Internal Program Manager, Artificial Intelligence

The Internal Program Manager, Artificial Intelligence coordinates the adoption and day-to-day operations of AI platforms and tools used internally (e.g., Claude, ChatGPT, GitHub Copilot, and M365 Copilot). The role measures adoption and makes the value created visible; supports teams with initiatives and the implementation of approved practices; tracks requests; serves as the single point of entry for internal AI requests; and manages the platform usage model, including groups, distribution, usage limits, and budgets. The incumbent connects teams, ambassadors, and decision-making bodies to promote the effective and responsible use of AI.

Responsibilities

Measurement, initiative tracking and reporting:

• Develop and maintain indicators that provide insight into adoption, outcomes, and opportunities for improvement, beyond consumption volumes.
• Produce reports and aggregated views by business area for leadership, and provide managers with tools to monitor and support their teams.
• Maintain existing directories and drive the development of the internal AI practices and use-case directory; track significant initiatives and their contribution within each business area based on established thresholds.
• Highlight commonalities and opportunities for sharing across business areas.
• Maintain the inventory of internal AI platforms, tools, and use cases (business area, business owner, and risk level assigned by AI governance), in collaboration with IT and AI Governance.
• Report to AI Leadership and AI Governance on the application of approved practices, observed gaps, and usage trends.

Adoption and Enablement:

• Build and maintain regular relationships with the various areas of the organization to understand AI uses, needs, and pain points.
• Ensure operational coordination of the AI Ambassadors Committee, follow up on its initiatives, and facilitate the flow of information.
• Recommend practices and implementation guides; support teams in improving how they use AI.
• Foster a regular cadence of internal AI communications, coordinate communications with ambassadors who contribute to the content, and maintain targeted monitoring of AI tools and practices.
• Escalate situations involving risk or requiring arbitration to the appropriate stakeholders.
• Communicate new policies, standards, and approved practices through AI ambassadors and managers, and ensure they are understood.
• Gather feedback from users and ambassadors on policies, practices, and learning resources, and bring it forward to AI Governance and Learning Leadership.
• Identify AI literacy needs by role, for both effective and responsible use, and communicate them to Learning Leadership.

Communication and Presentations

• Explain AI concepts, issues, and developments in clear, accessible language for users across all business areas through guides, FAQs, learning capsules, and demonstrations.
• Design and produce presentations, documents, and other communication materials for users, managers, and leadership.
• Present adoption status, results, and recommendations to executives and committees, adapting the message and level of detail to the audience.
• Facilitate information sessions, demonstrations, and practice-sharing sessions for teams and AI ambassadors.

New request-management process:

• Implement and operate the new AI request-management process.
• Serve as the single point of entry for all internal AI requests; route them to the appropriate bodies, including the AI Lab when experimentation is required; and track their progress.
• Maintain request documentation and decision logs, and follow up with requestors after decisions are made.
• Apply established intake criteria, including business owner, intended use, and data involved, to ensure requests are complete before they are routed.
• Route requests in accordance with established escalation paths and decision rights, based on the level of risk and type of request.

Platform usage model:

• Define and maintain the distribution model, groups, usage limits, and usage budgets for approved internal AI platforms, and monitor their use.
• Make authorized routine adjustments and recommend changes that require a decision or specialized intervention.
• Collaborate with IT, Security, AI Governance, and AI Leadership on groups, feature access, usage limits, and usage budgets.
• Identify usage anomalies, including unusual volumes or unexpected access or group assignments, and report them to IT and Security.
• Notify the appropriate bodies of significant vendor changes to platforms, including models, features, or terms, that may require review.
• Contribute to the periodic review and potential retirement of platforms and features by providing usage and adoption data.

Incidents and Operational Compliance

• Receive and document reports of incidents or risk situations related to AI use; route them to the appropriate stakeholders—Security, AI Governance, Legal, or Human Resources, as applicable—and follow each case through to closure.
• Monitor compliance with usage policies and approved practices, and report gaps to AI Governance.
• Document lessons learned from incidents and gaps, and incorporate them into implementation guides.