AI is the word on everyone’s lips these days.
And there’s this subtle pressure to prove your business is using it, experimenting with it, maximising it.
The latest trend I’ve seen is “tokenmaxxing”. Heard of it?
Well, this equates heavy AI usage, measured in tokens, with high value. It incorrectly implies that higher or more frequent usage automatically means you are being more productive, effective, or delivering high-value output.
That’s clearly not true. Have you seen all the AI slop?
Businesses don’t need another AI tool.
They need to understand where growth is stifled and business is being lost. And only then begin to consider how AI can plug those gaps.
It’s really that simple.
It could be the slow enquiry response. The sales follow-up that relies on memory. The customer question that gets answered manually every week. The marketing campaign that creates attention, but doesn’t bring in sales.
That is where AI can make the biggest impact.
The Problem With Vanity AI
There’s nothing wrong with experimenting.
In fact, most businesses need to give themselves permission to test, learn and make sense of what AI can actually do.
But there’s a big difference between a useful experiment and vanity adoption.
Vanity AI looks like trying every new tool because everyone else is talking about it.
Creating more content without a clearer strategy. Automating a weak process instead of fixing it. Tracking AI usage instead of outcomes.
And that’s where the hype becomes a problem.
Using more AI isn’t the same as building a better business.
It starts with a problem. A process. A missed opportunity. A point of friction that keeps slowing the business down.
AI Should Make the Business More Capable, But Also Make Business Sense
AI shouldn’t just be about making the team faster.
It should help the business become more capable of responding, guiding, qualifying, supporting, learning and converting.
But it also needs to make business sense.
Recently, I heard of a business that had used a number of virtual assistants to process data. These assistants had been doing it for years, and had become extremely efficient at.
However, it was decided the best use of budget and AI was to build a system that automated the work.
The business ended up spending three years’ worth of the virtual assistant budget to set it up.
The problem was, the business hadn’t been consistently hitting their sales targets and this work wasn’t linked to revenue generation in any way.
They spent time and money building something that wasn’t even the problem that needed solving.
This is where businesses need to pause.
Just because something can be automated, doesn’t mean it should be the first thing you tackle.
A task might be manual, but manageable. A process might be annoying, but not damaging. A piece of admin might take time, but not enough to affect sales, customer experience or profit in any meaningful way.
So, before jumping into an AI project, it’s worth asking whether the issue is actually holding the business back, or whether it just feels like something that would be satisfying to automate.
There’s a difference.
How Not To Fall Into The Shiny AI Trap
Before you adopt a new tool or start implementing AI, it’s worth doing a quick sense check:
- Is this solving a real business problem, or are we using AI because it feels like we should?
- Will this help us respond faster, sell better, support customers, or make clearer decisions?
- Is this connected to growth, customer experience, or team capacity in a meaningful way?
- Are we fixing a process that matters, or automating something that probably didn’t need fixing yet?
- Do we know what success would look like before we start?
These are the questions that help separate useful AI from shiny AI.
Once you can see the friction clearly, you can start to work out whether AI has a role to play, and what that role should be.
For example, if leads are going cold because follow-up is inconsistent, AI could help structure responses, create reminders, summarise enquiry details, or support a more reliable sales workflow.
If customers keep asking the same questions, AI could help turn those questions into website content, sales resources, knowledge base articles, or a support flow that answers things before someone has to ask.
If your CRM is full of data that nobody uses, AI could help summarise patterns, highlight missed opportunities, and make the information easier to act on.
But the starting point still has to be the business issue.
Not the tool.
Step One: Look At The Customer Journey
If you want to use AI for business growth, start by looking at the customer journey from the first point of contact through to enquiry, sale, delivery and follow-up.
- Where does the customer slow down?
- Where do they hesitate?
- Where do they need reassurance?
- Where do they ask for the same information?
For a service business, this might show up on the website. People visit the services page, but don’t enquire because they’re not sure which service fits their needs.
For an ecommerce business, it might show up when customers compare products. They may need more detail, clearer recommendations, better filtering or a more useful way to choose between options.
For a sales team, it might show up after the enquiry has already come in. The lead is good, but the response is slow or the follow-up depends on someone remembering to do it later.
These are all practical AI applications in business. Not big, vague transformation projects. Just sensible improvements to moments that already affect growth.
Step Two: Look At What The Team Repeats
The next place to look is internal repetition.
- What does the team do again and again?
- What questions do they answer all the time?
- What information do they copy from one place to another?
- What reports are created, but not really used?
- What admin has become so normal that nobody questions it anymore?
This is where AI for business can be genuinely useful, especially when it removes repetitive work and gives people more time to focus on judgement, creativity and problem-solving.
But again, be honest about value.
If the repeated task is slowing down sales, affecting customer experience, delaying delivery or draining time from higher-value work, it is probably worth exploring.
If it’s just mildly irritating, it might not need to be the first project.
That sounds obvious, but it’s where a lot of businesses go wrong.
They pick the thing that is easiest to automate, rather than the thing that would make the biggest difference.
Step Three: Use Data To Decide What Happens Next
Most businesses already have useful data. Website analytics, CRM notes, form submissions, email clicks, customer questions, sales feedback, search terms.
It’s all there.
The issue is that it’s usually scattered, messy or sitting in systems that nobody has time to review properly.
AI can help pull this information together and make it easier to understand. It can spot repeated questions, group enquiry types, summarise customer feedback, or highlight patterns in website and campaign performance.
But the value only appears when something changes afterwards.
- If customers keep asking about pricing, create clearer guidance.
- If people are visiting a page but not converting, review the message and the next step.
- If leads from one campaign are poor quality, change the targeting or qualification process.
- If ecommerce customers keep dropping off before checkout, look at where confidence is being lost.
This is one of the better uses of AI in business because it supports decision-making, not just output.
Step Four: Make Your Website Work Harder
A lot of websites still behave like digital brochures.
They explain who the business is, list the services, show a few examples and ask people to get in touch.
That’s fine, but it’s not always enough.
Your website should help people move forward. It should guide them, answer questions, make options clearer, and help them decide what to do next.
This is where AI tools for business growth can become useful.
You might build:
- A product selector.
- A quote builder.
- A guided enquiry form.
- A customer support assistant.
- A knowledge base.
- An internal dashboard.
- A customer portal.
- A comparison tool for ecommerce products.
These don’t have to be huge projects. They just need to solve a real problem.
The best marketing doesn’t always look like marketing. Sometimes it looks like a tool that helps the customer make a decision.
And if that tool removes friction, improves confidence or helps the right people enquire, then it is doing something commercially useful.
Step Five: Start Small And Measure It
You don’t need to overhaul the whole business to make AI useful.
Start with one clear problem.
One repeated customer question. One slow enquiry process. One underperforming landing page. One manual workflow. One point in the ecommerce journey where people hesitate.
Then test something small and measurable.
- Did response times improve?
- Did the team save time?
- Did more qualified leads come through?
- Did customers get answers sooner?
- Did more people complete the enquiry form?
- Did sales conversations become easier?
That is a much better measure of progress than how many tools you’ve tried or how many tokens you’ve used.
The Real Starting Point For AI Business Growth
The real starting point for AI business growth is the part of the business where growth is being held back.
It might be your marketing. Your website. Your ecommerce journey. Your sales process. Your internal systems. Your customer support.
Find the friction first.
Then decide whether AI can help reduce it.
At TH3, this is exactly why we created our AI Opportunity Lab. It’s for Yorkshire business owners who want to stop thinking about AI as a content shortcut and start seeing the practical opportunities AI can bring across marketing, websites and business processes.
Join the next live online session to find the opportunities in your business.
If you’re wondering how AI could support your marketing, website or ecommerce journey without adding more noise, get in touch with TH3 and let’s talk through where it could make the biggest difference.