AI Strategy & Transformation Lead, Commercial Banking

Job Description

Job Title: AI Strategy & Transformation Lead, Commercial Banking (Senior Director level)

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Work with: Executive Sponsor (COO/CTO-equivalent) at leading Commercial bank

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Reports to : Global Head, Consulting at Brillio

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Role Purpose

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This role is the embedded AI strategy partner to a senior banking executive, responsible for defining and driving the organization's AI adoption agenda from the ground up. It is not a delivery role and not a pure strategy role either. It requires someone who can set direction, build the internal case for change, work effectively across a large organization without formal authority over most of the people they need to influence, and then build and lead the team that will execute against that direction.

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Key Responsibilities

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AI Strategy

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• Define the AI strategy and roadmap for the commercial banking technology and business organization, translating executive intent and market pressure into a sequenced set of priorities
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• Identify where AI creates real operating leverage in commercial banking specifically (credit underwriting support, loan operations, treasury servicing, relationship manager tooling, document-heavy compliance processes) versus where it is hype
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• Stay ahead of the market on AI capability, positioning, and competitive movement, and translate that into points of view the executive sponsor can act on
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Cross-Functional Influence and Stakeholder Management

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• Build relationships and credibility across business lines, risk, compliance, and technology leadership to drive AI adoption without relying on direct reporting authority
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• Identify and address organizational resistance to AI initiatives, whether rooted in risk aversion, competing priorities, or unfamiliarity with the technology
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• Manage sensitive stakeholder dynamics discreetly, outside of formal documentation, engaging directly with the individuals and groups involved
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• Anticipate where existing governance, risk, or procurement processes could slow AI initiatives, and engage the relevant owners early to keep momentum
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Team Building

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• Define the roles, skills, and org structure for a new AI product management and strategy function from scratch
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• Recruit, hire, and stand up a team of AI product managers and AI strategists
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• Build the operating model for how that team engages with business lines: intake process, prioritization, delivery partnership with technology
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• Establish career paths and a competency model for AI product roles, since this function likely does not exist yet in a form the organization recognizes
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Change Management

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• Own adoption strategy for AI tools and workflows across affected business functions, including training, communications, and champion networks
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• Build the narrative and materials that make the case for AI adoption to skeptical or risk-averse stakeholders
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• Design and track adoption metrics that go beyond tool usage to actual behavior and workflow change
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Required Experience

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• 15+ years in technology strategy consulting or enterprise technology leadership, including prior experience establishing a new function or capability within a large organization
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• Direct experience in banking or another heavily regulated industry, with working knowledge of how initiatives are evaluated by risk, compliance, and governance functions
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• 3-5+ years of applied experience in AI strategy, product management, or transformation leadership
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• Proven track record building and leading product or strategy teams, not just staffing existing ones
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• Strong organizational influence skills, evidenced by prior roles where the person drove change across teams they did not formally manage
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• Change management experience at an enterprise scale, not just project-level adoption plans
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• Demonstrated ability to operate effectively with significant ambiguity and limited existing infrastructure
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What Success Looks Like in Year One

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• A defined AI strategy and roadmap has executive sponsorship and cross-functional buy-in
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• A core AI product management and strategy team is hired and operating
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• At least one or two AI initiatives have moved from concept to adopted workflow in a live business function
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• The organization has a repeatable process for evaluating and prioritizing new AI opportunities, rather than one-off pilots
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