Director, Enterprise AI Enablement & Execution

GHX

4d•$150,000 - $214,000•Remote

About The Position

The Director, Enterprise AI Enablement & Execution leads the internal AI transformation effort at GHX—helping the organization reimagine, redesign, and rebuild how work gets done through AI. This role is the primary partner to functional leaders and department heads across the enterprise, working with them to identify where AI can fundamentally change how their teams operate, and then driving that change through to execution and measurable impact. Reporting to the SVP of AI Transformation, this role owns the end-to-end lifecycle of internal AI initiatives: from understanding what a team needs and translating that into an AI-enabled solution, through delivery, workforce enablement, and ongoing value measurement. The successful candidate brings together strong program leadership, practical AI fluency, and the change management capability to move an organization forward. They will have a strong bias toward leveraging existing enterprise platforms to deliver near-term, measurable value—rather than over-engineering custom solutions—and will know when to engage engineering resources versus when an off-the-shelf capability is the right answer.

Requirements

Bachelor's degree in Computer Science, Information Systems, Business Administration, or a related field; advanced degree preferred.
8+ years of progressive experience in technology strategy, AI program management, digital transformation, or enterprise technology leadership.
3+ years of hands-on experience with AI/ML technologies, enterprise AI platforms, or large-scale AI deployment or enablement programs.
Demonstrated experience redesigning or reimagining business processes through technology in a complex, matrixed organization.
Experience standing up new functions, operating models, or enterprise programs strongly preferred.
Background in healthcare technology, regulated industries, or B2B SaaS is a plus.
Practical, hands-on experience with enterprise AI platforms such as Claude Enterprise, Microsoft Copilot, or ChatGPT Enterprise.
Working understanding of generative AI, large language models, and enterprise agentic platforms—sufficient to evaluate options, configure workflows, and guide responsible use; this is not a software engineering role.
Demonstrated ability to assess build vs. configure vs. buy decisions; a strong instinct for using existing platform capabilities (Salesforce Agentforce, Microsoft Copilot Studio, ServiceNow AI, or equivalent) to deliver fast, measurable results rather than defaulting to custom builds.
Familiarity with data privacy principles, enterprise security standards, and responsible AI practices.
Exceptional program and portfolio management capability; able to manage multiple concurrent initiatives with competing priorities and cross-functional dependencies.
Strong executive presence and communication skills; comfortable presenting to and influencing C-suite stakeholders.
Demonstrated change management capability, with a track record of driving technology adoption across a diverse workforce.
Collaborative, low-ego leadership style with proven ability to build influence and alignment without direct authority.
Strong business acumen; able to build business cases, model ROI, and connect AI capabilities to business outcomes.
Energized by building, ambiguity-tolerant, and committed to continuous learning.

Nice To Haves

Advanced degree (MBA, MS in Data Science, or related field).
Professional certifications in project management, data governance, or AI-related disciplines (PMP, CDMP, or equivalent).
Prior experience in a consulting or transformation program role.
Experience with process redesign methodologies (Lean, Six Sigma, or equivalent).
Technical proficiency with scripting, data analysis, or AI development workflows.

Responsibilities

Partner with functional leaders and department heads across the organization to identify where AI can redesign, automate, or fundamentally reimagine how work gets done.
Lead structured discovery engagements with business teams—mapping current-state workflows, identifying AI opportunity areas, and building the case for change.
Translate AI capabilities into practical redesign options that teams can evaluate, prioritize, and act on—serving as the bridge between what AI can do and what the business needs.
Drive the rebuild of AI-enabled workflows end to end, from initial design through implementation, testing, and adoption.
Help functional leaders and their teams understand how to engage with the AI program: what to bring forward, how decisions get made, and what to expect from the partnership.
Stay current on emerging AI capabilities—agentic systems, automation tools, AI-assisted decision-making—and proactively surface high-value applications to the right stakeholders.
Own the enterprise AI initiative portfolio, managing intake, prioritization, sequencing, and cross-functional execution across business units and Technology teams.
Maintain the AI use case pipeline; qualify opportunities and route them appropriately between centralized enablement and business-unit-led efforts.
Develop business cases and ROI models for AI investments, connecting AI capabilities to measurable business outcomes.
Track initiative progress, outcomes, and value realization; deliver consolidated portfolio reporting to the AI Steering Committee and senior leadership.
Apply a platform-first approach to solution design—maximizing value from existing enterprise AI tools (such as Salesforce Agentforce, Claude Enterprise, or equivalent) before engaging engineering resources for custom development; prioritize solutions that deliver measurable results quickly over longer-cycle builds.
Continuously improve delivery processes, tools, and resources based on outcomes and evolving capabilities.
Design and execute the enterprise AI adoption strategy, ensuring teams have the tools, training, and confidence to use AI effectively in their day-to-day work.
Build and activate a network of AI Champions across business units to drive grassroots adoption and surface high-value opportunities from within teams.
Partner with HR and Learning & Development to develop AI fluency pathways, role-specific playbooks, and onboarding resources for approved platforms.
Track and report on adoption metrics, training completion, and workforce readiness; design targeted interventions where gaps exist.
Communicate AI capabilities and program progress in accessible, non-technical language for employees at all levels.
Operationalize GHX's AI governance framework, including usage standards, data handling requirements, and responsible AI guidelines across all internal initiatives.
Manage the AI use case intake and approval process, applying consistent evaluation criteria that balance business value with risk and compliance requirements.
Partner with Legal, Risk, and Information Security to maintain required documentation, ensure adherence to applicable data privacy and security standards, and support audit readiness.
Identify and address shadow AI activity through discovery and policy reinforcement programs, in partnership with IT and Security.
Establish metrics and measurement frameworks for AI value realization, including productivity gains, cost savings, quality improvements, and efficiency outcomes.
Prepare and present AI program updates for the AI Steering Committee and executive leadership, covering portfolio status, delivered value, active risks, and forward priorities.
Drive continuous improvement through post-implementation reviews, outcome analysis, and systematic documentation of lessons learned.
Serve as the primary operational liaison between the Office of Enterprise AI, executive leadership, functional teams, and Technology organizations.
Set agendas, document decisions, and maintain action items for the AI Steering Committee and cross-functional working groups.
Manage organizational change across a complex, matrixed environment—securing stakeholder buy-in and sustaining momentum through resistance and competing priorities.
Model the behaviors and mindset GHX is asking of its workforce: curiosity, accountability, responsible judgment, and continuous learning.