Design Leadership in the Age of AI

A few years ago, most design conversations I had with teams were about craft. Layouts, grids, typography, handoff. Today, a lot of that work is supported by systems and AI powered tools. Component libraries, design tokens, and AI assisted layouts take care of many decisions that used to be manual.

That shift has not made design leadership less relevant. It has simply moved the center of gravity. When more of the execution is supported by AI and standardized systems, design leaders are asked for something different: clearer direction, stronger framing of problems, and a consistent way of keeping user experience visible while the work speeds up around it.

AI changes what we do with our time. It does not change the need for leadership.

What Changed for Design Teams

Many teams now work on top of mature design systems, with AI sitting on top of them as an extra layer. The question is less “how do we design this button” and more “why does this flow exist at all, and does it line up with everything else we are doing.”

AI has entered the picture in practical ways. It can suggest interface variations, help with microcopy, or propose ways to structure content. Used well, that gives teams more space to think. Used carelessly, it can turn into noise.

The requests that reach a design leader’s desk reflect this. They sound like:

• we have three directions that all look good, which one fits our product story
• how do we keep quality stable when everyone can ship faster
• is this work solving something real for users, or just rearranging screens

Those are questions about context, not only about craft.

From Supervising Outputs to Shaping Direction

When tools and AI handle more of the repetitive detail, leaders have an opportunity to work further upstream. Instead of correcting screens at the end, we can spend more time clarifying what a team is actually trying to change.

In practice, that often means:

• turning vague requests into clear design problems
• connecting research findings with design choices
• making trade offs explicit, so they are made consciously
• aligning flows with the rest of the product, instead of creating exceptions

A design system or an AI plugin can produce options. Someone still needs to say what “good” looks like in the current context. That is where design leadership earns its place.

Working with AI Without Losing the User

AI already touches many parts of design work. It can speed up exploration, help rewrite copy, or surface patterns in feedback. The risk is that it starts to feel authoritative rather than supportive.

I see leadership here as setting a few simple rules of engagement. For example:

• AI is useful for quick variations and early thinking
• real user behaviour has more weight than synthetic assumptions
• every AI output should be checked against what we know from research

At Useberry, this is also how we think about testing and analysis. AI can help summarize and organize, but it does not replace watching participants move through a flow or listening to how they describe their experience. As leaders, we can model that balance for our teams.

Keeping Users at the Center While Work Speeds Up

AI and automation usually come with speed. Teams can now move from idea to implementation much faster than before. That is positive, as long as velocity does not drift too far from real users.

One of the most practical things a design leader can do is tie speed to simple validation habits. For example:

• checking key flows with a short unmoderated test
• running a quick five second test on a high stakes screen
• watching a handful of recordings together before calling something done

Tools like Useberry make that rhythm easier to maintain. It becomes natural to upload a prototype, recruit a few participants, and review results without breaking the pace of the sprint. The point is not to slow teams down. It is to keep their direction in touch with reality.

Designing the Conditions, Not Only the Screens

As more of the execution layer is supported by systems and AI, a growing part of design leadership is about shaping how the team works around those tools.

That might include:

• deciding how design and research collaborate
• choosing which UX tools become part of the shared stack
• making space for junior designers to learn craft in a world where some steps are automated
• setting up simple rituals, such as weekly reviews of highlight reels or regular critiques

Most of this does not show up in a portfolio. It shows up in fewer surprises, better alignment, and a shared understanding of what “good experience” means for your product.

Skills to Lean on in 2026

The fundamentals have not gone anywhere. Clear thinking, a good eye, and the ability to give useful feedback still matter. AI has simply made some skills more visible:

• problem framing, so teams do not rush into solutions
• research fluency, so decisions link back to what users actually do and say
• facilitation, so cross functional conversations stay focused and constructive
• decision hygiene, so important choices are recorded and can be revisited

These are not skills any tool can take over. They sit above the tools and make them effective.

Leading Design in an AI Driven World

AI will keep moving into our work. More of what we used to do by hand will be assisted, and sometimes performed, by the systems we use. That is not something to resist. It is something to steer.

Design leadership in this environment is less about being the best individual contributor and more about setting direction, maintaining standards, and keeping users present in every conversation.

The tools will keep changing. The need for someone to connect them to real people, real problems, and real outcomes will not.