AI Product Owner – Digital Practice

About the role

Oliver Wyman Digital is hiring an AI Product Owner in Dubai/Abu Dhabi to shape the AI products and agentic solutions behind the firm's AI-first transformation work for clients. The role owns what an AI product should do and why, from business discovery and workflow design through prototyping, validation and adoption. It is not a traditional product owner role: you work in small, multidisciplinary teams with AI Product Engineers, consultants, industry experts and client teams on live engagements.

Key responsibilities

• Discovery and problem framing: work with users and clients to map processes, exceptions, decisions and data dependencies, and find where agents create value versus where simpler automation is better.
• Agentic workflow design: define agent roles, tool use, hand-offs, human checkpoints, failure handling and autonomy, and create solution blueprints linking user journeys, workflows, data flows and controls.
• Hands-on prototyping: build and refine working agent and workflow prototypes with agent platforms, no-code tools or light scripting, and test them against realistic scenarios.
• Acceptance and readiness: run functional acceptance tests covering edge cases and failed actions, and coordinate technical, security and risk approvals.
• Product ownership: define requirements, backlog, roadmap and acceptance criteria, build business cases, set performance baselines and measure value after deployment.
• User experience and adoption: design how people instruct, supervise and override agents, validate usability and support training and handover.
• Responsible AI: define acceptable use, data access and decision boundaries, and work with engineers, risk, legal and security on safeguards and governance.
• Collaborate with AI Product Engineers on feasibility and trade-offs, and use AI tools to speed up discovery, research and prototyping.

Required profile

• Degree in business, design, engineering, computer science or a related field, or equivalent practical experience.
• Experience with product, digital delivery, user research, service design or process improvement; successful product launches are valued for more senior candidates.
• Evidence of personally building, testing and improving at least one working AI, agentic or automation prototype.
• Ability to turn ambiguous problems into clear requirements, workflows and acceptance criteria.
• Excellent written and verbal communication in English.

Required skills

• Working technical understanding of LLMs, agents, tool calling, context, retrieval, APIs and common failure modes.
• Functional acceptance testing for agentic behaviour.
• Nice to have: agent-builder, low-code or workflow automation platforms and light scripting (e.g. Python or SQL); user interface design; product analytics and business cases; change management; responsible AI awareness.