I'm Jess Kessin. I create cultures where designers are happy, bold, and unafraid to try the unexpected — in the sectors where the problems have never been bigger and the outcomes have never mattered more. As AI reshapes how we build products, I bring a design-led perspective to responsible innovation. My through-line across all of it: I use design to create a better, more equitable, and inclusive future.
AI is transforming how banks make decisions that affect millions of people's financial lives. But the data these systems are trained on carries the biases of the world that created it — decades of lending discrimination, demographic gaps, and patterns that systematically disadvantage the people who need fair access most.
The question isn't whether to use AI in financial services. It's who's in the room when we decide how. Design has a critical role here: making the invisible visible, advocating for the people on the other end of every automated decision, and ensuring that efficiency never comes at the cost of equity.
AI can generate interfaces, write code, and prototype faster than any team. But speed isn't the hard part of product development — empathy is. Understanding what people actually need, not just what uninterpreted data says they want. As AI takes on more of the building, designers need to step into the work that matters most: deeply understanding users, framing the right problems, and making sure we're solving the ones that actually need solving. AI doesn't make designers obsolete. It makes human-centered design more important than it's ever been.
Every dataset carries the fingerprints of the world that created it — decades of discrimination, demographic gaps, and systemic inequity baked into the numbers. When we train AI on that history, we don't just repeat those patterns. We automate them, at a speed and scale that human decision-making never could. The potential for bias isn't smaller with AI. It's massively larger. And the people most affected are the ones who were already being underserved.
This is why trusted governance isn't a nice-to-have — it's urgent. Organizations need clear accountability for how AI systems are built, trained, and deployed. They need diverse voices at the table, not just in the engineering room but in the boardroom. They need transparency about what their models are doing and the courage to slow down when the data isn't fair. Design, diverse teams, rigorous oversight, and constant vigilance aren't optional — they're the only way to make sure we're building a future that's better than the past we're training on.
I teach at Stanford Graduate School of Business and the d.school, and recently taught at San José State. I teach Customer Experience Design to MBAs, Design Thinking and Organizational Alignment to executives, and Design for All to undergraduates — classes built on what I've actually done, not what I've read about. Teaching is where 25 years of practice turns into something that outlasts any single role.
Talks, podcasts, and writing on design leadership — how to build the teams, shift the culture, and do work that lasts.