AI in your business: what actually works today - and how to introduce it

What AI actually is

Right now, one technology sits behind most of the talk: large language models. These are programs trained on enormous amounts of text that learned to continue patterns. Ask a question and the model computes which answer most plausibly follows - word by word. That sounds banal, and it is. What comes out of it is the surprising part: drafting, summarising, translating, answering questions, writing code - all variations of the same ability to continue language in a way that makes sense.

Two things follow, and both take much of the fear out of the subject. First: AI isn't a thinking being with intentions of its own. It's a tool - a remarkably capable one, but a tool. Second: because the model always picks the most plausible continuation, it sounds confident even when it's wrong. That behaviour is called hallucination, and it's the main reason responsibility for a result stays with you. Understand those two sentences and you understand more about AI than most sales decks will tell you.

Nobody on your team needs to understand the mathematics. What they need to understand is what the tool is good at and where it fails - the same as with any other tool.

What AI can do

The honest answer: a lot, and more every month. Language models write and rework text in any tone and any language. They condense hundred-page documents into half a page. They answer questions about material you give them. Alongside them are models that generate and edit images, transcribe meetings word for word, produce voices, analyse spreadsheets and write software. And increasingly there are systems that do not just answer but act: they research on their own, operate other programs and work through multi-step tasks.

That breadth is impressive - and almost meaningless for your decision. Most of what AI can do will never play a role in your business, and that is fine. Nobody introduces "AI". What gets introduced are specific tools for specific jobs. So the question is not what AI can do. The question is which part of it changes your week.

What AI can do for your business

Look at what office work in a Swiss business actually consists of and the same four shapes of work keep coming up. All four are well covered today.

Writing drafts. The reply to a customer enquiry, the cover letter for a quote, the report to management: for all of these, AI delivers a usable first draft in seconds. You correct and sharpen instead of staring at an empty page. The blank page disappears from the workday - what remains is editing, and editing is faster.

Asking your own knowledge. Manuals, contracts, process descriptions, old project files: in most companies the knowledge sits in folders, and whoever needs something asks the one person who knows. An AI that knows your own documents answers such questions immediately - with references, so you can verify. Searching becomes asking.

Generating structured output. A project description becomes a structured quote, five bullet points become a job ad, one briefing becomes three social media posts. Wherever loose input has to become a document with a fixed shape, AI takes most of the typing off your hands.

Sorting and triage. Categorising incoming mail, separating urgent from routine, giving every message a summary and a suggested action: triage is unglamorous - and precisely because it happens every single day, it is one of the most rewarding places to start.

How many hours all of this saves depends on how much of that work exists in your company. There are no serious blanket numbers for it, and we won't invent any for you. What changes reliably is the shape of the work: less typing of raw drafts, more reviewing and deciding.

Something to try: our demos

Up to here, this was theory. On our demo page you can try AI tools right in your browser - from drafting a quote to a knowledge AI to email triage, along exactly the shapes of work described above. One thing up front: these aren't products we're trying to sell you. For most of these jobs, finished software exists today that does exactly this - more mature than a demo will ever be. Our demos have a different purpose: they make tangible how AI feels in everyday work, before you buy a single licence. Try them - five minutes of clicking explains more than any article, including this one.

Almost all of the demos, by the way, play out at the same company: Fehrlin AG, an entirely fictional Swiss joinery. The names and numbers in them are invented - the technology behind them is real.

And that's the honest heart of it: the demo isn't the offer. The offer is that someone works out with you which of the many finished tools fits your data, your processes and your team - and then rolls it out so it's still in use after month two.

Which tool for whom

The market is currently sorting itself into four classes, and for your choice these differences matter more than any single feature.

Assistants inside your Office environment. Microsoft 365 Copilot and its peers sit directly in Word, Outlook and Teams. Their strength: no new interface, and the data stays where it already lives. The obvious candidate for companies whose daily work happens in M365.

Standalone AI assistants. Tools of the Claude and ChatGPT class are the most versatile: writing, analysing, structuring, working with your own documents. Their strength is quality and range. The trade-off: they're a separate window - and the data protection question wants answering before the first login, not after.

AI inside software you already pay for. Accounting, CRM, support systems: many vendors build AI functions straight into their products. Often the smartest first step is to properly switch on and configure what you already own.

Features of your own. Sometimes the AI belongs not next to your software but inside it - more on that in a moment.

Which combination is right comes down to three sober questions: Where does your data live? Which tools does your team actually work with? And who is supposed to use all of this every day? It expressly does not come down to whichever demo impressed you most - ours included.

Data protection first

Switzerland's revised Data Protection Act applies, and if you work for customers in the EU, the EU AI Act enters the picture as well. That sounds like legal fine print, but behind it sits a handful of practical questions: Which categories of data may go into which tool - customer names? Contracts? Job applications? Where does the provider process the data, and is there a data processing agreement? And what commitments have you made yourself, for instance in non-disclosure agreements with your customers - what do those rule out?

Almost all of this is solvable: the major providers know these questions and offer reasonable contract and region options. But the answers have to be on the table before the rollout, not after it. A short data protection briefing at the start - what may go where, what is off limits, which settings are mandatory - spares you the uncomfortable version: finding out afterwards what your team has long been pasting into some free tool.

A rollout that sticks

The most common mistake with AI in a business isn't picking the wrong tool. It's the rollout by mass email: licence bought, link sent, good luck. Three people give it a try, one sticks with it, and after two months everything is back to normal, just one subscription richer.

We deliberately work one-on-one instead. First a short session for everyone: what the tool is, what it can do, where its limits are and which rules apply from now on. Then comes the part that makes the difference - a 1:1 session per person, at their own desk, with their own real tasks. The clerk builds her quoting routine, the project lead his weekly report. What someone has learned on their own tasks, they keep using once the novelty wears off.

And afterwards someone stays reachable: for questions, for new use cases, for fine-tuning. The rollout doesn't end with the training day - it runs until the tool has settled into everyday work.

When the answer is your own software

Sometimes the right tool is not off the shelf. If your business runs an application of its own - a customer portal, an internal tool, a product - the AI function can belong right where the work happens: as a feature in your software rather than another subscription next to it. Your data stays in your system, and the function does exactly what your process needs.

To show this isn't a thought experiment, here's our own product: veganise.it runs a converter built on Claude that translates classic recipes into plant-based versions - live, and you can try it right now. The same logic works for quote suggestions in your industry tool or reply drafts in your customer portal: AI where your data and your processes already are.

The next step

The road to AI in your business is more manageable than the noise around the subject suggests: first understand what the technology can do, then work out which part of it touches your work, and choose the tool that fits your data and your team - with data protection settled before the rollout, not after. And the rollout deserves the same care as the choice of tool.

That's exactly the road we walk with you - from the first assessment through tool selection and the data protection briefing to the 1:1 rollout with your team.