Artificial Intelligence: What It Is and How Businesses Use It in Practice

Artificial intelligence (AI) is software that learns patterns from data and uses them to produce outputs on its own: it answers questions, writes text, sorts documents, forecasts demand or recognises images. Unlike a conventional program, nobody has to write every rule for it. For most businesses today, the most practical forms are generative AI such as ChatGPT or Claude and automations that connect AI to email, a CRM or accounting software.

In short:

• Artificial intelligence is an umbrella term covering machine learning, neural networks and, above all today, large language models.
• In 2025, 20% of EU enterprises with 10 or more employees used at least one AI technology, up from roughly 13.5% a year earlier (Eurostat).
• AI delivers the most value in repetitive work with text and data: emails, quotes, customer support, document processing.
• AI makes mistakes and invents things. Anything that goes to a client or into the accounts needs a human check.
• Start with one specific process and measure how much time it saves before adding more tools.

What is artificial intelligence?

The easiest way to explain what artificial intelligence is: compare it with ordinary software. A conventional program does exactly what a developer tells it: "if an invoice is overdue, send a reminder". An AI system receives a large number of examples and works out the rules itself. That is why it can handle tasks that are hard to describe with rules, such as recognising that an email is a complaint even when the word "complaint" never appears.

The EU AI Act (Regulation (EU) 2024/1689) defines an AI system as a machine-based system that operates with some degree of autonomy and infers from the input it receives how to generate outputs such as predictions, content, recommendations or decisions. The key word is "infers": the result is not pre-programmed.

The term artificial intelligence was first used by American computer scientist John McCarthy in a 1955 proposal for a summer research project at Dartmouth College (the workshop took place a year later). The field is more than 70 years old, but it only reached ordinary businesses with tools you can operate in plain language. The turning point was ChatGPT at the end of 2022.

How artificial intelligence works

You do not need the maths to make business decisions about AI. Three terms cover most of what you will hear:

• Machine learning: a program learns from historical data. For example, it uses thousands of past orders to estimate how much stock you will need next month.
• Neural networks and deep learning: machine learning loosely inspired by the brain, with many layers of computation. They let AI recognise speech, images or handwriting.
• Generative AI and large language models: AI that creates new content. A large language model (LLM) has been trained on vast amounts of text and predicts which word should come next in an answer. ChatGPT, Claude and Gemini are all built on this.

This principle explains generative AI's main weakness: the model does not write what is true, but what is probable. Usually that is the same thing. When the model does not know something, though, it can confidently produce nonsense (a so-called hallucination). For facts, figures and legal questions, connect the model to your own documents or verify the output.

Types of artificial intelligence by what they do

All the AI businesses use today is so-called narrow AI: it handles a specific type of task, does not think like a person and wants nothing of its own. General artificial intelligence (AGI) that could do anything a human can does not exist yet. In practice, it is more useful to group AI by what it does:

The difference between a chatbot and an assistant is explained in our glossary entries chatbot and AI assistant. What systems that carry out steps on their own can already do is covered in AI agents for business.

How businesses use artificial intelligence in practice

According to Eurostat, 20% of EU enterprises with 10 or more employees used at least one AI technology in 2025, 6.5 percentage points more than in 2024. The most common uses were analysing written language, creating images, video or audio, and generating text or speech. Adoption varies widely: from over 40% of businesses in Denmark to around 5% in Romania. Large companies use AI far more often than small ones.

Where artificial intelligence most often saves businesses time:

• Sales and marketing: draft quotes and emails, product descriptions, campaign briefs, a summary of an enquiry before a sales call.
• Customer support: a chatbot answers repeat questions (delivery, dates, pricing) and hands complex cases to a person together with the conversation history.
• Admin and email: sorting incoming mail, draft replies, meeting notes and action items.
• Documents: extracting data from invoices, orders and contracts, and checking that nothing is missing.
• Internal knowledge: an assistant that answers from your policies, price lists and manuals, so new staff do not have to keep asking colleagues.
• Development and IT: writing and reviewing code, scripts, documentation.

Specific tools for each task are compared in AI tools for business. The biggest savings rarely come from the chat window itself, but from connecting AI to the tools you already use. How to build those connections is shown in n8n vs Zapier vs Make.

What artificial intelligence cannot do (yet)

• It is not accountable. Your business is responsible for a contract, a quote or a reply to a customer, not the tool.
• It does not know your data until you provide it. A general model knows nothing about your prices, customers or stock levels.
• It does not always know what is current. Without access to the web or your systems, it works with knowledge up to the date the model was trained.
• It will not fix a broken process. If a process is chaotic, AI just makes the chaos faster. First clarify who does what and by which rules.

Artificial intelligence and the rules: the AI Act and GDPR

AI use in the European Union is governed by the AI Act, which entered into force on 1 August 2024 and applies in stages. Since 2 February 2025, unacceptable practices such as manipulating people or social scoring have been banned. Since 2 August 2026, transparency obligations apply: when a chatbot talks to you, it must be clear that it is AI, and AI-generated content should be marked. The Digital Omnibus package (Regulation (EU) 2026/1744) postponed the strict rules for high-risk systems, such as AI used in recruitment or credit scoring, to 2 December 2027.

For a typical business using AI for text, email or customer support, this mainly means two things: a website chatbot must be labelled as AI, and personal data does not belong in AI tools without a legal basis and a data processing agreement. Business plans of AI tools do not use customer data for model training by default; free versions often do. More on data protection in our glossary entry GDPR. This article is for general guidance and is not legal advice.

How to start with artificial intelligence in your business in 5 steps

1. 1Pick one repetitive task. Ideally one that takes hours each week and involves text: replies to enquiries, product descriptions, meeting notes.
2. 2Measure the starting point. How long the task takes today and how many errors occur. Without this, you will not know whether AI helped.
3. 3Run a pilot with a business account. One tool, a small team, two to four weeks. Which assistant suits which job is covered in ChatGPT vs Claude vs Gemini, and how to brief the tool so the output makes sense is explained in how to write prompts.
4. 4Set the rules. What data may go into the tool, who checks the outputs and what never leaves without human approval.
5. 5Evaluate and connect. If the pilot saves time, connect AI to your email, CRM or online shop so people do not copy data between windows. Only then add the next process.

Model example (fictional): an installation company receives around 60 enquiries a week by email, and a salesperson retypes each one into a spreadsheet and replies manually. After automation, AI extracts the name, location, job type and preferred date, saves them to the CRM and drafts a reply. The salesperson checks the draft and sends it, and spends the saved time on calls with clients who are close to ordering.

When to bring in an expert

You can try ChatGPT or Claude for writing on your own in an afternoon. An expert is worth it when you want to connect AI to business systems (email, CRM, online shop, accounting), build a chatbot on your own documents, process customer personal data, or when you are not sure which process to automate first. At Weboptim we have worked on websites, automation and AI for 9+ years, and we build every solution around how much time or money it actually saves. Take a look at our AI solutions for business and digitalisation and process automation, or describe the process that slows you down most via our contact form.