Oliver Wyman - AI Product Enablement Senior Manager

Overview

Oliver Wyman is a Marsh (NYSE: MRSH) business. At Oliver Wyman, we bring deep industry insight, bold innovation, and a collaborative approach that cuts through complexity to help organizations navigate their most defining transformative moments. As a business of Marsh, we work alongside the world’s leading experts across risk, reinsurance and capital, people and investments, and management consulting. Together with Marsh Risk, Guy Carpenter, and Mercer, we help organizations build resilience and competitive advantages from every angle.

With annual revenue over $24 billion and more than 90,000 colleagues in 130 countries, Marsh helps build the confidence to thrive through the power of perspective.

Job Overview:
The Quotient Inside AI Product Enablement Senior Manager works closely with the Director of Product Enablement and leads the design and execution of the AI Capability & Enablement function within Quotient Inside. Operating at the intersection of Product Strategy and Product Delivery, this role translates firm-wide AI priorities into scalable enablement strategies, structured coaching, triage, experimentation, and institutional guidance. This role serves as a senior connector between strategic intent and enterprise execution, owning operating rhythms, stakeholder alignment, prioritization, and workflow design that enable AI usage to scale responsibly and effectively across Oliver Wyman.

The Senior Manager is both hands-on and highly strategic, setting a high bar for enablement quality while identifying patterns, risks, and opportunities, and converting them into improvements that strengthen adoption and impact across the organization.

Note:

Oliver Wyman/Marsh operates a hybrid working policy of 60% in-office attendance.

Execution & Operating Model Delivery

• Lead and continuously review the operating model for the AI Capability & Enablement function, recommending improvements to the Director of Product Enablement.

• Ensure coaching, triage, experimentation, and standards-setting activities run effectively and at scale.

• Design, implement, and optimize structured workflows for intake, routing, escalation, prioritization, and feedback loops across a complex stakeholder environment.

• Track and interpret key performance indicators (e.g., adoption patterns, recurring use cases, response time, enablement effectiveness) and use data to identify trends, drive course corrections, and inform strategic decision making.

• Establish clear operating standards, governance mechanisms, and service expectations that improve consistency, quality, and responsiveness across enablement activities.

Community Engagement & Triage

• Oversee OW channels and serve as a senior clearing house for AI questions, requests, and escalations, ensuring timely, thoughtful, and well-calibrated responses across audiences.

• Assess inbound needs, exercise judgment on priority and complexity, and route appropriately.

• Direct bugs, platform issues, and systemic pain points to formal feedback and product improvement mechanisms.

• Guide general AI usage questions to living exemplars, prompt libraries, training materials, or targeted coaching interventions.

• Connect teams tackling similar use cases across Oliver Wyman and Marsh to accelerate reuse, consistency, and institutional learning.

• Maintain credibility, clarity, and professionalism in high-frequency interaction with senior and junior colleagues, while influencing effective behaviors and responsible AI usage.

Coaching & AI Experimentation

• Lead AI coaching through office hours, working sessions, and 1:1 support with colleagues who reach out via feedback channels, focusing on high-value, ambiguous, or strategically important use cases.

• Advise colleagues on translating ambiguous business problems into AI-solvable opportunities and practical workflows that drive measurable impact.

• Conduct and guide hands-on experimentation with AI tools, including:
  Meta-prompting refinement;
  Custom GPT configuration;
  Workflow prototyping.

• For high-value or repeatable problems, lead sessions that build colleague capability and judgment—teaching approach, decision logic, and scalable methods rather than simply delivering final outputs.

• Identify opportunities to elevate experimentation into repeatable practices, playbooks, and standards that can be adopted more broadly across the firm.

Pattern Capture & Institutional Learning

• Identify recurring patterns, unmet needs, and emerging opportunities across user requests, use cases, and adoption behaviors.

• Synthesize insights into reusable artifacts (living exemplars, blog posts, short demos, structured guides, playbooks) that improve consistency and enable broader self-service.

• Translate frontline learning into strategic recommendations for Product Strategy and the Director of AI Product Enablement, helping shape priorities, standards, and roadmap decisions.

• Proactively surface cross-cutting themes, risks, and opportunities that can improve enterprise AI enablement effectiveness…