Head of Artificial Intelligence & Enablement

Please note that this position is based in Princeton, NJ. Acadia's hybrid model requires this role to work in our office three days per week on average.

Position Summary

The Executive Director, Artificial Intelligence (AI) Strategy & Enablement will oversee the company’s enterprise AI agenda, ensuring that AI adoption is safe, ethical, and value-driven. This individual will define the AI strategy, champion education and cultural change, oversee platform and architecture choices, and establish governance frameworks to ensure responsible and compliant AI adoption across Acadia globally.  As a close partner to the business, the Executive Director will shape how AI creates business value at scale, from accelerating innovation in R&D, increasing our impact in commercialization, to transforming corporate operations while ensuring trust, transparency, and risk management. This role oversees the enterprise AI governance framework, chairs the AI Governance Council, and holds final recommendations on AI native platform selection and architecture standards, balancing capabilities, cost, performance, data residency, and security.

Primary Responsibilities

• Define the enterprise AI strategy and roadmap, aligning with business priorities and overall company vision.
• Publish and iterate on a 24-month AI portfolio roadmap with value hypotheses, build-vs-buy decisions, target architectures (LLM Ops / ML Ops), and deprecation plans.
• Institutionalize an AI use-case intake and prioritization process (value, feasibility, risk), reviewed quarterly with senior leadership. 
• Partner with leadership to identify and prioritize high-value AI opportunities across R&D, Commercialization, and Corporate Functions.
• Track AI trends, emerging technologies, and regulatory landscapes to keep the organization at the leading edge.
• Facilitate RFI / RFP initiatives for evaluating new technology solutions and partnerships.
• Launch a tiered AI Literacy curriculum (Executive, Manager, Practitioner) with certifications and communities of practice; publish adoption dashboards.
• Drive change management and cultural adoption of AI as a strategic business capability.
• Establish forums to accelerate responsible experimentation and knowledge-sharing across the enterprise.
• Lead platform selection for GenAI/ML (model endpoints, vector stores, agent frameworks, guardrails), including TCO, data residency, and security posture.
• Publish reference architectures and reusable patterns for enterprise AI adoption.
• Define LLM Ops / ML Ops standards (model registry, evaluation benchmarks, prompt/version control, observability, rollback).
• Implement an enterprise AI system of record for models, prompts, and datasets with lineage, approvals, and audit trails.
• Partner with Information Technology, Data Insights and Analytics, and Information Security to ensure infrastructure, platforms, and governance frameworks support priority objectives.
• Chair the cross-functional AI Governance Council spanning risk, legal, security, and business leader membership.
• Maintain policies for lifecycle management, bias/robustness testing, explainability, human oversight, and incident response.
• Map controls to major frameworks/regulations (e.g., NIST AI RMF, EU AI Act readiness), with annual assurance.
• Ensure compliance with global AI regulations and ethical standards. Lead a product-centric, agile delivery model for AI adoption across the enterprise.
• Run a quarterly AI portfolio review with functional leadership to prioritize investments based on value, feasibility, and risk.
• Partner with Insights & Analytics leaders on their delivery of analytics use cases while focusing on AI strategy, platforms, literacy, and governance to support their ability to derive insights and actions, ultimately supporting business outcomes
• Perform other duties as assigned.

Education/Experience/Skills

• Bachelor’s degree in Information Systems, Computer Science, Data Sciences,