Is AI actually creating more work for your team?

AI was supposed to remove repetitive work.

But in some businesses, something slightly different is happening.

Employees are spending more of their day helping different systems and AI tools work together.

Copying information from one platform into another. Giving an AI tool extra context it can't access itself. Checking data between different apps. Correcting an AI-generated answer that's almost right. Then copying the finished result somewhere else.

Sound familiar?

There's a term for this: human middleware.

It's when people effectively become the glue holding disconnected technology together.

And once you start looking for it, you'll probably see examples everywhere.

When people become the integration

Imagine someone needs AI to draft a response to a customer.

First, they open one system to find the customer's details.

Then they copy information from another application.

They paste everything into an AI tool, explain the context, check the response and correct anything that's wrong.

Finally, they copy the result back into whichever system they were originally working in.

The AI might have produced the response in seconds.

But the employee still had to do all the work around it.

Multiply that across different people, processes and applications and those little manual steps can consume a surprising amount of time.

AI can save time while creating new admin

The strange thing is that businesses can still feel more productive while this is happening.

And in many ways, they probably are.

AI can help draft emails, summarise information, analyse documents and speed up all sorts of everyday tasks.

The problem is what happens around the AI.

New tools are often introduced faster than the underlying technology and processes can adapt.

A business adds an AI assistant here. An automation there. Another AI-powered feature somewhere else.

Individually, they might all be useful.

But if they don't connect properly with your existing systems, employees end up bridging the gaps themselves.

That's when AI can start adding a new layer of administration rather than removing one.

Look at the whole process, not just the AI

This is why adopting AI shouldn't simply be about finding more AI tools.

You need to look at how work actually moves through your business.

Where does your data live?

Which systems need to communicate with each other?

Where are employees repeatedly copying and pasting information?

Which processes still depend on manual handovers?

And are people spending too much time checking AI-generated information because the data or context behind it isn't reliable enough?

Sometimes the biggest opportunity isn't adding another AI tool.

It's fixing the process underneath it.

Your employees shouldn't be the glue

Good technology should reduce friction.

Your team should be spending their time helping customers, solving problems, making decisions and doing work that creates value.

They shouldn't have to spend large parts of the day helping one piece of software communicate with another.

If employees are constantly switching between applications, copying information, correcting AI outputs and manually stitching workflows together, it could be a sign that your technology strategy needs some attention.

AI can absolutely make a business more productive.

But it works much better when the technology, data, security and processes around it are ready too.

Is your technology genuinely reducing workload - or simply moving it somewhere else?

If you'd like help reviewing how AI and technology are being used across your business, get in touch.