I established the design standards and governance frameworks for generative AI experiences at a Fortune 100 financial services company — creating guidelines for trustworthy AI, an AI Design Studio, and cross-functional alignment across Legal, Model Risk, UX, and Content stakeholders.
This work is confidential. Below is a summary of scope and impact.
When generative AI started moving from research to product, Capital One faced a challenge that most large companies share: dozens of teams moving fast in different directions, each making independent decisions about how AI should look, feel, and behave — without shared principles, review processes, or quality bars.
In a regulated financial environment, that's not just a design consistency problem. It's a risk problem. Customers interacting with AI features need to understand what they're being told, who they're talking to, and what happens when the model is uncertain. Those aren't nice-to-haves — in fintech, they're table stakes for trust.
My scope was to define what "trustworthy AI" actually means as a design practice, build the infrastructure to make it repeatable, and get Legal, Model Risk, UX, and Content aligned on shared standards they'd actually use — without slowing the organization down.
Built and launched guidelines adopted by product and content teams, establishing a quality baseline for AI-powered experiences.
Founded an AI Design Studio to enable designers across the organization to ship quality GenAI features faster.
Secured buy-in on governance frameworks that balance regulatory compliance with design velocity across multiple lines of business.
Created shared standards for Trustworthy AI experiences by aligning Legal, Model Risk, UX, and Content stakeholders in a highly regulated financial environment.