Head of AI Risk and Compliance

Career Guide
The Head of AI Risk and Compliance leads the strategy and day to day execution of how an organization identifies, reduces, and documents risks from AI systems. This role sets policies, partners with legal and security teams, and ensures AI products meet regulatory expectations and internal standards for safety, privacy, and fairness.

Key Responsibilities

  • Set the AI risk and compliance strategy and operating model
  • Create and maintain AI governance policies and standards
  • Define risk assessments for AI use cases and AI vendors
  • Oversee model documentation and approval processes
  • Partner with legal teams on regulatory readiness and reporting
  • Work with security teams on AI security controls and incident response
  • Ensure privacy requirements are met across AI data and outputs
  • Establish monitoring for model performance and harmful outcomes
  • Lead audits and evidence collection for internal and external reviews
  • Train product and engineering teams on compliant AI development
  • Manage cross functional committees and executive updates
  • Own remediation plans and track risk acceptance decisions

Top Skills for Success

Risk Management
Stakeholder Management
Executive Communication
Program Management
Policy Writing
Regulatory Analysis
Privacy Compliance
Third Party Risk Management
Audit Management
AI Governance
Model Risk Assessment
AI Safety
Bias Risk Assessment
Model Monitoring
Incident Response

Career Progression

Can Lead To
Chief Compliance Officer
Chief Risk Officer
Head of AI Governance
Head of Trust and Safety
Head of Security Governance
VP Risk and Compliance
Transition Opportunities
Product Risk Leader
Privacy Leader
Security Risk Leader
Responsible AI Leader
Enterprise Risk Leader

Common Skill Gaps

Often Missing Skills
AI System KnowledgeModel EvaluationData GovernanceAI Vendor Due DiligenceControl DesignEvidence ManagementChange ManagementMetrics Design
Development SuggestionsBuild a repeatable governance process with clear approval steps, evidence templates, and monitoring metrics. Deepen practical AI knowledge by partnering with engineering teams and reviewing real model documentation. Practice translating technical risk into business impact for executives.

Salary & Demand

Median Salary Range
Entry LevelRare as a true entry role. Typical pathway starts at $160,000 to $220,000 in a senior manager role
Mid Level$220,000 to $320,000 total compensation
Senior Level$320,000 to $500,000 total compensation
Growth Trend
Strong growth. Demand is rising due to new AI regulations, increased model risk scrutiny, and broader enterprise AI adoption.

Companies Hiring

Major Employers
MicrosoftGoogleAmazonAppleMetaIBMSalesforceOpenAIAnthropicNVIDIAJPMorgan ChaseGoldman Sachs
Industry Sectors
TechnologyFinancial ServicesHealthcareInsuranceRetailTelecommunicationsGovernmentDefenseAutomotiveEnergy

Recommended Next Steps

1
Create an AI risk register template and pilot it on two high impact AI use cases
2
Draft an AI governance policy and get feedback from legal, security, and product leaders
3
Define a model documentation standard and roll it out with training
4
Set up a lightweight approval workflow for new AI deployments
5
Design a monitoring dashboard for safety, quality, and compliance signals
6
Establish an AI incident response playbook and run a tabletop exercise
7
Build a third party AI assessment checklist for procurement and vendor review
8
Prepare an executive brief that summarizes current AI risk and top mitigations