Executive Director, AI Acceleration and Enablement

Wells Fargo Bank•Charlotte, NC

About The Position

Wells Fargo is seeking an Executive Director, AI Acceleration and Enablement to set the strategy and operating model that help business teams identify, prioritize, govern, adopt, and scale artificial intelligence solutions. You will connect business priorities with enterprise artificial intelligence strategy, standards, tools, risk requirements, and delivery capabilities to accelerate responsible implementation and measurable business outcomes. The role provides companywide and cross-functional influence, establishes repeatable enablement practices, and guides senior leaders through complex decisions involving innovation, control readiness, investment, adoption, and execution. In this role you will: Represent the Business on AI Strategy, Governance, and Risk Serve as the senior business representative and primary bridge across AI business teams, governance, risk, technology, data, operations, legal, compliance, information security, and model risk Represent business priorities in enterprise, risk, and policy forums, translating complex AI, technology, and risk topics into clear business implications and actionable decisions Advise senior leaders on emerging AI capabilities, policy developments, governance requirements, and risk considerations, enabling practical, responsible adoption Drive Enterprise Governance Compliance and RAU Stewardship Lead business engagement for Risk Assessment Unit (RAU) designations and governance requirements, establishing accountability, ownership, and appropriate oversight across the AI portfolio Drive consistent application of AI and model risk policies, challenge designation decisions when appropriate, and support regulatory readiness Promote policy awareness, interpretation, adoption, and share evidence compliance across lines of business as needed Shape the Future of AI Governance Develop differentiated governance approaches for machine learning, generative AI, foundation models, agentic AI, autonomous agents, and AI-enabled workflows based on capability, use case, and risk Define governance standards for AI agents and autonomous systems, including accountability, human oversight, decision boundaries, monitoring, auditability, and operational safeguards Anticipate emerging technology, regulatory, and industry developments and translate them into governance strategies that enable innovation while strengthening risk management and resilience Influence Enterprise Policy and Operating Models Influence the evolution of AI and model risk policies, standards, and decision frameworks by advocating for risk-based, business-informed improvements Partner with enterprise and risk leaders to simplify governance processes, reduce execution friction, clarify ownership, improve transparency, advance reusable patterns and controls, and accelerate decision-making Bring together business, functional, and control partners to resolve ambiguity, manage cross-organizational dependencies, and develop durable solutions spanning products, functions, or lines of business

Requirements

10+ years of Business Execution, Implementation, or Strategic Planning experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education

Nice To Haves

Experience establishing and scaling artificial intelligence enablement, innovation, transformation, or adoption capabilities in a large, regulated organization
Knowledge of generative artificial intelligence, agentic artificial intelligence, machine learning, data, model lifecycle, technology delivery, and human-centered adoption practices
Experience translating artificial intelligence risk management, model risk management, data, privacy, legal, compliance, information security, and third-party requirements into executable business practices
Experience leading complex portfolios from opportunity identification and experimentation through production adoption, ongoing monitoring, and benefits realization
Ability to influence executive stakeholders, build consensus across business and control partners, and resolve ownership or prioritization issues across organizational boundaries
Experience creating portfolio measures, governance routines, business cases, funding recommendations, and executive-level reporting
Ability to communicate complex technical and risk topics clearly to business, technology, control, and executive audiences

Responsibilities

Represent the Business on AI Strategy, Governance, and Risk
Serve as the senior business representative and primary bridge across AI business teams, governance, risk, technology, data, operations, legal, compliance, information security, and model risk
Represent business priorities in enterprise, risk, and policy forums, translating complex AI, technology, and risk topics into clear business implications and actionable decisions
Advise senior leaders on emerging AI capabilities, policy developments, governance requirements, and risk considerations, enabling practical, responsible adoption
Drive Enterprise Governance Compliance and RAU Stewardship
Lead business engagement for Risk Assessment Unit (RAU) designations and governance requirements, establishing accountability, ownership, and appropriate oversight across the AI portfolio
Drive consistent application of AI and model risk policies, challenge designation decisions when appropriate, and support regulatory readiness
Promote policy awareness, interpretation, adoption, and share evidence compliance across lines of business as needed
Shape the Future of AI Governance
Develop differentiated governance approaches for machine learning, generative AI, foundation models, agentic AI, autonomous agents, and AI-enabled workflows based on capability, use case, and risk
Define governance standards for AI agents and autonomous systems, including accountability, human oversight, decision boundaries, monitoring, auditability, and operational safeguards
Anticipate emerging technology, regulatory, and industry developments and translate them into governance strategies that enable innovation while strengthening risk management and resilience
Influence Enterprise Policy and Operating Models
Influence the evolution of AI and model risk policies, standards, and decision frameworks by advocating for risk-based, business-informed improvements
Partner with enterprise and risk leaders to simplify governance processes, reduce execution friction, clarify ownership, improve transparency, advance reusable patterns and controls, and accelerate decision-making
Bring together business, functional, and control partners to resolve ambiguity, manage cross-organizational dependencies, and develop durable solutions spanning products, functions, or lines of business