How to navigate the uninvited participant in your next client meeting.

I was working with a client I’ve known for over fifteen years when they casually mentioned that they had asked ChatGPT to review the website design I’d recently delivered. To be clear, we have a strong relationship, and I don’t think there was anything malicious behind it. If anything, the exercise seemed more exploratory than evaluative. Still, for a brief moment, I felt oddly insulted. After all, I’ve spent decades developing expertise in design, and now I found myself discussing my work alongside the opinions of a machine that learned many of its design principles by consuming the very internet that web creators and designers like me helped build.

The feedback itself wasn’t terrible. Some of the points were reasonable. Others, in my opinion, would have created new problems while solving old ones. During our discussion, I acknowledged the useful observations, explained where I disagreed, and offered alternative solutions. Ultimately, the client went with my recommendations.

But this was not the first time it happened.

In fact, several other clients have used AI in some capacity to either evaluate work I had produced or generate suggestions. The first few times it caught me off guard. Not because I was surprised it happened, but because I was surprised I hadn’t anticipated it sooner. The moment you stop and think about it, the behavior is almost inevitable. If clients now have access to a tool that can instantly produce a second opinion, why wouldn’t they use it?

For designers, this creates a strange new reality. It is already difficult enough trying to determine how AI fits into our own workflows. We are still figuring out when to trust it, when to ignore it, and where it genuinely adds value. Now we must also navigate clients and stakeholders using those same tools, often with significantly different levels of understanding about how the systems actually work. In many cases, the conversation is no longer between a designer and a client. It is between a designer, a client, and a machine sitting invisibly in the corner offering unsolicited commentary.

Oddly enough, AI-generated design feedback itself is not particularly controversial. Many designers already integrate AI into their workflows to critique layouts, evaluate accessibility, identify usability concerns, or brainstorm alternatives. I even use it in the classroom. Some of my assignments have my students use guided prompting exercises to receive feedback on certain projects. When the prompts are carefully structured and the objectives are clear, AI can be remarkably useful at surfacing issues that a designer might overlook.

The difference is that those situations are controlled. The designer understands the limitations of the tool and the prompts are intentional. The feedback is filtered through experience and context.

Client use of AI is a different animal entirely. Anyone who has worked in design knows that managing the client relationship is often as challenging as the design work itself. Good designers spend an enormous amount of time translating expertise into language that non-designers can understand. We explain tradeoffs, justify decisions, balance business goals, user needs, technical constraints, and aesthetics. AI now inserts itself directly into that process, often presenting its recommendations with the same confidence regardless of whether they are insightful, superficial, or completely wrong.

The real challenge is not that clients will receive bad feedback. The challenge is that they may receive plausible feedback. Bad advice is easy to dismiss. Plausible advice is far more dangerous because it requires analysis. Every suggestion becomes another conversation and every recommendation becomes another decision to unpack. The designer is no longer just defending design choices — they are increasingly being asked to defend them against an endlessly available synthetic consultant that works for free and never sleeps.

The irony is that this development may ultimately make expertise more important rather than less. When everyone has access to infinite suggestions, we find ourselves living out a modern spin on the attention economy — where data is infinite, but the scarce resource becomes human judgment. AI can generate observations, identify patterns, and even produce surprisingly competent critiques. What it cannot do particularly well is determine which observations matter most within a specific business, audience, budget, timeline, or organizational context. And at the end of the day, someone still has to decide.

So how should designers respond?

• First, don’t take it personally. Clients are not necessarily questioning your expertise — most are simply using the tools available to them. Seeking a second opinion from AI is rapidly becoming as normal as searching Google or reading online reviews.
• Second, ask to see the prompts and feedback. Understanding what the AI was told often reveals why it produced certain recommendations. The quality of the output is usually a reflection of the quality of the input.
• Third, treat AI feedback the same way you would treat feedback from any stakeholder. Evaluate the idea itself rather than its source. Some suggestions will be useful. Others will be irrelevant. Most will fall somewhere in between.
• Finally, recognize that part of the designer’s role is evolving. Increasingly, we are not just creating solutions. As the industry shifts, professional creative roles are moving away from pure production and toward high-level curation. We are interpreting, contextualizing, and filtering an overwhelming amount of information generated by both humans and machines. The designer is becoming less of a producer and more of a translator between competing perspectives.

Perhaps this is simply the next stage of the profession. Many designers are worried that AI would replace them altogether. Instead, we may discover that our new challenge is something far stranger — managing clients and stakeholders who have acquired a tireless digital design intern with unlimited confidence and no accountability. The machine now has a permanent seat at the table. The question is not whether it belongs there. The question is whether we can learn to conduct the meeting while it keeps whispering in everyone’s ear.

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AI has become the third wheel was originally published in UX Collective on Medium, where people are continuing the conversation by highlighting and responding to this story.