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Why Most Businesses Don’t Need AI (yet) | AAG IT Support
Mark Swift · 2026-04-29 · via AAG IT Support

The Reason Most Businesses Don’t Need AI (yet)

A lot of this comes down to one simple misunderstanding.

AI and automation are often talked about as if they’re the same thing.

They’re not. They solve completely different problems, and confusing the two is where things start to go wrong. In fact, we covered this topic is detail in: AI vs Automation: The Difference Most Businesses Get Wrong.

Automation is about removing repetitive, predictable work.

If a task follows a clear set of rules and produces the same outcome every time, it can usually be automated. Things like moving data between systems, generating reports, routing approvals, collecting information.

Once that process is defined, the system can run it every time without needing a person involved. It doesn’t get bored or distracted; it doesn’t do it differently on depending on what day it is, or whether it’s 3 degrees or 30 degrees outside. It just works.

AI, however, is different.

AI is useful when something requires interpretation. When there isn’t a fixed answer and context matters. Great examples include: summarising information, analysing data, spotting patterns, generating insights.

That’s where AI adds value. Not by replacing the process, but by adding intelligence to it, and that is precisely why most businesses don’t need AI (yet), first they need automation.

Why Most Businesses Start With AI

AI gets all the attention because it’s the visible part.

It’s the part that feels new. The part that feels impressive. The part people can see working straight away.

So naturally, that’s where businesses focus.

  • They enable Copilot
  • They introduce ChatGPT
  • They encourage teams to “start using AI”, especially in the software that provides it

And to be fair, there is an immediate benefit.

Emails are written quicker, notes summarised faster, information is easier to find. But if you zoom out and look at the bigger picture, very little has actually changed.

The same work is still happening.

  • People are still gathering data
  • Still moving information between systems
  • Still chasing updates from colleagues

They’re just doing it with an assistant now. At best, it’s an incremental improvement, but we’re sorry to say that it is not a transformation.

What should you do instead of starting with AI?

The biggest gains come from removing work altogether, and AI can’t do that alone. Which is often the bit that gets most overlooked.

Take reporting as an example.

A lot of organisations look at AI and think, “great, we can use this to analyse our reports.” And yes, you can, AI is useful for that task. But it’s not where the real value is.

The real value is asking:

Why is someone compiling that report manually in the first place?

Or:

Why are updates being chased across teams?

Why is data being moved between systems by a person?

Whilst using AI to analyse a report is useful, if you still have someone compiling the report, chasing colleagues for bits of data and then duplicating the data from the system to the report, then using AI at the very end of all that is only a small efficiency gain. Look at it this way: you made part of the overall task slightly quicker, but you didn’t remove the biggest time drain.

So, by starting with automation, you can generate these reports instantly with live, current data. No chasing, no moving data, just a clear and up-to-date report. That removes work altogether.

Don’t get caught up in the talk of people looking for jobs that are “AI proof”, because in reality, automation has already changed more jobs than AI ever has.

AI is mostly speeding people up, whilst automation is removing the work entirely. And don’t worry, we’re not saying automation always replaces jobs, but it does often reduce the number of people needed. That’s the thought that needs to sink in.

This is a topic we’ll cover in detail at a later date.

AI vs Automation (in simple terms)

Automation
Removes repetitive, predictable work
Artificial Intelligence
Adds intelligence where interpretation is needed
Removes repetitive workAdds intelligence
Same results every timeFlexible outputs
Best for predictable processesBest for interpretation

Real World Example, Starting With Automation

We’re very honest here at AAG IT Services, we use automation and AI for several internal processes. We do this with the focus on cutting the friction of day-to-day IT support for our customers. However, there are other areas and departments where automation and AI has proven to be fruitful.

Take our Sales Team for example.

When a new enquiry comes in, before anyone picks up the phone, there’s usually a bit of research involved. Every Sales Team experiences this. You spend time:

  • Looking at the company website
  • Checking LinkedIn
  • Searching for recent news
  • Trying to understand who they are

Done properly, that can take two to three hours.

Now, here’s how automation and AI have helped transform that task into 2-3 minutes.

Automation takes the repetitive steps: looking at the company website, LinkedIn, news outlets, etc. And uses AI intelligence to pull all the relevant information, AI can then go one step further and populate this information into something meaningful like a clear one-page report.

The research hasn’t just become faster; it’s disappeared as a task.

Which means instead of spending two hours gathering information, that time can be spent actually speaking to the client.

And that’s why starting with automation is always the first step

What can you do next?

AI is powerful. There’s no question about that. But on its own, it rarely transforms a business.

The real opportunity sits in automation, because once you remove the work that shouldn’t exist in the first place, AI can finally do what it’s meant to do.

Enhance the work that actually matters.

This is something that AAG IT Services can support your business with. Contact our team today and we’ll even show you the report that we automate to gain a better understanding of your organisation.