AI Strategy & Transformation Lead, Commercial Banking

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

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

Reports to Global Head, Consulting at Brillio

Role Purpose

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.

Key Responsibilities

AI Strategy

• 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
• 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
• 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

Cross-Functional Influence and Stakeholder Management

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

Team Building

• Define the roles, skills, and org structure for a new AI product management and strategy function from scratch
• Recruit, hire, and stand up a team of AI product managers and AI strategists
• Build the operating model for how that team engages with business lines: intake process, prioritization, delivery partnership with technology
• 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

Change Management

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

Required Experience

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

What Success Looks Like in Year One

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