AI next to the work
Most of the businesses we talk to have tried Claude or ChatGPT in the browser. Some employees use it daily. Others opened it once and forgot about it.
What they have in common is that the AI sits next to the work, not inside it. The employee has to switch tabs, paste text in by hand, copy the answer back, and make sure nothing sensitive ends up somewhere it shouldn't. It works for the odd draft. But it never becomes part of how the job actually gets done.
The result is predictable: the AI delivers a little value, to a few too many people, in slightly too random ways. And because no one is really steering it, a private, unstructured kind of use takes hold that neither management nor IT has any visibility into — what we've written about as shadow IT.
A licence is not a strategy. A chat window is not a workflow.
What it means to get Claude into the work
The difference between having AI next to the work and inside it comes down to two things: where it lives, and which tasks it actually does.
Where it lives. Claude is connected to the systems you already work in — the line-of-business system, email, documents, the knowledge base. The employee doesn't have to copy data back and forth. Claude fetches what it needs, where it sits, with access control deciding what it's allowed to see.
Which tasks it does. Not generic examples from a course, but the actual tasks that take time in your business: summarising a case across documents, preparing a response based on real data, quality-checking something against your own procedures.
When Claude lives where the work happens and works on real tasks, it stops being a website people occasionally open. It becomes part of operations.
When the connection doesn't exist, you build it
Many tools have ready-made connections to Claude today. But not all of them. If your business uses a line-of-business system Claude can't talk to yet, there are two choices: do without, or build the connection yourself.
The bridge between Claude and a system is called an MCP (Model Context Protocol). When it exists, Claude can fetch data from and perform actions in the tool — safely, and with access control in place. That's the difference between an AI that talks about the work and one that can actually take part in it.
This is where it gets technical, and this is where most people stop. We've built connections like this before — including to Microsoft Outlook, and to an accounting system (PowerOffice) for quality management at a client. A simple connection might be a read-only lookup against one system. A more advanced one might write back to a line-of-business system, with authentication and logging. The point is the same: Claude gets to work with the tools you have, not just the ones Anthropic has built a connection for.
A human at the wheel
Let's be clear on one thing, because it matters: this is not an autonomous AI that makes decisions on its own.
Claude is a tool for your employees. A person is always at the wheel. When we connected Claude to an accounting system for quality management, it wasn't so the AI could approve anything itself — it was so a caseworker could get a better basis for the decision, faster, and make the call themselves.
That's not a limitation we apologise for. It's how responsible AI should work in a business. The more Claude is connected to real systems, the more it matters to know who checks what, which decisions a human has to make, and where the data flows.
It starts with structure — here too
This is the deep, technical end of what we do. But it starts in the same place as everything else: with structure.
Before we connect anything, we map the tools, the workflows, and the data. Which systems are used daily? Where does the information sit? Which tasks give the most value the fastest? And what access and what security have to be in place before Claude is let in?
An AI Ready assessment answers the question are we ready. Getting Claude into operations answers how do we make it happen. The first is the entry point. The second is the execution.
A natural path is to start small — one use case or one department — prove the value, and roll out more broadly once the foundation is in place. You don't have to take the whole business at once. You have to take the first step right.
What this is not
To be honest about what you get, it's just as useful to say what you don't get:
- We don't sell a licence and disappear.
- We don't set up a chatbot on your website and call it an AI strategy.
- We don't hand over a slide deck of recommendations you have to carry out yourself.
- We don't build an AI that makes decisions without people.
What we do is teach your business to use Claude on real tasks, connect it to the systems you already work in, and build the connection ourselves if it's missing — with structure, access, and control in place first.
AI starts not with technology. It starts with structure.
Get in touch for a free AI Ready assessment →
Read also: Claude Cowork: When the AI Agent Moves to Your Desktop