AI FOMO – when to jump in and when to sit tight.
- Chris Godfrey
- 1 day ago
- 4 min read
It’s easy to get sucked into the AI vortex, rushing to build it into operations, but many businesses don’t need this tech – at least not yet.
Picture this: You're at a business breakfast in Manchester, your coffee going cold as another owner bangs on about their "AI-powered customer service platform." Meanwhile, the person sitting next to you relates how they’ve just integrated machine learning into their inventory system. Even your accountant has started dropping "algorithmic forecasting" into casual conversation.
And there you are, wondering if you've missed the boat.
But here's the thing, you're not alone in feeling this pressure. Nearly every SME owner is wrestling with the same question: Do I actually need AI, or am I just scared of being left behind?
The hype is enormous
Right now, AI feels absolutely unavoidable. It's like a cloak dropped over the entire business world. Trade magazines are full of dire warnings about "adapt or die." Your competitors are suddenly all "AI-powered" (whatever that actually means). A blizzard of tech vendors have popped up flogging solutions you didn't know you needed.
The pressure to do something, anything, with AI is intense. But here's what nobody talks about: Jumping in without a proper strategy is expensive. Really expensive. As in ‘could bankrupt you’ expensive.
I've seen businesses sink thousands into AI projects that went nowhere. They bought clever tools that solved problems they didn't actually have. They've exposed themselves to cyber risks they didn't understand and created data governance headaches that keep them up at night. All because they felt they should be using AI, not because they'd worked out why they needed it.
The hard facts about AI in business:
1. Only 31% of UK SMEs are actually using AI
2. 33% of UK SMEs have no plans to use AI at all
3. 30% of UK SME leaders simply don't see the value in AI
4. 41% of UK small businesses want to integrate AI but don't know where to start
5. 89% of British businesses haven't seen any customer value from their AI investments yet
6. 80-85% of AI projects fail to meet their expected outcomes
7. 42% of companies abandoned most of their AI initiatives in 2025, up from 17% in 2024
Let's get real about what AI actually does
So where does AI genuinely help SMEs, and where is it just costly theatre?
The stuff that actually works:
Automating the boring, repetitive admin that eats away at your team's time. Getting better insights from customer data you're already sitting on. Smart scheduling that stops the diary becoming a nightmare. Chatbots that handle the "what are your opening hours?" questions at 11pm.
The stuff that's often oversold:
Complex systems that need constant attention and a data scientist on retainer. "AI-powered" tools that are basically a glorified spreadsheet with a fancy label. Cutting-edge solutions that aren't sharp enough for real-world messiness.
Here's the unglamorous truth: Sometimes a better process beats a shiny AI tool. Sometimes you just need a decent CRM and someone who knows how to use it properly.
But how do I know if I need it or not?
Before you adopt any AI, ask yourself three questions:
What specific problem am I trying to solve?
Could I fix this with what I've already got?
Do I actually have decent data to feed it? (Because AI trained on rubbish data just means pricey rubbish coming back.)
If you can't answer these questions, you're not ready. And that's fine. You’re just one of millions in the same boat who are terrified of missing out but aren't missing out at all.
The smart way forward
Let’s assume you've identified a genuine use case. How do you move forward without getting burned?
Start small
Pilot before you scale. Test one process, one team, one use case. See if it actually delivers value before you roll it out across the business.
Mind your data
Where's it being stored? Who can access it? If you're dealing with customer information, cloud sovereignty isn't just techie jargon, it's about compliance and control. You need to know where your data lives and who's got their hands on it.
Security comes first
AI tools need protecting just like everything else in your tech stack. Actually, sometimes more so, because they're often handling sensitive information or making decisions that affect your operations.
Skills matter
Do you have someone who can actually manage the tech, or are you flying blind? If the answer's the latter, you either need to hire, train, or reconsider the timeline.
Go back to the beginning
Here's a principle that’s worth remembering: Automation before AI. Get your basic processes digitised and working smoothly first. You'd be amazed how many "we need AI" problems are actually "we need to get our spreadsheets talking to each other properly" problems.
You're allowed to be thoughtful
It's absolutely fine to be a "slow adopter". Being thoughtful about technology isn't the same as being left behind. In fact, the businesses that rush in without thinking are often the ones that end up genuinely behind, because they've wasted time, money, and team morale on failed projects.
The best time to adopt AI isn't when everyone else is doing it. It's when you've identified a clear business need, you've done your homework on the solutions available, and you've got the foundations in place to make it work.
Final word:
Currently, AI isn’t for everyone.
Instead, focus on the problem you're trying to solve, not the technology that's trendy. That's not playing it safe - that's being strategic - and strategic always beats trendy in the long run.
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