the enterprise AI Governance Strategy, policies, standards, and operating model.
• Define governance structures, decision-making forums, accountability frameworks, and escalation processes for AI initiatives.
• Establish AI lifecycle governance covering ideation, design, development, deployment, monitoring, and retirement.
• Create governance controls that support responsible adoption of AI-enabled operational services, automation platforms, and intelligent service management capabilities.
• Ensure alignment between AI governance objectives and broader enterprise technology, transformation, and business strategies.

Responsible AI & Risk Management

• Establish policies and controls to ensure AI solutions operate in a responsible, transparent, fair, and secure manner.
• Lead AI risk assessments covering operational, security, compliance, legal, financial, reputational, and model risks.
• Define governance processes for model validation, approval, performance monitoring, and ongoing oversight.
• Develop controls for AI explainability, accountability, auditability, and traceability.
• Ensure appropriate management of risks associated with autonomous operations, intelligent automation, and AI-driven decision-making.

Key Responsibilities (continued)

Compliance, Security & Regulatory Oversight

• Partner with security, privacy, legal, and compliance teams to ensure AI solutions comply with applicable regulations and organizational policies.
• Establish governance controls for data privacy, information security, access management, and data protection within AI ecosystems.
• Define audit and reporting mechanisms to demonstrate compliance and control effectiveness.
• Support internal and external audits involving AI, automation, analytics, and operational platforms.
• Ensure AI governance practices are integrated with existing enterprise risk and security frameworks.

Data Governance & Quality Management

• Define governance requirements for data quality, lineage, ownership, retention, and stewardship supporting AI solutions.
• Establish standards for the use of operational, business, and infrastructure data in AI models.
• Ensure governance controls exist to manage data bias, quality issues, and inappropriate use of enterprise information.
• Collaborate with data platform teams to maintain trusted and governed data environments.
• Monitor adherence to data governance policies across AI and analytics initiatives.

Key Responsibilities (continued)

AI Operations & Performance Oversight

• Define governance metrics, KPIs, and reporting standards for AI-enabled services and automation initiatives.
• Establish monitoring and review processes to measure AI effectiveness, business value realization, service quality, and risk exposure.
• Oversee governance of predictive analytics, intelligent automation, AIOps, and self-service solutions.
• Facilitate periodic reviews of AI performance and governance maturity.
• Drive continuous improvement initiatives based on operational insights and governance findings.

Vendor & Third-Party Governance

• Establish governance processes for evaluating and managing AI-related technologies, vendors, partners, and service providers.
• Define due diligence, contractual governance, and risk assessment requirements for third-party AI solutions.
• Monitor compliance with governance standards across vendors participating in AI-enabled service delivery models.
• Support enterprise vendor consolidation and governance initiatives by ensuring appropriate controls over externally provided AI capabilities.

Key Responsibilities (continued)

Stakeholder Engagement & Governance Leadership

• Chair or lead AI Governance Boards, Review Committees, and Risk Forums.
• Provide executive reporting on AI risks, compliance posture, value realization, and governance effectiveness.
• Educate business and technology stakeholders on responsible AI practices and governance requirements.
• Promote a culture of accountability, transparency, and responsible AI adoption throughout the organization.
• Serve as a trusted advisor to senior executives on AI-related governance and strategic decisions.

Required Skills & Experience

Education

• Bachelor's degree in Computer Science, Information Technology, Data Science, Engineering, Law, Risk Management, or a related discipline.

Professional Experience

• 12+ years of experience in enterprise technology, governance, risk management, compliance, security, architecture, or operational leadership roles.
• 5+ years of experience governing AI, analytics, automation, digital transformation, or emerging technology programs.
• Proven experience developing enterprise governance frameworks, policies, standards, and operating models.
• Experience working within complex, multi-vendor, large-scale managed services or enterprise environments.
• Demonstrated success influencing executive stakeholders and leading cross-functional governance initiatives.

Required Skills & Experience (continued)

Technical & Governance Expertise

• Strong understanding of Artificial Intelligence, Machine Learning, Generative AI, Predictive Analytics, Intelligent Automation, and AIOps.
• Deep knowledge of AI governance principles, model risk management, and AI lifecycle controls.
• Experience implementing governance frameworks for enterprise technology platforms and cloud environments.
• Understanding of data governance, data quality management, metadata management, and data protection controls.
• Familiarity with IT Service Management, operational governance, and enterprise transformation programs.
• Knowledge of cloud platforms, enterprise monitoring, analytics platforms, and automation toolsets commonly used in modern infrastructure environments.
• Understanding of security controls, privacy requirements, and regulatory considerations affecting AI solutions.

Leadership & Business Skills

• Strong executive communication and stakeholder management capabilities.
• Ability to balance innovation objectives with governance and risk management requirements.
• Excellent facilitation, negotiation, and decision-making skills.
• Proven ability to establish enterprise-wide governance programs and drive organizational adoption.
• Strong analytical and problem-solving capabilities.
• Experience leading governance councils, steering committees, and executive review boards.

Required Skills & Experience (continued)

Preferred Certifications

• Relevant governance, risk, compliance, or AI governance certifications.

Success Measures

• Establishment of a robust and auditable enterprise AI governance framework.
• Successful adoption of responsible AI practices across the organization.
• Reduction of AI-related operational, compliance, and security risks.
• Increased transparency, accountability, and trust in AI-enabled services.
• Demonstrated business value realization from governed AI and automation initiatives.
• Successful regulatory, compliance, and audit outcomes related to AI implementations.