Oliver Wyman - AI Product Owner, Product Strategy - Dallas

📍 Job Overview

Job Title: AI Product Owner, Product Strategy

Company: Oliver Wyman (a Marsh McLennan Business)

Location: Dallas, Texas, United States

Job Type: Full-time

Category: Product Management / Strategy / Operations

Date Posted: November 3, 2026

Experience Level: 5-10 years

Remote Status: Hybrid

🚀 Role Summary

• This role is pivotal in bridging the gap between high-level product strategy and tangible delivery execution for AI-enabled products and capabilities within Oliver Wyman's Quotient Inside initiative.

• The AI Product Owner will be instrumental in defining product experiences, leading specific workstreams, and translating strategic visions into detailed, prioritized requirements and actionable delivery plans for engineering and development teams.

• A key aspect of this role involves deep collaboration across Product Strategy, Design, Research, Engineering, Enablement, and AI Capability teams to ensure that AI products are not only aligned with business objectives but also grounded in genuine end-user needs and operational realities.

• Success in this position will be measured by the ability to drive AI-enabled products from conceptualization through successful launch, adoption, and ongoing iteration, leveraging structured problem-solving, product ownership, and effective executive communication.

📝 Enhancement Note: The "Quotient Inside" designation suggests an internal product or platform initiative aimed at enhancing consulting operations or client-facing capabilities through AI. This implies a focus on practical application, user adoption within a professional services context, and a direct impact on consultant efficiency and client outcomes. The role requires a blend of strategic thinking and hands-on execution, typical of product owner roles within technology-focused divisions of large consulting firms.

📈 Primary Responsibilities

• Product Definition & Initiative Ownership: Take full ownership of defined AI products or capabilities from initial concept through to launch, user adoption, and subsequent iterative improvements, ensuring alignment with strategic goals.

• Requirement Translation & Backlog Management: Translate high-level strategic direction and epics into detailed product requirements, features, user stories, acceptance criteria, and measurable success metrics, meticulously managing the product backlog.

• Cross-Functional Collaboration & Alignment: Serve as the central point of coordination for assigned AI products, fostering strong relationships and ensuring alignment across Product Strategy, Engineering, Design, Research, Enablement, AI Capability & Adoption teams, and consulting stakeholders.

• Discovery & User Insight Integration: Actively participate in and co-lead discovery activities (interviews, workshops) to gather user needs, practitioner pain points, and operational friction, translating these insights into actionable product requirements and features.

• Roadmap, Prioritization & Work Planning: Drive prioritization discussions for epics and features, balancing user value, business impact, technical feasibility, and strategic alignment; develop and maintain detailed work plans with timelines and milestones.

• Business Case & Executive Communication: Contribute to the development of business cases for AI products, articulating value propositions, risks, and expected outcomes, and create executive-ready materials that clearly communicate complex AI concepts and product plans to senior leadership.

• Delivery Readiness & Continuous Improvement: Partner closely with delivery teams to ensure requirements are clear and actionable, facilitate product demos, validate delivered functionality against acceptance criteria, and support launch and adoption planning, while also tracking feedback for iterative enhancements.

📝 Enhancement Note: Given the context of a consulting firm like Oliver Wyman, the "user needs" and "practitioner pain points" will likely refer to internal consultants and their workflows, or potentially client-facing applications that consultants will utilize. The emphasis on "AI-enabled products" and "non-deterministic validation" indicates a need for understanding the nuances of AI/ML outputs and how to manage their inherent variability within a structured product development process.

🎓 Skills & Qualifications

Education: While no specific degree is listed, a Bachelor's degree in a relevant field such as Computer Science, Engineering, Business, Information Technology, or a related discipline is typically expected for roles of this nature. Advanced degrees or certifications in Product Management or AI are advantageous.

Experience: 4-8 years of progressive experience in product ownership, product management, management consulting, strategy development, or digital product delivery.

Required Skills:

• Proven experience owning defined products, capabilities, or features from concept through their entire lifecycle (build, launch, adoption, iteration).

• Demonstrated ability to translate business needs and strategic priorities into structured product requirements, features, user stories, acceptance criteria, and success metrics.

• Expertise in facilitating stakeholder discussions, conducting discovery sessions, leading workshops, managing backlog refinement, prioritization, and planning sessions.

• Strong capabilities in business case development and applying structured problem-solving methodologies.

• Excellent executive presentation skills, with a high proficiency in PowerPoint and the ability to craft compelling narratives for senior audiences.

• Familiarity with AI-enabled products, internal platforms, and workflow automation tools.

• Experience operating within complex, matrixed organizational structures, preferably in professional services. Preferred Skills:

• Direct experience delivering AI-enabled products, including familiarity with Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) workflows.

• Experience with non-deterministic validation of AI outputs and evaluating AI capabilities in a practical, business context.

• Deep understanding of Agile delivery practices, including sprint planning, backlog refinement, and sprint demos.

• Ability to build high-level mock-ups to support design and engineering teams.

• Experience