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A model that's starting to feel its age

Most digital interfaces still follow a structure that was designed for a different era. Static pages with fixed navigation, search bars that return a list of links and leave you to figure it out, and forms that ask you to provide information the system probably already has. It works, but it’s not exactly meeting people where they are anymore.

Users increasingly expect experiences that feel more responsive, more personal, and more aware of context. They don’t necessarily want to click through twelve pages to find an answer, and they’d rather not re-enter information they’ve already provided. AI makes a different kind of experience possible, but there’s an important distinction between what’s technically possible and what’s actually well-designed.

The shift in expectations is already visible. Someone who’s used ChatGPT to plan a trip now finds a keyword-based site search frustrating. A customer who handles banking and insurance through KBC’s Kate doesn’t want to go back to a static FAQ page. The bar moved. And when Google rushed out AI Overviews in Search, it was because ten blue links stopped being enough. People don’t compare your interface to your competitor’s. They compare it to the last time an AI actually understood what they needed.

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Three shifts that are worth paying attention to

From search to conversation. Traditional search assumes users know what they're looking for and can translate that into the right keywords. Conversational interfaces take a different approach. Users can describe what they need in their own words, and the system does the heavy lifting. When it's done thoughtfully, this can genuinely reduce friction. But when it's implemented without enough care for dialogue design, error handling, and edge cases, it can actually create more frustration than the search bar it replaced.

From forms to contextual intelligence. Every field in a form is essentially a question you're asking someone to answer. AI can reduce that burden by using context, history, and behavioural signals to prefill information, suggest answers, or skip steps entirely. A returning visitor probably shouldn't have to re-enter their address. The point isn't to collect less information, it's to stop asking people for things you already know.

From navigation to guidance. Static navigation works well when users already know where they want to go. But AI-powered interfaces can adapt in real time, surfacing relevant content based on what someone is actually doing, adjusting the experience to their needs, and helping them find what they're looking for without requiring them to understand your site structure. It's a bit like the difference between giving someone a map and walking with them.

The design challenge is getting harder, not easier

It might seem like AI would reduce the amount of design work needed. Fewer pages, fewer fixed layouts, more automation. But in practice, the opposite is true. Conversational interfaces need careful dialogue design, good error handling, and clear signals that help users understand what they're interacting with. Adaptive layouts need robust logic and thorough accessibility testing. AI-generated content calls for editorial standards and transparency about what's automated and what isn't.

Design isn't becoming less important in this shift. If anything, they're becoming more essential, because many of the patterns for trust, control, and transparency in AI-powered interfaces haven't been established yet. We're all figuring this out together.

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Adding AI without a clear direction

It’s tempting to start from the technology. AI is moving fast, and the pressure to ship something is real. We’ve been there too. But when AI gets added without research or a clear picture of the problem it’s supposed to solve, the results disappoint.

Not because the technology doesn’t work. It usually does. But because it’s solving the wrong problem, or solving the right one in a place where nobody was looking for help. A strong experience gets stronger with AI. But if the foundation is shaky, AI just makes the cracks more visible.

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Starting from the customer experience

The organisations that seem to get this right tend to share a common approach: they start from the customer experience rather than from the technology. They take the time to map the journey, identify where people are running into friction, and then ask honestly whether AI could help in those specific places. Sometimes it can, and sometimes a simpler solution turns out to be the better answer.

Answering that honestly about your own organisation is the harder part, and worth a structured read: where your organisation stands with AI across strategy, data, customer experience, and team.

That's how we think about it at Leap Forward. AI is a genuinely powerful tool, but it works best when it's in service of a clear understanding of what people need. Technology follows strategy, not the other way around.

designer

Author

Creative Lead

Jan Van Lysebettens

Jan is an experienced senior designer and developer who’s really passionate about creating beautiful designs and turning them into fully functional digital experiences. He combines a strong sense for aesthetics with an analytical approach to turn a client’s vision into meaningful digital products.

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