Design and AI

AI has shifted how I think about design process. With tools that enable faster ideation, research synthesis and competitive analysis, designers are freed up to spend more time on solving complex problems with expert judgment and empathy.

As a design leader, I believe integrating AI well requires more than tools. It requires experimentation, adaptability, and a continued commitment to human-centered design.

Principles

1

Experiment

I believe firsthand experience is essential to understanding what AI can and can't do. I encourage my teams to experiment directly so that their understanding is grounded in reality rather than speculation.

I've taken this approach before. Years ago, while working in news, I joined Twitter so I could internalize how it worked and not rely on the critical opinions of other people, some of whom hadn't used it. Experiencing the 140-character constraint firsthand and engaging in real-time conversations changed how I understood the platform and its potential. That same instinct guides how I approach AI today: learn by doing.

2

Have an adaptive mindset

AI is not the first major shift design has faced, and it won't be the last. Staying relevant requires flexibility and a willingness to evolve.

I began my career in print design. As the industry shifted to digital, I expanded my skills into video, motion graphics, and eventually UX design. Each transition required letting go of familiar workflows and embracing uncertainty. That adaptability now shapes how I think about AI, not as a fixed solution, but as something that will continue to change how people interact with systems, products, and services.

Because we as designers understand systems, context, behavior, and intent, we are uniquely positioned to shape the industry's evolution. We can influence how AI is integrated in ways that serve real human needs.

3

Stay human-centered

With the efficiency that AI may bring design teams, what matters is what designers do with the time saved for customers and businesses.

AI should help us rethink experiences, not flatten them. That means staying grounded in empathy, maintaining strong design instincts, and making responsible, ethical decisions. It also means continuing to strategically tell stories rooted in real customer voices, needs, and data and using AI to support that work, not replace it.

AI is most powerful when it strengthens what designers already do best: making sense of complexity, imagining better futures, and designing with intention.

AI in practice

I've applied AI tools in both professional and personal work. Here are some of the tools I use with my team and for myself as well as some of the use cases.

Some of the tools I've used

  • Cursor
  • Figma Make
  • Perplexity
  • Copilot
  • Claude
  • Notebook LM

Example of ways I've used it

  • Design ideation
  • Competitive analysis
  • Research synthesis
  • Image generation
  • Persona agent creation
  • Website building

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