Let’s be clear: I don’t think that the UK is facing an AI bubble, but what we are seeing right now could be described as a general “lack of innovation.” Many projects are focusing on using artificial intelligence in generic ways instead of applying it to solve meaningful or novel problems. The report I mentioned above suggests that over 80% of companies are doing exactly that.

This is a common hallmark of AI washing – when startups slap the AI label onto projects with little thought as to whether it actually adds tangible value to the public. So what can be done to address this problem?

Avoid thinking too short-term

One of the main reasons for the disconnect we’re seeing between funding and real-world impact is short-term planning. Many startups prioritise speed over quality – get something out, raise the next round, rinse and repeat. But this approach skips a crucial step: identifying the problem worth solving in the first place.

When an AI company starts with the tech and tries to force a use case around, it won’t get very far. Some pilot customers, perhaps, but not something that will endure in the long run. A product without a clear purpose won’t find lasting users.

And if users won’t stick around, revenue won’t grow, which leads to a different problem. Namely, the fact that far too many startups chase after what’s “popular” in the moment, ultimately burning through capital with nothing to show for it.

Strategy first: a problem-first approach to building AI startups

So how can founders reverse this trend? The way I see it, it starts with a mindset shift – from solution-first to problem-first. Here are a few practical ideas which, in my opinion, founders can apply from day one:

Start by defining real pain points. Before you go building any solutions, look at your target market and identify what issue your product is going to address. This isn’t just a formality – it’s the compass that will guide everything else you do from this point onwards.

Talk to your users early and often. Direct conversations with your target audience will reveal insights you won’t find in reports. There is nothing quite so vital for refining your approach as feedback from the people who will be ultimately using what you come up with.

Don’t fear niche markets. Some might fear “thinking too small,” but solving a specific problem for a smaller audience often creates a stronger product-market fit than chasing solutions that try to cater to everyone, only to end up being generic and shallow. Niche doesn’t have to mean small – it simply means “focused”.

Be ready to evolve. Your understanding of the problem will grow as your product develops. That’s only natural. Embrace it and expect that your roadmap will go through more than a few iterations. Once again, customer feedback is going to be a powerful guiding force here, even if it means that your original ideas will need to be reconsidered in new ways.

Keep checking your focus. Regularly ask yourself: is this feature/update/etc. going to help us solve the core problem we’re aiming at? If not, it’s likely a distraction, and you don’t need to waste time and resources on it.

Why this approach works

There are three strong reasons why I believe building around real problems is critical to business success:

• Stronger demand: products built to solve real, identifiable issues naturally generate higher user interest. People want solutions to their problems. It’s that simple. Solve those problems – get a loyal following
• Investor confidence: in a tighter funding environment, investors want to see well-defined use cases and a clear route to profitability. Vague ideas and being simply enthusiastic about “innovation” aren’t going to cut it. A problem-first approach, on the other hand, shows you’ve done the groundwork and can be taken seriously
• Smarter resource use: when you know what you’re solving, it becomes that much easier to focus time, effort, and money where they need to go, rather than bells and whistles no one is going to need. You can deploy an MVP faster, test quickly, and scale what you know is working for certain

In today’s AI landscape, purpose is the real differentiator. Founders should aim to build with intent, even if it means stepping away from oversaturated markets and exploring underserved areas. Very often, that’s exactly where thoughtful, long-term AI solutions can make a real difference.

Projects that understand this and build accordingly won’t just survive the hype cycle – they’ll lead the next wave of meaningful innovation.

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