AI-Augmented UX
Using AI to accelerate design thinking — without abandoning design fundamentals
In 2025, the rapid emergence of generative AI tools began reshaping how product teams approached design work. As these tools gained traction across the organization, my goal was not simply to adopt them, but to help our team use them responsibly and effectively.
I led the introduction of AI-augmented workflows across 9 designers and 2 researchers supporting 21 product teams across three portfolios (Pricing, Store Merchandising, and Merchandise Execution).
Rather than treating AI as a replacement for UX, we framed it as a capability multiplier: a way to move faster through the design process while preserving the critical thinking, critique, and empathy that only trained designers bring to the work.
Building Responsible AI Adoption
Adoption happened quickly. Following announcements around Figma Make in spring 2025, our team began experimenting with generative AI tools to support the UX workflow. By summer we were running internal trainings, and by November I hosted a UX Summit focused on responsible AI adoption and practical applications.
To support this transition, I:
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created workflow documentation to guide AI-assisted work
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encouraged AI experimentation across ChatGPT, Figma Make, FigJam AI, and Windsurf
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led internal training sessions on design fundamentals to ensure the team’s craft remained strong
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extended these sessions to PMs and engineers, reinforcing a shared understanding of the UX process
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encouraged designers to explore additional tools outside the organization and share learnings
This helped ensure that while AI accelerated certain tasks, the discipline of UX remained intact.
AI Across the UX Workflow
AI tools can support nearly every stage of the UX process — but they should augment, not replace, the work of trained designers.
I created the visual below to show our team how to explore AI capabilities across the UX workflow while supporting the end-to-end process we had already established on our teams.
Research
AI can accelerate synthesis of interviews and documentation.
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Summarize interviews and identify recurring themes
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Generate survey questions or discussion prompts
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Maintain “living personas” based on prior research
However, AI cannot replace human research. It cannot build trust with participants, interpret emotional nuance, or identify subtle signals during interviews.
Discovery
Once a problem space is understood, AI helps surface gaps in knowledge and possible directions.
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identify missing research questions
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generate hypothesis lists
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draft problem framing or survey questions
This stage benefits most when UX and Product collaborate together with AI.
Lo-Fi Exploration
Tools like Figma Make enabled rapid concept generation.
Designers and PMs could co-prompt layouts and interaction patterns during wirestorming sessions, exploring many possibilities quickly before selecting a direction to refine.
This dramatically accelerated early ideation while keeping designers in control of decision-making.
Validation
AI can assist in preparing and analyzing validation activities.
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draft validation questions
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run synthetic testing to expose obvious usability issues
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summarize findings
Synthetic testing helps identify early issues but never replaces testing with real users.
Hi-Fi Design & Prototyping
Within Figma, AI features supported rapid refinement.
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generate UI variants
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assist with layout adjustments
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convert designs into interactive prototypes more quickly
Guardrails: Protecting Design Fundamentals
While AI can accelerate design work, it cannot replace the critical thinking and critique that define strong UX practice.
One challenge with generative AI is that it cannot critique itself effectively.
Design quality still depends on humans who understand:
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design principles
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interaction patterns
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usability heuristics
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visual hierarchy
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accessibility
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human behavior
To reinforce this foundation, I created a series of short design fundamentals refreshers for the team covering topics such as:
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color theory
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the value of low-fidelity exploration
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design principles and critique
These sessions ensured that AI enhanced our process rather than weakening the craft behind it.
Reflection
AI is changing how product teams work, but it does not eliminate the need for design.
What it does is remove some of the friction around exploration and documentation, allowing designers to focus more energy on the parts of the process that matter most: understanding people, framing problems, and making thoughtful decisions.
My goal as a leader was to ensure our team embraced these tools without abandoning the fundamentals that make great design possible. AI should open doors for designers — not close them.
Are you looking for a leader to help your team embrace AI without losing sight of what matters?