AI Program Manager

Art and Wellness Enterprises (AWE) is a professional services organization supporting non-profits founded by Alice Walton, including the Alice L. Walton Foundation, Alice L. Walton School of Medicine, Art Bridges Foundation, Crystal Bridges Museum of American Art, the Momentary, and Heartland Whole Health Institute. Job Description: Job Title: AI Program Manager Reports to: Senior Director of Financial Planning and Strategic Projects FLSA Classification: Exempt Location: Bentonville, Arkansas (On-site) Date Reviewed: 07/07/2026 Art and Wellness Enterprises (AWE) supports operating non-profits founded by Alice Walton, including the Alice L. Walton Foundation, Alice L. Walton School of Medicine, Art Bridges, Crystal Bridges Museum of American Art, the Momentary, and Heartland Whole Health Institute. About The Position The AI Program Manager is a strategic thought leader that designs and operationalizes an enterprise AI ecosystem across Art and Wellness Enterprises (AWE) and the diverse, complex portfolio of supported organizations spanning healthcare, arts, education, and philanthropy. This role moves beyond isolated AI tools and instead establishes a governed, scalable, and version-controlled AI architecture that enables repeatable, auditable, and value-driven outcomes, with a focus on automation and responsible AI usage. This role defines and implements the foundational architecture, governance model, and versioning strategy required to support AI-enabled workflows and automation across the organization. This includes designing system-level prompts, decision frameworks, and behavioral rules that ensure consistency, traceability, and compliance across all AI agents and solutions. This role owns the development of the architecture and strategy, as well as the hands-on execution of AI-enabled workflows and automation. The AI Program Manager partners closely with executive leadership, technology teams, and business units to ensure AI is deployed as an integrated ecosystem—grounded in governance, structured architecture, and measurable business value—not as bespoke, one-off solutions. This role is also responsible for accelerating adoption of AI-enabled ways of working by partnering cross functionally to understand opportunities, strategies, and building repeatable AI driven solutions. Success in this role requires strategic thinking, strong relationship-building and communication skills, and the ability to influence stakeholders across technical and operational teams. The ability to balance enterprise AI strategy, governance, and architecture with practical execution, organizational change, and responsible AI adoption is essential, along with the ability to navigate ambiguity, build consensus, and deliver measurable organizational value in a fast-paced, evolving environment. Essential Duties and Responsibilities AI Strategy and Architecture Define and implement a scalable AI architecture and framework capable of supporting multiple agents, workflows, and business use cases across the AWE ecosystem. Establish design principles for role-based agents, scoped tool usage, and modular AI components. Develop and maintain reusable patterns for AI-enabled workflows (e.g., financial review, operational analysis, stakeholder reporting). Design system prompts, reasoning frameworks, and rule sets that define how AI agents interpret data and generate outputs. Standardize prompt structures to ensure consistency across use cases and teams. Establish meta-rules governing agent behavior (e.g., prioritization logic, discrepancy handling, data validation standards). Continuously refine prompts and rule sets as part of a controlled, versioned improvement process. AI Governance and Controls Design and implement a formal AI governance framework aligned with organizational risk management and compliance requirements. Establish policies for responsible AI use, data integrity, model behavior, and decision transparency. Define control mechanisms to ensure AI outputs can be reviewed, validated, explained, and audited. Partner with leadership to position AI governance as a core capability, similar to financial and operational controls. Develop and enforce versioning standards across all layers of the AI ecosystem, including prompts, business logic, data schemas, and outputs. Maintain a structured version control system enabling rollback, comparison, and audit of AI-driven outputs. Ensure that every AI-generated outcome can be traced back to its underlying logic, assumptions, and versioned configuration. Create documentation standards that capture decision logic and evolution over time. AI Transformation and Adoption Design and implement a structured change management approach to support adoption of AI-driven workflows and operating model changes. Guide business units in transitioning from manual processes to AI-supported decision-making frameworks. Develop adoption roadmaps, readiness assessments, stakeholder engagement strategies, communications, and value realization frameworks tailored to AI-enabled transformation. Partner with leaders and team members to identify, anticipate, and address barriers to AI adoption, including trust, capability gaps, process and operating model changes, and responsible AI considerations. Develop and implement practical change interventions that accelerate AI adoption and sustain organizational change beyond initial deployment. Support the development and implementation of training, communications, and stakeholder engagement strategies that accelerate adoption and sustain long-term organizational change. Strategic Partnership Partner with technology teams to ensure architecture and governance are embedded into all technical implementations. Collaborate with business leaders to identify, prioritize, and develop high-value AI use cases suitable for scalable AI deployment, building and maintaining an enterprise roadmap and prioritizat