I have been taking a hybrid approach that blends Design Thinking with the Stingray model to integrate AI intentionally into design. This means balancing empathy and iteration with learning loops that define goals, train with data, and test AI alongside human research.

Though my process has always been been deeply rooted with the design thinking structure: research, discovery, ideation, prototyping, iteration. But with so many AI tools becoming available, the bar of the team’s skill set has increased exponentially. We are constantly navigating how and when to best integrate AI into the design ecosystem, in ways that are intentional and valuable to the design outcome, the business, and the process of design.

Fairly recently the Board of Innovation introduced the Stingray Model to help explain how the landscape of design is changing. I’ve adopted a hybrid approach that lives between the double diamond and the stingray, easing the integration of AI more intentionally into practice. While Design Thinking emphasizes empathy and iterative work but can at times lack financial viability or technological feasibility, Stingray emphasizes learning loops where we define goals, train with the right data, develop parallel explorations, and iterate quickly with AI in the mix. It’s been an interesting mind shift and I strongly believe it’s an evolving space. As a leader, I help navigate uncertainty, keep alignment, and ensure AI is not an afterthought but a core part of how we design.

For this particular project, as a strategic lead I brought clarity by turning ambiguous research and AI signals into sharp problem definitions. I helped set direction to guide the product and team in choosing what to experiment with using AI and what to validate through human research. I also empowered myself and designers to explore AI prototypes and AI research synthesis tools while anchoring the work to user needs and business value.