AI Product Owner

AI Product Owner

Location: Hybrid in New York, NY

Duration: 6-12 Month Contract

Position Overview

We are seeking an experienced AI Product Owner to lead the strategy, prioritization, and delivery of AI-enabled products and services across a global enterprise environment. This role will serve as the bridge between business strategy, technology, governance, and operational execution, ensuring AI initiatives deliver measurable business value while aligning with organizational priorities, security standards, and responsible AI practices.

The ideal candidate brings a strong blend of product ownership, stakeholder management, and practical AI knowledge, with the ability to work effectively across a complex, federated organization. This is a highly collaborative and business-facing role focused on driving adoption, improving operational efficiency, and enabling scalable AI capabilities across the enterprise.

Key Responsibilities

AI Product Strategy & Roadmap

• Define, maintain, and evolve the enterprise AI product roadmap in alignment with organizational objectives.
• Translate business priorities into scalable AI-enabled solutions and actionable use cases.
• Identify opportunities for automation, operational simplification, decision support, and workforce augmentation.
• Balance short-term business value with long-term strategic AI capability development.
• Prioritize initiatives based on business impact, complexity, adoption readiness, and risk considerations.

Stakeholder Engagement & Collaboration

• Partner with senior business leaders, program teams, operations, HR, Legal, Communications, and Technology stakeholders globally.
• Facilitate discovery sessions and workshops to identify operational challenges and AI opportunities.
• Build alignment across a decentralized operating model through influence, collaboration, and strong communication.
• Present AI concepts, opportunities, and risks in clear, business-oriented language.
• Support organizational change management efforts, training initiatives, and user enablement programs.

Product Ownership & Delivery

• Own the AI product backlog and roadmap execution from concept through deployment and adoption.
• Define user stories, acceptance criteria, KPIs, and success metrics.
• Collaborate closely with engineering, enterprise architecture, cybersecurity, data, and platform teams.
• Support Agile delivery methodologies, sprint planning, and iterative product development.
• Coordinate pilots, proof-of-concepts, and enterprise-scale rollouts.

AI Governance, Risk & Compliance

• Ensure AI solutions align with organizational ethics, privacy requirements, legal obligations, and cybersecurity standards.
• Contribute to the development and operationalization of AI governance frameworks and responsible AI guardrails.
• Partner with Information Security and Legal teams on data governance, model usage, third-party risk, and compliance considerations.
• Monitor and help mitigate emerging AI risks including hallucinations, bias, deepfakes, misinformation, and data leakage.

Adoption & Change Management

• Drive enterprise adoption and value realization for AI initiatives.
• Develop training materials, communications, and self-service guidance to support end users.
• Establish user feedback loops, adoption metrics, and continuous improvement processes.
• Promote responsible, practical, and business-focused use of AI technologies across the organization.

Data, Integration & Platforms

• Partner with enterprise architecture and data teams to support AI-ready data structures and governance practices.
• Advocate for API-first and integration-led approaches to AI enablement.
• Support integration efforts across enterprise platforms including Microsoft 365, Teams, SharePoint, Dynamics, ServiceNow, and knowledge management systems.

Performance Measurement & Reporting

• Define KPIs and measurable outcomes for AI programs and initiatives.
• Track and report on adoption rates, operational efficiencies, productivity improvements, and risk posture.
• Deliver executive-level updates to leadership teams and governance committees.

Required Qualifications

• Proven experience as a Product Owner, Product Manager, Digital Product Lead, or similar role delivering enterprise technology solutions.
• Practical understanding of AI technologies including Generative AI, AI copilots, AI agents, automation platforms, and Large Language Models (LLMs).
• Experience working within complex global organizations and managing diverse stakeholder groups.
• Strong facilitation, communication, and relationship management skills.
• Experience supporting Agile delivery methodologies and product lifecycle management.
• Ability to translate business challenges into scalable technology solutions and measurable outcomes.
• Strong written, verbal, and presentation communication skills.
• Understanding of data governance, cybersecurity, privacy, and compliance principles.

Preferred Qualifications

• Experience working within foundations, NGOs, international development organizations, or mission-driven enterprises.
• Hands-on experience with the Microsoft AI ecosystem including Copilot, Azure AI, Power Platform, and Purview.
• Familiarity with enterprise architecture concepts, APIs, and integration patterns.
• Experience contributing to AI governance or Responsible AI frameworks.
• Experience managing external vendors, implementation partners, and third-party technology providers.

Desired Attributes

• Pragmatic, solutions-oriented, and outcome-driven.
• Comfortable operating within ambiguity and evolving priorities.
• Collaborative and relationship-focused with strong influencing skills.
• Strong judgment, critical thinking, and risk awareness.
• Passionate about emerging technologies while grounded in operational realities.
• Able to simplify complexity and communicate effectively across technical and non-technical audiences.

Success Metrics (First 12 Months)

• Enterprise AI roadmap established and aligned with stakeholder priorities.
• Successful delivery of high-value AI use cases with measurable business impact.
• AI governance framework and adoption model operationalized.
• Increased AI literacy and engagement across business teams.
• Reduction in manual effort and duplicated processes through AI-driven automation.
• Clear executive reporting established around AI value realization, operational impact, and risk management.

Example Areas of Focus

• Enterprise AI assistants and copilots
• Knowledge management and enterprise search
• Workflow automation and agentic AI solutions
• Translation and multilingual support
• Meeting summarization and action tracking
• AI-assisted policy and document analysis
• Service desk and operational support automation
• Cybersecurity and threat intelligence augmentation