In my last post, I talked about symptoms and causes. This week, the question that naturally comes next, is once you know what's really wrong, why isn't buying AI the answer?

Picture two businesses a year from now. Both have invested in AI. One is calmer, quicker to respond to customers and no longer dependent on the owner for every decision. The other has three new subscriptions, a team still working around them, and the uncomfortable truth that nothing has actually changed.

The difference between those two futures isn't the technology they chose. It's what they understood about their own business before they chose it.

I've posted recently about the board from the Caerphilly Business Expo, and the things that struck me most about it. Dozens of honest answers about time, communication, clarity and wellbeing, and not one of them was the actual problem. They were symptoms, and the real causes sat further down, in how work moves through the business.

Since then, quite a few of you have messaged me, and I've noticed the same follow-up question keeps appearing in different forms. Once you know what's really wrong, surely the next step is picking the right AI tool or solution to fix it?

I understand why it feels that way. But I argue there's still one step missing, and it's the one that decides whether the technology works at all.

Diagnosis tells you what's wrong. Readiness decides whether the fix will hold.

To me, the conversation is in the wrong order

Right now, businesses everywhere are being encouraged to ask which AI tools they should be using before they've understood how work actually moves through the business. The technology becomes the starting point, when it should sit much closer to the end of the conversation and the numbers show exactly what that produces.

UK SMEs now using AI is 54%

UK SME's using it extensively to automate operations is 11%

Same survey, same businesses. (British Chambers of Commerce, 2026)

According to this, more than half of UK SMEs are now using AI in some form (although I would argue this is higher), but only around one in ten are using it in a way that genuinely changes how the business operates, this is agree with. That gap isn't a technology gap. The tools available to the 54% are the same tools available to the 11%. It's a readiness gap.

I've lost count of the demonstrations I've seen recently showing AI producing content, answering phones, writing proposals or automating emails. They're all impressive in their own right, and I say that as someone who builds with these tools every week for clients. But every one of them assumes the business is already clear about what it's trying to achieve.

What happens if it isn't?

AI can accelerate a process, but it can't tell you whether the process makes sense in the first place.

It can write emails faster, but it can't decide whether those emails should exist at all. It can automate decisions, but it can't fix a business that has gradually built itself around workarounds, duplicated effort and information that only exists inside someone's head. As I have said, point good technology at a symptom and all you've done is help your business do the wrong thing faster. Readiness is what stops that happening.

So what does readiness actually look like?

It has very little to do with technology. It starts with understanding your business well enough to know where technology will genuinely make a difference. In practice, that comes down to considering things like:

How your processes cope with growth

Is your data accurate enough to trust?

Does your team all work from the same information?

Can work continue consistently if one key person is suddently off?

Where are customers experiencing unnecessary friction?

They're not glamorous questions, but they're the ones that determine whether any new technology becomes genuinely transformational or simply another subscription added to an already complicated business. Underneath every one of them sit the same three things: your processes, your data and your people. Get those right, and almost any well-chosen tool will deliver. Get them wrong, and even the best technology will disappoint.

A better conversation

This thinking has become the foundation of what I do. Every day brings another announcement, another tool and another prediction about the future of work, and it's easy to conclude that AI readiness means buying something before everyone else does.

That's just not true. Readiness means understanding your own business first. Only then does it make sense to decide which technology deserves a place in it.

If that's a conversation you've been meaning to have, I'd love a chat.

Until the next time.

Estelle