AI Product Owner

The AI Product Owner is responsible for defining, prioritizing, and delivering AI-enabled products and services across a complex global organization. This role sits at the intersection of business strategy, technology delivery, governance, and operational execution, with a strong focus on applying AI to improve productivity, decision-making, knowledge management, risk oversight, and service delivery outcomes.

This is a business-facing product leadership role rather than a deep technical engineering position. It requires strong stakeholder engagement across senior leadership, delivery teams, data and technology specialists, and operational users in a federated environment. The role ensures AI initiatives are aligned to organizational priorities, delivered effectively, and adopted at scale., AI product strategy and roadmap

• Define and maintain the enterprise AI product roadmap aligned to organizational priorities.
• Translate business needs into practical AI use cases and deliverable solutions.
• Identify opportunities for automation, augmentation, and process simplification.
• Prioritize initiatives based on value, risk, complexity, and adoption readiness.
• Balance short-term delivery with long-term capability development.

Stakeholder engagement

• Partner with business, operations, legal, HR, communications, security, and technology teams.
• Facilitate workshops to capture requirements and identify pain points.
• Build alignment across a federated organization through influence and collaboration.
• Communicate AI opportunities, constraints, and risks in clear business terms.
• Support change management and training in coordination with delivery teams.

Product ownership and delivery

• Own and manage the AI product backlog and prioritization process.
• Define user stories, acceptance criteria, and measurable success outcomes.
• Collaborate with engineering, architecture, data, and cyber security teams.
• Support agile delivery practices including sprint planning and backlog refinement.
• Oversee pilots, proof-of-concepts, and scaled production deployments.

AI governance and risk

• Ensure AI solutions comply with ethical, legal, privacy, and security standards.
• Support development and enforcement of AI governance frameworks and controls.
• Work with security and legal teams on data usage, model risk, and third-party considerations.
• Monitor and address AI-related risks including bias, hallucinations, data leakage, and misuse.

Adoption and change management

• Drive adoption and realization of AI-enabled value across the organization.
• Develop training materials, communications, and user guidance.
• Establish feedback loops and usage reporting mechanisms.
• Promote responsible and effective use of AI tools across business functions.

Data and integration

• Collaborate with enterprise architecture and data teams to ensure AI-ready data foundations.
• Support integration of AI capabilities across enterprise platforms and systems.
• Promote API-led and scalable integration approaches.

Performance and reporting

• Define KPIs and success measures for AI initiatives.
• Track and report on adoption, efficiency gains, and risk outcomes.
• Present progress updates to senior leadership and governance forums.

• Experience as a Product Owner, Product Manager, or Digital Lead delivering enterprise technology products.
• Understanding of AI concepts including generative AI, copilots, automation, and LLM-based systems.
• Experience working in complex, multi-stakeholder global organizations.
• Strong facilitation, communication, and stakeholder management skills.
• Experience working in agile delivery environments.
• Ability to translate business requirements into technology outcomes.
• Understanding of data governance, privacy, and cybersecurity principles.

Desirable

• Experience in mission-led organizations such as NGOs, foundations, or international development.
• Exposure to Microsoft AI ecosystem (Copilot, Azure AI, Power Platform, Purview).
• Familiarity with enterprise architecture and integration patterns.
• Experience defining AI governance or responsible AI frameworks.
• Experience managing third-party vendors and technology partners.