Insight

What every app owner should know about AI integration

Photo of Courtney Smith

Courtney Smith

digital marketing assistant

6 minutes

time to read

July 1, 2025

published

AI isn’t just for tech giants anymore. It’s no longer locked behind jargon, billion-pound R&D budgets or labs full of scientists. Whether you’re in travel, health, finance or retail, chances are your competitors are already weaving artificial intelligence into their digital products. The question isn’t should you consider AI, it’s how to do it well.

If you’re working with app developers (or are on the hunt for application developers in the UK), knowing how AI fits into the development process could give you a serious edge. But let’s face it, unless you're deep in the tech weeds, a lot of the conversations around AI can feel like alphabet soup.

So here’s your plain-English guide to what really matters when adding AI to your app, from cost to compliance, models to maintenance.

 

1. AI is not a magic wand. Start with the problem, not the tech

AI sounds impressive, but its real value lies in solving specific problems. Before getting excited about integrating AI, take a step back. What problem are you trying to solve?

  • Do users need quicker access to support?
  • Are you manually processing a mountain of admin tasks?
  • Could your app be smarter at surfacing personalised content?

One of the biggest mistakes app owners make is leading with “we want to use AI” without knowing what the goal is. The right app developers will help you work backwards from your objectives and figure out if AI is actually the best way to get there, or if a simpler automation would do the job just as well.

And when AI is the right fit? That’s when things get exciting.

 

2. Cost isn’t just about the build

We won’t sugar-coat it: AI adds complexity. That means time and cost. But not just upfront. The big picture includes:

  • Training time (if you’re using a custom model)
  • Ongoing API usage costs (for tools like OpenAI or Google Cloud AI)
  • Maintenance and updates
  • Storage for data, especially if you’re capturing user behaviour

According to Gartner, businesses will spend nearly $135 billion on AI software globally by 2025. Why? Because when done well, the return outweighs the spend.

The takeaway is to be prepared to invest, but make sure your application developers are clear about the long-term costs as well as the shiny launch-day version.

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3. Not all AI is created equal

When we say “AI”, we’re talking about a range of technologies, from rule-based automation to machine learning, computer vision, and large language models. Picking the right one matters.

If your app needs basic predictions (like suggesting nearby locations or detecting spam), off-the-shelf models are fast and affordable. But if you're trying to do something novel (say, generate travel itineraries based on user preferences), custom models or fine-tuning will be required.

A good app development team won’t just drop in ChatGPT and call it a day. They’ll guide you through model selection based on accuracy, speed, data needs, and cost. And they’ll make sure it fits with your existing infrastructure, not bulldoze it.

 

4. AI needs feeding. And that means data

If AI is the engine, data is the fuel. But here’s the thing most non-tech stakeholders don’t realise: your AI is only as good as the data you give it.

Outdated, biased or poorly structured data will limit what AI can do, or worse, make your app behave in ways you didn’t expect. According to a study, 55% of companies said data issues were the biggest barrier to effective AI adoption.

You don’t need perfect data to start, but you do need a clear plan for collecting, cleaning, and managing it. The best application developers in the UK won’t just build the feature. They’ll help you design your data pipeline so the AI can actually learn and improve over time.

 

5. There are ethical implications, and you can’t ignore them

If your app makes decisions based on user data, say, denying a customer a credit limit, prioritising one job candidate over another, or even just recommending content, it needs to be explainable and fair.

You might not be legally required to implement ethical AI practices yet (although in the UK, that’s changing fast), but you are responsible for the outcomes your app delivers. Transparency, bias mitigation, and user control are becoming essential trust signals.

 

6. Security and compliance aren’t optional

Whenever you bring AI into the mix, you’re also bringing in more complexity to your data flows. And that means more points of vulnerability.

If your AI features rely on third-party tools (which they often do), you need to make sure they comply with GDPR and other local data regulations. Just because an AI service works brilliantly doesn’t mean it’s storing data the right way.

When working with app developers, ask:

  • Where is the data stored?
  • Who can access it?
  • How long is it retained?
  • Are we using anonymisation techniques?

This isn’t a “nice to have”, it’s table stakes. One slip-up and you risk fines, reputational damage, and user trust loss. Your app needs to be airtight, and your dev team should be up to speed with UK and EU legislation.

 
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7. AI doesn’t run itself, be ready for ongoing maintenance

This one catches people off guard. Unlike static features, AI systems evolve. That’s their strength, but also a maintenance headache if you’re not ready.

You’ll need to:

  • Retrain models with new data
  • Monitor performance for drift
  • Adjust for algorithmic bias
  • Update APIs and services as platforms change

Think of AI as a garden, not a sculpture. It needs tending. The best app developers businesses trust don’t just hand you an AI feature and walk away; they set you up with support plans, performance monitoring tools, and clear ownership for ongoing improvements.

 

8. Your users don’t care that it’s AI. They care that it works

It’s easy to fall into the trap of marketing your app as “AI-powered” like it’s a badge of honour. But your users? They don’t care what tech powers it. They care that it solves their problem - fast, simply, and reliably.

If your AI makes the app feel clunky, weird, or unpredictable, it doesn’t matter how advanced it is. It will frustrate your users and damage your brand.

The difference between a clunky AI feature and a seamless one usually comes down to UX. That’s why working with experienced app developers, who understand how to balance functionality with user experience, is critical.

 

So... is AI worth it?

Absolutely. But only when it’s done well.

Done right, AI can:

  • Boost personalisation
  • Reduce admin overhead
  • Offer smarter insights
  • Improve support
  • Make your product feel future-ready

But it’s not plug-and-play. It’s a strategic decision. And the best application developers (like us 👋) will help you make that decision in a way that works for your business, your users, and your goals.

 

Final thoughts

If you’re exploring AI integration for your app, don’t just chase the hype. Take a step back, work with developers who understand both the tech and your industry, and build something that’s genuinely useful.

At The Distance, we’ve helped businesses across travel, finance, health and beyond bring smart, secure and scalable AI features into their apps. And we do it without jargon, drama, or unnecessary complexity. Just honest conversations and solid execution.

Need help integrating AI into your app?

Let’s talk through your ideas and see what’s possible. No pressure, no hard sell, just expert advice from application developers who know how to make it work.

 
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