A short history of AI
The history of AI is a history of different approaches, not just a string of chatbots.
What is it?
AI has existed as a research field since the 1950s. Approaches have come and gone: first rules and logic, then machine learning, deep learning and today’s generative models. Periods of excitement have alternated with periods of disappointment.
An everyday example
In 1997 the chess computer Deep Blue beat world champion Garry Kasparov by searching through moves. Today’s chatbots work in an entirely different way, by learning from huge amounts of text.
Why does it matter?
History shows that progress is not a straight line and that big promises have been premature before. That helps us read today’s forecasts with a cool head.
A common misconception
That AI was invented in the last few years, or that chatbots are the only form it takes.
In more detail
When did the name AI appear?
The term “artificial intelligence” took hold in the 1950s, though the field has older roots.
What came before deep learning?
Researchers built logic systems, search methods, chess programs, expert systems and early neural networks.
Why did deep learning advance so fast?
More data, more powerful chips, better methods and big investment in research.
What did generative AI change?
It made machines much better at working with everyday language and other kinds of content. It also raised new questions about errors, authorship and power.
Remember: Today’s AI is not necessarily the final stage of its development.
Reliable sources
Last reviewed 1 November 2026. An explainer, not professional, legal or medical advice. For rules and figures that change, check the official version.