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About the Role
Establish and lead the organization's AI governance framework, ensuring AI, Generative AI, Machine Learning, automation, and advanced analytics initiatives align with business objectives, regulatory requirements, security standards, and ethical principles. Serve 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.
Responsibilities
- 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 governance across the AI lifecycle, covering ideation, design, development, deployment, monitoring, and retirement.
- Create governance controls that support the 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.
- 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.
- 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.
- 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.
- 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 realisation, 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.
- 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.
- Chair or lead AI Governance Boards, Review Committees, and Risk Forums.
- Provide executive reporting on AI risks, compliance posture, value realisation, 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.
Requirements
- 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.
Skills
- Artificial Intelligence
- Machine Learning
- Generative AI
- Predictive Analytics
- Intelligent Automation
- AIOps
- AI governance principles
- Model risk management
- AI lifecycle controls
- Enterprise technology platform governance
- Cloud environment governance
- Data governance
- Data quality management
- Metadata management
- Data protection controls
- IT Service Management
- Operational governance
- Enterprise transformation programs
- Cloud platforms
- Enterprise monitoring
- Analytics platforms
- Automation toolsets
- Security controls
- Privacy requirements
- Regulatory considerations for AI solutions
- Executive communication
- Stakeholder management
- Innovation
- Risk management
- Facilitation
- Negotiation
- Decision-making
- Problem-solving
Experience Level
- 12+ years of experience
- 5+ years of experience
Education Level
- Bachelor's degree in Computer Science, Information Technology, Data Science, Engineering, Law, Risk Management, or a related discipline.