How I'm using AI to keep my team focussed on what matters

"Creativity is driven by spikiness—the unique, out-of-the-box ideas that often come from human intuition and insight. AI can enhance this process, but it cannot replace the creative spark that defines human innovation." ~ Tim Brown

There's a version of this post where I tell you AI is going to replace designers. Or any other role for that matter. Where this would lead, whether humans are left only interacting with versions of AI rather than other humans, may be a dark spiral we can investigate later (dead internet theory?).

There's another version of this post where I dismiss it as hype and tell you nothing has really changed.

The reality is somewhere more interesting, and hopefully more practical. Over the past year, I've been deliberately integrating AI into how my team works day-to-day, not to cut corners, but to protect something I care about deeply: my team's time and headspace for strategic thinking. I'd be lying if I said it was all figured out, or that we have reached any form of final opportunities.

But for now, here's what that's actually looked like.

The problem I was trying to solve

"Do more with less," has become the defining statement of the last few years. An age of efficiency and shrinking margins.

In a fast-paced retail environment, the pace of questions doesn't slow down to match the pace of good design. We're often asked to validate decisions that have already been made, respond to briefs that needed answering yesterday, or produce concepts before all stakeholder conversations have happened.

The traditional UX toolkit - weeks of research, careful synthesis, deliberate concepting - is still right. The principles haven't changed. But the timeline expectations have, and I needed my team to be able to operate at that speed without sacrificing the quality of thinking.

That's where AI has genuinely helped.

What we're actually doing

Research at the speed of the question

I often joke I'm being asked to answer question before they'e asked. But it's pretty much true.

We've adopted a research platform that can conduct hundreds of interviews in hours, not weeks. Askable's Insight Stream has been a hit with the team and stakeholders alike. For the kinds of questions that come up constantly - "how do customers feel about this?" or "what do customers find value in here?" - we can now have qualitative insights at scale of quantitative studies.

This doesn't replace deep qual or quant work, but it means we're rarely flying blind, and we're not the bottleneck when leadership needs a read on something quickly.

Eventually, we'll have enough data sets here to query it back and answer new questions from existing data.

Concepting from our design library in seconds

We've built a solid design library over the years - components, patterns, tokens, the whole thing. We're now using that as the foundation for Figma Make to generate early concepts at a pace that would have taken days before.

While Make still isn't hitting it on the head immediately, the impact can be significant in the right rooms: it's much easier to have a strategic conversation about direction when you have something on screen. We can get to alignment faster, and with more shared understanding across teams of varying knowledge foundations.

Synthesis without the manual labour

Workshop outputs, research notes, sticky walls of observations - we've all been there. I remember spending days on this in the past for significant pieces of research. At the least, they represent hours of careful manual sorting. We're now using AI-powered whiteboard tools to arrange and theme data in a fraction of the time. The insights and communication still requires a human. The organisation and distillation doesn't have to.

Investing in the team's own capability

We've also been working through structured learning on how to use AI tools effectively, including how to use them to tell better stories about our own work. Portfolio development, case study writing, presenting our impact, these are skills that matter for any designer's career and team's influence, and AI can genuinely help you do them better if you know how to use it.

What this makes possible

I want my team focused on real strategic value - the kind of work that genuinely shapes product direction, builds organisational capability, and delivers outcomes for customers. Not drawing squares. Not reformatting decks. Not doing manually what a tool can do better and faster.

The time we've reclaimed from repetitive tasks has gone back into the work that actually requires UX expertise: framing the right problem, building stakeholder alignment, designing for edge cases, advocating for the customer in rooms where they're not represented.

That's the trade I'm making. AI handles the scaffolding. My team handles the thinking.

What hasn't changed

Here's the part I want to be clear about, especially for teams just starting this journey: the foundations still matter.

AI amplifies what's already there. If your information architecture is poor, if your content strategy is shaky, if your design system is inconsistent, AI will produce faster versions of those problems. The discipline of good UX practice doesn't go away because the tools have changed.

There's also a newer consideration worth naming: as AI-driven answers (AEO - answer or agent engine optimisation) increasingly shape how people find information, the same principles that made good SEO and good IA important are becoming even more critical. Structured, semantic, well-organised content isn't just good practice, it's table stakes for being discoverable in an AI-first world. I will have more to say on this in another post.

The principles haven't changed. The stakes for getting them right have gone up.

Where this is heading

I'm genuinely optimistic about what this means for UX as a discipline. The things AI can't do (empathy, judgment, facilitation, influence, system-level thinking) are exactly the things that make great UX leaders valuable. If anything, this moment is clarifying what design leadership actually is.

The teams that will thrive are the ones that invest in both: the AI capability to move fast, and the human capability to think well. I'm building for both.

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