How businesses without an AI team can make AI work

“We’d love to use AI, but we don’t have the team for it.”

This comes up a lot in small business circles, and it’s understandable. Between the perceived need for deep technical expertise, the upfront costs, and questions about whether it’ll pay off, AI can still feel like something only big companies can do well.

But that assumption is costing smaller teams more than they realise.

The truth is, you don’t need an in-house AI team to benefit from AI. You just need to know where to start, which tools to use, and who to partner with if things get more complex.

In this article, we’ll show you how small businesses can get real outcomes from AI through off-the-shelf tools, the right custom support, and systems that are ready to scale when you are.

Why building an AI team isn’t always step one

Hiring your own AI team might sound like the gold standard, but it’s not the only way to see results.

Let’s say you were to build one. In the UK, data scientists alone earn an average of £67,000 a year. And that’s just one seat. You’d also be looking for a machine learning engineer, an AI researcher, and someone to manage infrastructure or dev ops. Beyond salaries, these roles need up-to-date tools and ongoing training, too.

For many small businesses, that kind of investment makes sense later, but not when you’re just trying to solve day-to-day bottlenecks.

If you’re looking for traction now, there are two practical starting points that let small teams tap into the benefits of AI, without taking on technical overhead.

Let’s walk through them.

Start with off-the-shelf tools

If you’re just getting started with AI, one of the easiest (and smartest) ways to begin is with off-the-shelf AI.

These tools are designed to work straight out of the box. Many come with free trials or pricing plans for small teams, allowing you to test features without a large budget or extensive setup.

Where off-the-shelf AI works best

Here are a few examples of where these tools are already helping small teams:

• Customer service

  Tools like Zendesk or Chatfuel can handle FAQs, booking, and basic routing. That means fewer repetitive queries for your staff and faster responses for your customers.

• Sales

  CRMs like HubSpot and Pipedrive use AI to score leads and prompt follow-ups, helping you to focus on the right conversations at the right time.

• Operations

  Forecasting tools like StockTrim use AI to predict demand and suggest smarter reordering. Great for small retail or inventory-based businesses trying to minimise overstock and stockouts.

• Marketing

  Platforms like Jasper or Copy.ai can help generate drafts for product descriptions, social captions, or email campaigns. Handy if marketing is just one of the many hats you wear.

The best part about off-the-shelf AI is that you can get started in a few days. It’s low effort to try, easy to scale if it works, and simple to move on from if it doesn’t.

That said, every business is different.

If your team’s already tried some of these tools and found they don’t quite fit how you operate, or if your workflows are more specific than what a plug-and-play tool can handle, there’s another route.

When custom AI makes sense

If you’ve got more specific workflows or you’ve hit limits with plug-and-play solutions, custom AI might be a better fit.

Now you might be thinking, “You just said I don’t need an AI team… and now we’re talking about custom development?”

Custom doesn’t always mean building a tool from zero. Sometimes it’s about tweaking or extending what you already use so it works better for how your team actually operates.

Think of it like tailoring a suit. Off-the-shelf gets you in the ballpark, but custom fits your business exactly.

And no, you don’t need to hire an in-house AI team. But you might need to work with one, externally.

That’s where a trusted AI development service provider comes in.

Instead of hiring engineers and learning on the fly, you collaborate with a team that’s done it before. One that helps you spot what’s feasible, builds in small steps, and delivers something your team can use (and maintain).

So, how do you know when to go custom?

Here are a few signs:

• You’re sitting on data that isn’t being used.

  Maybe it’s tucked away in old systems or scattered spreadsheets, and no out-of-the-box tool is built to handle it.

• Your workflows don’t follow the usual templates.

  If you’ve built processes around client needs, service levels, or compliance steps, standard automation often falls short of expectations.

• You want to compete by doing something different.

  Sometimes the win is solving something your competitors can’t, like building an AI-powered quote generator or forecast tool tuned to your industry edge.

• You work in a regulated space.

  Finance, legal, and healthcare sectors need AI that adheres to rules. A custom setup means your compliance stays baked in.

Spotting one or two of those signs means you’re ready for something more tailored to remove friction and make better use of what you already have.

Don’t forget the foundations

Whether you go off-the-shelf or custom, your AI’s only as good as the systems it plugs into.

This might not sound exciting, but infrastructure is often the silent barrier to AI success. In fact, 47% of SMB decision-makers say they don’t yet have the systems in place to scale AI as quickly as they’d like.

But that doesn’t have to be your story.

Getting the groundwork right (early) means you’re setting AI up to work with your operations. That groundwork might include:

• Structuring your data (e.g., moving away from error-prone spreadsheets)

• Standardising inputs like forms or fields

• Streamlining how your tools talk to each other

Take Jupiter Underfloor Heating, for example. Their original quoting process was manual, fragmented, and full of friction. We built a system that not only streamlined the workflow but gave them a clean, structured data set that could support future AI-driven quoting and scheduling.

You don’t need a data science department to make progress with AI. If the workflow is clear and the problem is real, there’s almost always a way forward.

Want to go further with the tools you’ve got?

Adapt works with small businesses to improve or tailor existing AI tools, so they fit your workflow, not the other way around.

Let’s map out what that could look like.