AI Product Owner Vice President

AI Product Owner Vice President

Wealth Management Platforms

Purchase NY

Morgan Stanley Wealth Management Platforms (WMP) Digital Client Experience (DCE) is seeking a product leader to serve as anAI Product Ownerdriving the strategy and delivery ofAI-enabled digital servicingexperiences across Morgan Stanley and E*TRADE client platforms. You will own AI-centric product outcomes acrossvirtual agentsrisk programs andplatform unification delivering measurable improvements in client experience operational efficiency and risk posture.

This role is a hands-on builder PO: you willown OKRspartner deeply with UXwork across large dependency teamsin a legacy environment and be capable ofusing tooling to generate code prototypes and analytics dashboardsto accelerate delivery.

What youll own (focus areas)

• Virtual Agents & Conversational Experiences:AI-assisted self-service guided journeys escalation/handoff patterns and agent-assist capabilities.
• Risk Programs for AI Digital Servicing:Responsible AI controls governance monitoring and audit-ready documentation embedded into the product lifecycle.
• Platform Unification:Converging servicing capabilities across web/mobile and Morgan Stanley/E*TRADE surfaces including shared components APIs and consistent UX patterns.

About Morgan Stanley

Morgan Stanley is a leading global financial services firm providing a wide range of investment banking securities investment management and wealth management services. The Firms employees serve clients worldwide including corporations governments and individuals from more than 1200 offices in 43 countries.

Morgan Stanley is committed to helping its employees build meaningful careers and we strive to be a place for people to learn achieve and grow.

Department Overview

In the Wealth Management division we help people businesses and institutions build preserve and manage wealth so they can pursue their financial goals

Wealth Management (WM) Platforms manages industry-leading platforms across all WM channels and client segments to provide a unified digital experience unlock growth and deliver efficiencies for Advisors Clients and Institutions. WM Platforms consists of ten sub-teams including: Field Experience & Platforms Digital Client Experience & Platforms Workplace Platforms Automation & Workflow Digital Trading & Investing Generative AI UX Design & Research Strategy & Execution WM Platforms Risk and the Chief Operating Office.

What youll do in the role:

• Product strategy & outcome ownership
  • Define product vision andOKRsfor AI-enabled servicing (e.g. containment/deflection time-to-resolution CSAT/NPS impact cost-to-serve reduction risk events reduction).
  • Own a metrics-first operating cadence: set baselines targets instrumentation requirements and post-launch optimization loops. (Expands the current KPI ownership expectation)
• Disciplined AI product development lifecycle
  • Lead end-to-end product development: problem framing discovery delivery launch optimization using usage data client feedback and competitive intelligence as in the original role but adapted to AI systems (probabilistic outputs continuous improvement).
  • Translate ambiguous needs into AI-suitable scope andtestable acceptance criteria including explicit do-not-automate boundaries and human oversight needs.
• Backlog roadmap and dependency orchestration in a complex environment
  • Build and maintain a prioritized backlog inJira and manage roadmap sequencing across multiple platforms and legacy services.
  • Drive alignment across many dependency teams (technology service UX Legal Risk Compliance Data Operations).
• UX ownership (experience and conversation design)
  • Be accountable for end-to-end experience quality (not requirements handoff): co-own IA content strategy and interaction design with UX.
  • Ensure experiences meet usability standards: clarity recovery from failure safe fallback behavior and accessible design.
  • Establish and enforce design patterns across unified platforms to reduce inconsistency and cognitive load.
• AI evaluation quality and release readiness
  • Define AI quality measures (task success rate hallucination/error rates escalation accuracy safety policy adherence).
  • Own evaluation strategy: offline test sets human review workflows pilot/A-B plans and regression checks.
  • Ensure release readiness includes monitoring rollback incident playbooks and measurable guardrails.
• Embedded risk management for AI digital servicing
  • Identify risks that impact roadmap delivery and client outcomes (as in the original) expanding to include AI-specific risks: privacy leakage unsafe responses bias explainability expectations and misuse.
  • Partner with Legal Risk Compliance and Fraud to define required controls (approvals logs disclosures audit trails) and integrate into the Definition of Done.
• Data product ownership for AI readiness
  • Drive requirements for data access quality labeling/ground truth taxonomy and lifecycle management needed to support virtual agents and servicing automation.
  • Ensure analytics/events are implemented to measure OKRs and model performance in production.
• Hands-on acceleration: dashboards prototypes and code generation
  • Create and maintaindashboardsfor OKRs/KPIs experimentation results and operational health (containment escalations top intents failure modes drift indicators).
  • Use approved tooling togenerate code snippets API examples test scripts prompt/policy configurations and lightweight prototypes to accelerate engineering throughput (with appropriate review and SDLC controls).
  • Provide high-quality developer-ready artifacts: sequence diagrams edge cases error states instrumentation specs.
• Stakeholder leadership & business reviews
  • Orchestrate business reviews exec updates and working forums (planning materials execution follow-ups) as in the original role adding AI program reporting: risk posture evaluation results and production health.

Skills Required:

• 9.5 Years of transferable experience across work and higher education
• Master of Business Administration (MBA) or Bachelors degree (BS/BA) with ample work experience.
• 5 years building digital products/platforms including backlog management roadmap planning and metrics ownership.
• Experience owning digital containment KPIs (e.g. containment/deflection escalation precision task success rate) and operating a post-release optimization loop.
• Experience defining and running AI evaluation (offline golden set regression testing human review rubric) and production monitoring/incident response.
• Ability to define AI product requirements: guardrails human-in-the-loop points evaluation metrics and monitoring.
• Ability to understand technical architecture and code converse in detail with engineering about APIs logs and system diagrams; able to work effectively inlegacy architecturesand across multiple dependency teams.
• Uses approved AI/dev tooling to producereviewablecode artifacts (scripts prototypes test cases prompt/policy configs) to accelerate delivery;engineering ownsproduction implementation review and SDLC compliance.
• Demonstrated capability with UX and engineering to deliver high-quality client-friendly experiences including ownership of end-to-end flows content and interaction patterns.
• Strong written/verbal communication critical thinking organization and ability to drive cross-functional alignment.

Preferred Skills

• Experience partnering with Legal/Risk/Compliance on customer-facing digital experiences and capable of embedding controls into product delivery for AI-enabled features.
• Wealth management / brokerage / banking domain familiarity preferred.
• Customer servicing process knowledge (intent taxonomy call drivers servicing flows) preferred.

Success Outcomes

• Digital containment improves 5% annually with no increase in high-severity complaints; with measurable reduction in top servicing pain points (time-to-resolution repeat contacts).
• Unified platform capabilities reduce duplicated work across channels/brands; consistent UX and shared components adopted by multiple teams.
• OKRs are instrumented reviewed monthly and drive roadmap decisions; dashboards are trusted by stakeholders.
• AI risk controls are audit-ready: logs evaluations and governance artifacts are complete and continuously maintained.

WHAT YOU CAN EXPECT FROM MORGAN STANLEY:

At Morgan Stanley we raise manage and allocate capital for our clients helping them reach their goals. We do it in a way thats differentiated and weve done that for 90 years. Our values - putting clients first doing the right thing leading with exceptional ideas committing to diversity and inclusion and giving back - arent just beliefs they guide the decisions we make every day to do whats best for our clients communities and more than 80000 employees in 1200 offices across 42 countries. At Morgan Stanley youll find an opportunity to work alongside the best and the brightest in an environment where you are supported and empowered. Our teams are relentless collaborators and creative thinkers fueled by their diverse backgrounds and experiences. We are proud to support our employees and their families at every point along their work-life journey offering some of the most attractive and comprehensive employee benefits and perks in the industry. Theres also ample opportunity to move about the business for those who show passion and grit in their work.

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Morgan Stanley is an equal opportunity employer committed to building and maintaining a workforce that is diverse in experience and background. Our recruiting efforts reflect our strong commitment to a culture of inclusion where individuals are hired developed and advanced based on their skills and talents.

Our workforce reflects a broad cross-section of the global communities in which we operate bringing a variety of backgrounds talents perspectives and experiences.

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