The Rise Of The AI Stack: Why Small Businesses Are Turning To Multiple AI Tools

For a while, the conversation around AI adoption was largely centred on the question of which AI tools businesses should be using. And the question was a general one. ChatGPT quickly became the obvious answer for many, with millions of people turning to it for everything from writing emails and researching ideas to analysing information and solving everyday problems. At least at the outset.

But as businesses become more familiar with what AI can do, it has become clear that relying on just one tool might no longer be enough, and more than that, it may not be the best way to get the most out of these advanced AI platforms.

Instead, small businesses are increasingly building what could be described as their own AI stacks: that is, collections of different AI tools that work alongside one another, each serving a slightly different purpose.

According to a new survey from Network Solutions, 73% of small business owners in the United States who use AI now rely on more than one AI tool to run their businesses. What’s more, 27% of those surveyed are using as many as four or more.

It’s an interesting development, particularly when you consider that many of these businesses aren’t large companies with dedicated IT departments or substantial technology budgets. In fact, the survey found that 57% of respondents were running businesses on their own.

So, why are small businesses turning to multiple AI tools, and what does this tell us about the future of work?

One AI Tool Doesn’t Necessarily Do Everything

I like to think of it in the same way that humans have evolved to organise society based on different people having varying specialisations and skills. In order to become a more sophisticated species, it was imperative that at least some people were able free up some time previously used to do essential tasks like, say, hunting, to focus a little bit more on making tools, crafting shelters and creating medicinal remedies and such. In modern society, the same pattern applies – a builder is able to provide construction services for people who require them, while the task of growing food for instance, has been outsourced elsewhere, allowing society at large to specialise far more deeply in very specific occupations.

When it comes to AI models, we’re kind of doing the same thing: we’ve identified that different models may be better at different types of tasks. For instance, GPT is known for being pretty good at writing and general organisation and admin, while Claude is (arguably) better at coding. Of course, there’s one little difference here, which is that we still have an expectation that at some point, there will be a single model that is the best at all these different things (at least in theory), whereas that’s obviously not plausible, even conceptually, for humans.

Now, back to AI models. ChatGPT might have become something of a default starting point for AI adoption, but that doesn’t mean it’s the only tool businesses are reaching for. The Network Solutions survey found that 82% of respondents had used ChatGPT in the previous three months, with 51% naming it as their most-used AI tool. Google Gemini followed, with 64% having used it, while Claude, Canva AI, Microsoft Copilot and Meta AI also featured.

But the interesting part isn’t necessarily which platforms are winning the popularity contest, but rather why business owners are using so many of them in the first place. Among those using multiple AI tools, 62% said different tools were better suited to particular tasks. Another 46% said they liked having access to different personalities or writing styles, while 39% used multiple platforms to compare answers and double-check information.

In other words, businesses aren’t necessarily collecting AI subscriptions just for the sake of it. They’re actually starting to recognise that different tools have different strengths, and that using them together can sometimes produce better results. Kind of a “many hands make light work” sort of scenario. This is particularly interesting for smaller businesses, where the same person might be responsible for marketing, customer service, administration, research and a dozen other things. Thus, having access to different tools that can help with those responsibilities could make a meaningful difference.

Are AI Stacks Making Small Businesses More Productive?

Of course, the bigger question is whether using multiple AI tools actually makes businesses more productive, because it sounds great in theory, but reality could be a little different. Indeed, the survey suggests that, at least for many of the respondents, it actually does improve efficiency.

More than half (55%) said using multiple AI tools produced better results than relying on a single platform, and that figure increased to 76% among those using four or more tools. There’s also a potential productivity benefit. Three in five business owners surveyed (60%) said AI saves them at least two hours a week, while 29% reported saving six hours or more.

Interestingly, the businesses reporting the biggest time savings weren’t necessarily those using the most expensive or sophisticated tools. Instead, they tended to be the ones using AI across more areas of their operations. Business owners who used AI for at least eight of the 10 tasks included in the survey were six times as likely to report saving six or more hours a week as those using it for four or fewer tasks.

That seems to indicate to us that the real value of an AI stack might not lie in having access to lots of different platforms, but in finding practical ways to incorporate AI into everyday workflows.

The Problem with Having Too Many AI Tools

However, there’s a slight contradiction here, and a little problem that ought to be addressed. While business owners appear to appreciate the benefits of having several AI tools at their disposal, many would actually prefer not to have to juggle them. More than two in five respondents (43%) said they would be willing to pay more for a single AI tool that could do everything well, and among those using four or more tools, that figure rose to 59%.

And I think that’s actually both understandable and perhaps to be expected. Managing multiple subscriptions, remembering which tool does what, moving information between platforms and keeping track of different outputs can introduce a level of complexity that smaller businesses might not necessarily want. There’s also the question of accuracy and oversight. Although 39% of respondents using multiple tools said they compared answers across platforms, the survey found that 67% of all respondents checked AI’s work rather than trusting it outright.

So, while AI might be taking certain tasks off business owners’ hands, it hasn’t necessarily removed the responsibility of checking that the work is actually right. And I’d argue that that may, in fact, be one of the most important tasks to do.

The Future Might Not Be About Finding One Perfect AI Tool

One of the more interesting takeaways from the survey is that small businesses aren’t necessarily waiting for technology companies to develop one platform that does everything. In fact, they’re actually finding ways to combine the tools already available to them.

And this could have wider implications for how businesses operate. For smaller companies, particularly those without the resources to employ specialists across every department, an effective AI stack could offer access to capabilities that would otherwise be difficult or expensive to obtain.

But more tools don’t automatically mean better results, and that’s an important part to remember. Businesses still need to understand what they’re using, where each platform adds value and when human oversight is necessary.

So, perhaps the future of AI at work won’t be about finding one platform that can do absolutely everything. Instead, it could be about knowing which tools to use, when to use them and how to make them work together.