AI Is Changing User Experience Faster Than It’s Changing Technology

For the past few years, the AI conversation has centred on what the technology can do.

Models have become faster, cheaper and more capable. They can write code, analyse documents, generate images and complete tasks that would have seemed impossible only a few years ago. For founders, it has opened up opportunities to build products at a speed that would once have required significantly larger teams.

As those capabilities become more widely available, however, they become less distinctive. Access to powerful AI is no longer reserved for the biggest technology companies. Increasingly, startups are building on the same foundation models, using the same APIs and solving similar technical challenges.

That shifts the focus elsewhere. If the technology is becoming more accessible, the way people interact with it starts to matter much more.

In the latest episode of Nothing Ventured, a podcast led by our founder and CEO Aarish Shah, we featured incredibly talented Milena Nikolic, co-founder of Heywa Labs and former Senior Engineering Director at Google, to talk about how AI is changing user experience faster than the technology itself, and what that means for founders building the next generation of products.

Why are AI products starting to feel so similar?

Spend a few minutes trying different AI products and you’ll notice how quickly they begin to blur together.

Most start with an empty text box and expect the user to know exactly what they want. If the first response isn’t quite right, the solution is usually to write a better prompt, provide more context or ask a more specific question.

For some tasks, that’s perfectly reasonable. If you’re asking AI to summarise a report or write a piece of code, you probably know what success looks like before you begin.

Many decisions don’t work that way.

Imagine you’re looking for a family holiday. You may know your budget, but you’re flexible on the destination. You might prefer somewhere warm, but you also want direct flights, activities for children and somewhere you haven’t visited before. Those preferences develop as you explore the options. They aren’t fixed at the start of the process.

The same applies when you’re choosing accounting software, hiring a senior employee or deciding whether to expand into a new market. The right answer often becomes clearer as you gather more information.

People rarely arrive with a perfectly formed prompt. They work things out as they go.

The next challenge is helping people decide

This is where user experience becomes far more interesting than the underlying technology.

An AI model might already be capable of answering complex questions, but that doesn’t automatically create a good product. A good product helps users reach a decision with less effort than they would have needed on their own.

That doesn’t always mean generating a better response. Sometimes it means asking the right question at the right moment. Sometimes it means presenting options visually instead of through another paragraph of text. Sometimes it means recognising that a person’s priorities have changed halfway through the process and adapting accordingly.

The technology required to do those things is already improving rapidly. The bigger opportunity lies in designing experiences that feel intuitive rather than transactional.

Why founders should pay attention

It’s easy to become distracted by the pace of AI development.

Every new release promises better reasoning, lower costs or another leap in performance. Those improvements are valuable, but they are also becoming expected.

Customers rarely choose a product because it uses a particular model. They choose it because it solves a problem in a way that feels simple, reliable and worth coming back to.

That changes where founders should invest their attention.

Technical capability will always matter, but understanding customer behaviour is becoming just as important. Where do users hesitate? What information do they struggle to provide? Which decisions take longer than they should? Those are user experience problems, and solving them often creates far more value than adding another AI feature.

The same thinking applies beyond the product

The conversation around AI often focuses on customer-facing applications, but the same principles apply inside a business.

Finance teams now have access to tools that can automate reporting, accelerate forecasting and reduce hours of manual work. Those developments make the function more efficient, but they don’t remove the decisions that sit behind the numbers.

A forecast is only useful if it helps a founder decide whether to hire, raise funding or slow spending. Cash flow projections still need to be interpreted in the context of investor expectations, commercial priorities and the reality of running a growing business.

In other words, better technology doesn’t eliminate judgement. It creates more opportunities to apply it where it matters most.

As AI continues to evolve, the businesses that stand out are unlikely to be the ones with access to technology that nobody else can use. More often, they’ll be the ones that understand how people make decisions, remove unnecessary friction from that process and build products that feel genuinely useful from the first interaction onwards.

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