Five practical ways UK businesses can use Claude and ChatGPT today

Forget the hype. These are the everyday business processes where AI models like Claude and ChatGPT are already saving time, and how to get started without a big budget.

Most conversations about AI swing between “it will change everything” and “it's all hype”. The truth for most businesses is more useful than either: there are specific, repetitive processes where today's AI models do a genuinely good job, and they're often the processes your team likes least.

Here are five places we'd look first.

1. Processing documents

Invoices, purchase orders, delivery notes, application forms, contracts. If someone in your business reads documents and types the contents into another system, that's a strong candidate. Models like Claude are very good at reading a document and pulling out structured data, which can then be checked and posted automatically.

2. Triaging email and enquiries

AI can read incoming email, work out what it's about and how urgent it is, route it to the right person and draft a reply for them to approve. Your team stays in control, but loses the sorting and first-drafting.

3. Answering questions from your own knowledge

Policies, product specs, procedures, past proposals. A well-built assistant can answer staff or customer questions from your own documents, and show where each answer came from so it can be checked.

4. Making sense of reports

Rather than everyone reading the same dashboard and drawing different conclusions, AI can produce a short plain-English summary of what changed this week, and flag anything unusual for a person to look into.

5. First drafts of routine writing

Quotes, proposals, product descriptions, job adverts and reports. AI is a quick first drafter. The value comes from wiring it into your own templates and data, so the draft is close to right first time.

How to get started

Pick one process that's repetitive, high-volume and well understood. Measure how long it takes today. Then build a small proof of concept against real examples and compare. If it works, scale it up; if it doesn't, you've learned something for a small cost.

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