Description
Summary:
The AI Product Manager sets product strategy and drives the planning, prioritization, and delivery of AI and data-enabled products that advance Commercial Banking's AI transformation agenda. This role owns the product strategy and plan for one or more priority AI domains across the commercial client lifecycle (e.g., client service, credit, capital markets, treasury management, and sales) end-to-end - from opportunity assessment and problem definition through business case, build, governance, launch, and measured adoption - partnering closely with engineering, data science, segment risk, compliance, the Commercial Digital product team, and the central Enterprise Data & AI Strategy and Technology Innovation functions. The AI Product Manager is accountable for translating Commercial Banking's highest-value opportunities into a clear product vision and an executable roadmap, integrated with existing digital channels, that delivers measurable value to customers and colleagues.
Duties and Responsibilities:
Define and own the product strategy for assigned Commercial Banking domains (e.g., client service, credit, capital markets, treasury management, and sales): a clear point of view on where AI creates differentiated value for clients and colleagues, which problems to solve first, and what not to pursue.
Shape a multi-year product vision grounded in client and colleague needs, market and competitive insight, and emerging AI capabilities, and translate it into outcome-based goals (e.g., OKRs) and a prioritized roadmap.
Assess build, buy, partner, and enterprise-platform reuse options, recommending trade-offs that balance value, speed to market, risk, and cost, and revisit the strategy as results, technology, and business priorities evolve.
Own end-to-end accountability for the broader product plan, stakeholder messaging, and investment case for assigned AI initiatives - not just the backlog or delivery schedule.
Build and defend the business case (cost, benefit, PPNR/revenue impact, and risk) required to secure and sustain funding through Huntington's AI governance and prioritization process.
Serve as the credible, single point of accountability that segment leaders, technology partners, and executive sponsors can turn to for status, trade-offs, and outcomes.
Lead with user value: define the colleague or client benefit and the problem to be solved before selecting a capability, model, or vendor.
Use design thinking and direct engagement with relationship managers, service teams, and customers to validate needs, pain points, and workflow @context before scoping solutions.
Translate validated needs into clear product requirements and acceptance criteria for cross-functional delivery teams.
Maintain one integrated view across initiatives, segments, data readiness, cross-functional dependencies, and adoption.
Partner across Commercial, Regional Banking, Payments, Wealth, Insurance, Ops, Risk, and Technology Innovation to align priorities, sequencing, and shared data foundations.
Maintain a current, transparent roadmap and dependency map that leadership can use to make sequencing and resourcing decisions.
Partner closely with the Commercial Digital product team to integrate AI capabilities into existing client- and colleague-facing digital channels and platforms, rather than building standalone experiences.
Align AI product roadmaps with Commercial Digital roadmaps and release plans, jointly planning dependencies, sequencing, and shared capacity so AI features ship as part of the broader digital experience.
Establish shared intake, prioritization, design standards, and success metrics with Commercial Digital product owners to deliver consistent client and colleague experiences and avoid duplicative investment.
Define success before launch: establish baselines, target metrics, business outcomes, and attribution methodology in partnership with Finance and Analytics before development begins.
Ensure measurement goes beyond usage counts to tie adoption to real business outcomes - revenue, banker productivity, customer experience, and risk/quality.
Report progress against the defined baseline and value case throughout the product lifecycle, adjusting scope when tracking falls short of plan.
Build within workflows and channels: design and deliver capabilities that meet colleagues and clients where they already work and bank, including existing CRM, servicing, and digital channels, rather than requiring new tools or habits.
Partner with HR, segment leaders, and change management to build role-specific training, manager reinforcement, and adoption reporting for each launch.
Continuously gather adoption and quality feedback post-launch and iterate on the product to close usage and value gaps.
Move from roadmap to execution: convert prioritized concepts into resourced, sequenced delivery plans with clear owners, milestones, and go-live dates.
Serve as product manager for one or more cross-functional pods (engineers, data scientists, analysts), prioritizing the backlog and ensuring iterative, quality delivery each sprint/quarter.
Navigate Huntington's AI governance lifecycle (business value definition, solution assessment, governance/risk review, contracting, and implementation) to keep initiatives on track and in compliance.
Basic Qualifications:
Bachelor's degree in Business, Finance, Computer Science, Data/Analytics, or a related field
7+ years of product management experience, including direct ownership of AI, machine learning, or data-driven products from concept through launch.
Preferred Qualifications:
Experience working in an Agile/Scrum delivery model as a product owner or product manager for a cross-functional team of engineers, data scientists, and analysts.
Demonstrated experience defining product strategy and vision, building and managing a product roadmap, writing business requirements, and defining measurable success criteria (KPIs, OKRs, or equivalent).
Experience in commercial banking, corporate banking, or another regulated financial services environment, including familiarity with credit, treasury, or relationship-management workflows.
Experience with generative AI/agentic AI products, CRM platforms (e.g., Salesforce, including Financial Services Cloud), and enterprise data platforms.
Experience integrating AI or data-driven capabilities into existing digital banking channels and platforms in partnership with digital product, design, and engineering teams
Familiarity with model risk management, AI governance, and regulatory considerations (e.g., fair lending, data privacy) within banking.
Track record partnering with Risk, Compliance, Legal, and Finance to move AI initiatives through formal governance and funding approval processes.
Strong executive communication skills, with experience presenting business cases, roadmaps, and value narratives to senior leadership and steering committees.
LI-DS23
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Exempt Status: (Yes = not eligible for overtime pay) (No = eligible for overtime pay)
Yes
Workplace Type:
Office
Our Approach to Office Workplace Type
Certain positions outside our branch network may be eligible for a flexible work arrangement. We're combining the best of both worlds: in-office and work from home. Our approach enables our teams to deepen connections, maintain a strong community, and do their best work. Remote roles will also have the opportunity to come together in our offices for moments that matter. Specific work arrangements will be provided by the hiring team.
Huntington is an Equal Opportunity Employer.
Tobacco-Free Hiring Practice: Visit Huntington's Career Web Site for more details.
Note to Agency Recruiters: Huntington Bank will not pay a fee for any placement resulting from the receipt of an unsolicited resume. All unsolicited resumes sent to any Huntington Bank colleagues, directly or indirectly, will be considered Huntington Bank property. Recruiting agencies must have a valid, written and fully executed Master Service Agreement and Statement of Work for consideration.
