Definition
Artificial intelligence (AI) is software that performs tasks which normally require human intelligence: understanding language, recognising patterns in images, making predictions and taking decisions. It is not one technology but a family of techniques. Some are rules written by hand. Most modern artificial intelligence is machine learning, where the system learns from examples rather than from explicit instructions. The result is software that behaves usefully in situations nobody programmed line by line.
In a company, artificial intelligence shows up in three layers. The first is invisible: fraud detection in your payment provider, spam filters, route optimisation in logistics. The second is assistive: a chatbot answering support tickets, an assistant drafting emails, a tool summarising meetings. The third is operational: AI agents that read an invoice, check it against a purchase order and book it in the accounting system without a person in the loop.
The state of the art in 2026 is dominated by large language models and the agents built on top of them, offered by a handful of labs and by open-weight alternatives. The common misconception is that AI is either magic or hype. It is neither. It is a probabilistic tool that is excellent at language and pattern tasks, weak at guarantees, and only as good as the data, evaluation and process you wrap around it.
In practice
A mid-size logistics company uses AI to read incoming delivery notes, match them against orders and flag the 5% that do not add up. Three people who used to key in data now handle exceptions and customer calls.
Why it matters
AI is now a cost and revenue lever in every function, not an IT project. In the companies I run, the question is no longer whether to use it but which processes to redesign around it first.
Frequently asked questions
- What is the difference between artificial intelligence and machine learning?
- Artificial intelligence is the broad goal: software that performs tasks needing human-like judgement. Machine learning is the main method used today to achieve it, where the system learns patterns from data instead of following hand-written rules. Almost all AI you meet in business is machine learning underneath.
- Does my business need artificial intelligence?
- If your business has repetitive work that involves reading, writing, classifying or predicting, yes, and probably sooner than you think. Start with one painful, measurable process, run a pilot with a clear success metric, and expand only when the numbers hold.