Director, AI Enablement

Director, AI Enablement

The Director, AI Enablement will lead internal AI strategy, adoption, and transformation initiatives across business functions, identifying opportunities that deliver measurable operational and financial value. This hands-on role combines strategic portfolio management with technical prototyping to validate solutions before transitioning them to implementation partners for production deployment. You will collaborate with functional leaders, IT, Legal, and executive stakeholders to prioritize investments and establish responsible AI practices. A key focus will be preparing company data and knowledge so AI tools can operate reliably, securely, and at scale. You will also drive adoption of existing technologies, monitor performance, and ensure AI investments deliver tangible results. Reporting to the VP of IT and working with an executive steering group, you will influence enterprise-wide change without direct managerial authority. This is a remote opportunity for a U.S.-authorized professional who can connect emerging AI capabilities with practical business needs.

Accountabilities:

The Director, AI Enablement will own the internal AI portfolio from opportunity identification and experimentation through adoption, governance, and performance measurement, working across functions to deliver scalable and responsible solutions.

• Solution design and prototyping: Map end-to-end workflows with process owners and determine whether AI, conventional automation, or process redesign offers the best solution.
• Build and configure working prototypes using modern AI agents, automation platforms, and APIs to validate business value before committing significant investment or implementation resources.
• Define evaluation frameworks, human approval checkpoints, and measurable success criteria for proposed AI solutions.
• Transition validated prototypes to implementation partners for production development, ensuring clear handoffs and alignment with business requirements.
• Work with business owners to establish adoption plans and accountability for realized outcomes.
• Portfolio and strategy management: Own the internal AI use-case portfolio, including opportunity intake, prioritization, funding decisions, and retirement of underperforming solutions.
• Develop and maintain a practical AI roadmap that guides decisions about which capabilities to build, buy, or defer.
• Manage the AI investment budget, from annual planning and approval through expenditure tracking and performance assessment.
• Provide quarterly reporting on anticipated benefits, realized results, and portfolio performance.
• Data and knowledge readiness: Prepare structured and unstructured company information for reliable use by AI tools.
• Collaborate with business and technology leaders to improve data quality, governance, accessibility, and scalability.
• Delivery and adoption: Select and manage technology vendors and implementation partners, ensuring solutions meet security, integration, and operational standards.
• Increase adoption of existing AI tools through training, functional champions, usage reporting, and license optimization.
• Conduct scheduled effectiveness reviews for AI tools and agents, improving, replacing, or decommissioning solutions that fail to deliver sufficient value.
• Governance and reporting: Partner with IT and Legal to establish acceptable-use policies, data-handling practices, and security guardrails.
• Maintain AI governance practices that support ethical use and compliance with applicable requirements, including the EU AI Act, GDPR, and CCPA.
• Provide senior leadership with clear reporting on AI adoption, investment costs, risk exposure, and business impact.
• Collaborate with product teams when internal AI initiatives overlap with product capabilities or shared data, while keeping product and customer-facing AI development outside the role's direct scope.

Requirements

The ideal candidate combines hands-on technical fluency with business strategy, financial acumen, and experience leading enterprise transformation. They can translate complex AI capabilities into practical business opportunities, influence stakeholders across organizational boundaries, and deliver measurable results in an evolving environment.

• Strong practical knowledge of current AI agents, automation tools, and APIs, with the ability to build or configure functional prototypes.
• Ability to interpret technical architectures and code well enough to assess proposed solutions and challenge vendors and internal technical teams.
• Strong business and financial acumen, including the ability to connect AI investments with strategic priorities and measurable business outcomes.
• Deep understanding of AI solution patterns, decision intelligence, and the use of AI to redesign workflows, optimize operations, and enable new business models.
• Demonstrated ability to lead cross-functional transformation and technology initiatives without relying on direct reporting authority.
• Proven ability to build trust, secure executive sponsorship, and align stakeholders with competing priorities.
• Excellent communication skills, including the ability to explain complex AI concepts and technical trade-offs clearly to non-technical audiences and senior leaders.
• Familiarity with AI governance, ethical AI practices, data protection, and relevant regulatory frameworks, including the EU AI Act, GDPR, and CCPA.
• Initiative, adaptability, and comfort navigating ambiguity in a fast-moving environment.
• Bachelor's or master's degree in business, a STEM discipline, computer science, data science, or equivalent professional experience.
• At least 8 years of business or technology leadership experience, including responsibility for cross-functional technology or transformation programs.
• Experience leading business transformation or technology initiatives across complex organizations.
• Strategy or management consulting experience is an advantage.
• Work authorization: Must be legally authorized to work in the United States.

Benefits

• Remote work arrangement within the United States.
• Opportunity to shape enterprise-wide AI strategy and adoption.
• Direct collaboration with executive leadership and an AI steering group.
• Opportunity to influence technology investments, operational transformation, and measurable business outcomes.
• Exposure to modern AI agents, automation platforms, APIs, and enterprise AI governance initiatives.