Most people use AI like a better search engine: ask a question, get an answer, done. That leaves most of the value on the table. AI only becomes truly useful when you put it to work as a partner, on the work that fills your day.
This page gives you the overview: getting started, choosing the right tool, getting better answers, having tasks done, and protecting your data. Each part sums up a theme and points to the full article. The common thread: the technology keeps getting easier, and the choices around it decide what it delivers.
The fastest way to get something out of AI is to start small, with a task you do every week. An update you write, a report you summarise, a conversation you prepare for. You let AI help with it once, and build a habit from there.
AI helps most with four kinds of work: writing, summarising, preparing and looking things up. Whichever tool you choose, this is the starting point.
Read more: how to use ChatGPT or Claude in your daily work →ChatGPT, Claude and Copilot are similar, and for a lot of daily work it makes little difference which one you pick. For more specific work there are differences: ChatGPT is the all-rounder, Claude is strong at writing and long documents, and Copilot is at its best when your organisation runs on Microsoft 365.
For a single user the choice is small. For an organisation, cost, where your data ends up and how well it connects to your systems all weigh in.
Read more: ChatGPT, Claude or Copilot, which fits which work →The difference between a generic and a usable answer rarely lies in the tool. It lies in your question. An AI only knows what you put into it: your goal, your situation, your audience, what already exists.
Learn to get that across well and you get consistently better answers, with far less rewriting. It is a skill you can pick up in a few rounds of practice.
Read more: how to give AI good context and goals →AI can now do more than give answers. It carries out tasks on your files, writes and runs code, generates images, and drafts an approach for a project. You set a goal, and the AI works out the steps in between.
It saves a lot of time, and it calls for new habits: start with low-stakes tasks, keep sight of what the AI did, and remember that you stay responsible for the result.
Read more: what can AI do beyond chatting, running tasks, code, images and planning →With ChatGPT, Claude and Copilot, your input goes to the servers of a US provider. For a lot of work that is fine. For sensitive data you can choose an open source model that you run in-house or within Europe, so your data never leaves your own environment.
That takes more setup, and in return it gives you the most control over your data. For organisations with sensitive data it is often the serious alternative.
Read more: open source AI, your data in-house (coming soon)
If you simply want your people to learn to work with it, the workshop Claude as a Daily Work Partner is the place to start. In one afternoon you work with your own tasks and feel the difference between chatting and having AI do the work.
If you want to set it up properly at organisation level, we think along on which tool fits which work, how you keep a grip on cost and data, and how you bring your people along so it keeps running after the start.
Book a no-obligation call and we will look together at where the first gains are for your organisation.
With one task you do every week that costs you time. Let AI help with it once and build from there. Start small, not with a big project.
For daily work ChatGPT, Claude and Copilot all work fine. The choice starts to matter for more specific work and at organisation level. There is an overview in ChatGPT, Claude or Copilot: which fits which work.
By giving it your goal and context clearly. The sharper you explain what you want to achieve and for whom, the more usable the answer. More on that in how to give AI good context and goals.
That depends on the tool and the version. Business accounts are usually not used for training, free versions sometimes are. For sensitive data, open source running in-house is an option.
No. You work with plain language, the way you would ask a colleague something.
