Associate Vice President, Model & AI Governance

Humana

2d•$189,400 - $260,500•Remote

About The Position

The Associate Vice President, Model & AI Governance is the enterprise leader responsible for establishing and overseeing Humana’s model governance, artificial intelligence risk management, responsible AI, and AI governance frameworks. Reporting to the Chief Audit & Risk Officer, the role provides independent second-line oversight and challenge of the organization’s use of models, advanced analytics, machine learning, generative AI, and emerging AI technologies. It establishes governance, risk-management, control, monitoring, and escalation frameworks so AI models are deployed safely, ethically, transparently, explainably, compliantly, securely, and in alignment with the organization’s mission and risk appetite. The position partners with executive leadership and teams across technology, data and analytics, clinical and business operations, compliance, legal, privacy, cybersecurity, information security, internal audit, and enterprise risk management. It advises executive management on emerging model and AI risks while maintaining independence from model and AI development and deployment teams. The role leads a hybrid team of internal associates and specialized external partners responsible for model validation, governance administration, AI risk assessments, monitoring, and assurance. It also promotes responsible AI and sound model governance through training, awareness, stakeholder engagement, and enterprise-wide education. This is a remote position with occasional travel to Humana offices for training or meetings; the posting indicates 25% travel and a preference for Washington, DC, New York, or Louisville, Kentucky. Work-from-home employees need a dedicated space that protects member PHI/HIPAA information and internet service with at least 25 Mbps download and 10 Mbps upload speeds.

Requirements

Bachelor’s degree required.
15+ years of progressive experience in risk management, model risk management, AI governance, technology risk, data governance, analytics, compliance, internal audit, or another relevant discipline.
Significant experience leading enterprise-wide model governance, AI governance, responsible AI, or technology risk programs.
Demonstrated experience operating at an executive level within a complex, highly regulated organization.
Strong understanding of AI/ML technologies, generative AI, model development and validation, data governance, and technology risk.
Knowledge of emerging AI regulatory and governance frameworks and applicable healthcare regulatory requirements.
Strong understanding of enterprise risk management, internal controls, issue management, and risk appetite frameworks.
Demonstrated experience presenting complex risk, technology, analytics, and AI governance topics to executive leadership and Board-level audiences.

Nice To Haves

Healthcare experience is strongly preferred.

Responsibilities

Own and continuously enhance the enterprise model governance framework across model identification, inventory, classification, risk tiering, development, validation, approval, implementation, monitoring, change management, retirement, and documentation.
Define model risk appetite, risk taxonomy, minimum control standards, governance requirements, and escalation thresholds.
Provide effective challenge over model development, validation, implementation, monitoring, and performance.
Oversee the enterprise model inventory, ensuring appropriate ownership, accountability, documentation, and risk classification.
Establish model validation standards covering conceptual soundness, performance, stability, data quality, bias, explainability, and ongoing monitoring.
Ensure appropriate governance of third-party and externally developed models.
Develop and oversee the organization’s Responsible AI framework and principles.
Establish AI governance standards addressing fairness, bias, transparency, explainability, accountability, privacy, human oversight, safety, security, and appropriate use.
Establish processes for AI use-case risk intake, assessment, approval, monitoring, and ongoing oversight, coordinating with other AI governance functions to streamline processes.
Develop standards for responsible use of generative AI, large language models, AI agents, automated decision-making, and emerging technologies in coordination with stakeholders.
Establish governance mechanisms to identify and address unintended consequences, model drift, hallucination, discrimination, explainability limitations, and other AI-specific risks.
Own the enterprise AI risk management framework and associated governance processes.
Oversee governance requirements for the enterprise AI inventory, ensuring applications and use cases are inventoried, classified, risk-rated, assigned accountable owners, and monitored throughout their lifecycle.
Develop AI risk assessments and approval requirements proportionate to potential impact.
Establish ongoing monitoring of AI performance, effectiveness, risk indicators, incidents, exceptions, and emerging threats.
Partner with cybersecurity, Privacy, Legal, Compliance, Data Governance, and Technology Risk to address AI-specific risks.
Establish governance for external AI providers, foundation models, APIs, AI platforms, and third-party AI solutions.
Establish policies, standards, procedures, control requirements, and governance committees for managing model and AI risk.
Define clear first-line ownership and second-line oversight responsibilities.
Develop, maintain, and monitor enterprise model and AI risk appetite metrics, tolerance thresholds, and key risk indicators for enterprise reporting and decision-making.
Lead Model Risk and AI Risk Governance committees and report to executive management, Risk Committees, and Board Committees on exposure, emerging risks, policy compliance, significant incidents, exceptions, and trends.
Lead a hybrid team of internal associates and specialized external partners carrying out model validation, governance administration, AI risk assessments, monitoring, and assurance.
Promote responsible AI and sound model governance through training, awareness, stakeholder engagement, and enterprise-wide education programs.