Superintelligence is the idea of an AI system far smarter than any human across nearly everything that involves thinking: science, strategy, writing, planning, invention. It is hypothetical. No one has built one, and people disagree about whether, when or how it could happen.
Where the term comes from
The philosopher Nick Bostrom popularized it in his 2014 book Superintelligence, defining it as any intellect that greatly exceeds the cognitive performance of humans in virtually all domains of interest. His definition does not say how such a system would be built, and it does not settle whether it would be conscious. He also allowed narrower versions that vastly beat humans in one domain, such as chess, while being useless elsewhere. A chess engine that cannot do anything else does not count under the general definition.
You will see several labels used loosely, so it helps to separate them.
- Today's AI is strong in many tasks and weak in others. A frontier model can write code and pass exams yet still make basic mistakes.
- Artificial general intelligence (AGI) usually means a system that can do most tasks a human can. Definitions vary by who is speaking.
- Superintelligence is the step beyond: not just matching people, but surpassing them by a wide margin.
Some labs and officials now use "superintelligence" in marketing, mission statements and even government documents, so check how a given source is using it. It is often a stated ambition, not a measured capability.
Why it matters
The concept shapes how people talk about AI safety. If a system could outthink its overseers, then making sure it pursues the goals people actually intend, the work of AI alignment, becomes much more urgent. Researchers study problems such as reward hacking in today's systems partly as small versions of that larger worry.
It also shapes investment and policy. Claims about being on the path to superintelligence are used to justify large spending, and to argue for or against regulation.
A simple example
Imagine a research assistant that does not just answer questions but designs, runs and interprets experiments faster and better than the best scientists, then improves its own methods. That is the kind of scenario people mean. Today's AI agents can do small slices of such work, but nothing close to the whole.
What to remember
Treat the word as a claim about the future, not a product feature. When someone says a system is "superintelligent" or heading there, ask what it can actually be shown to do, on what tests, and compared with whom.