Neither of these exists…yet Both get used in the present tense anyway, often in the same paragraph, by people who are describing two quite different situations.
The words are worth separating, because the gap between them is where most of the actual argument lives.
AGI
Artificial general intelligence means a system that handles the broad range of cognitive work a capable person can handle, including tasks nobody trained it for. The contrast is with narrow AI, which is superhuman at exactly one thing and useless one inch outside it. A chess engine will beat every human alive and cannot be talked into ordering a sandwich.
There’s no agreed test. OpenAI’s charter defines it roughly as systems that outperform humans at most economically valuable work, which is a business definition. Others want a benchmark, or a specific job done start to finish. The bar also keeps moving: beating chess, passing the Turing test, and writing competent code were all once treated as the marker, and each got reclassified as ordinary software about a year after it happened.
ASI
Artificial superintelligence means past human level, not at one skill but across essentially all of them, including the skill of building better AI.
That last part is what makes it a separate category instead of just more AGI. A system that can improve itself compounds, and the people who worry about this expect the distance between the two to be short. Not decades. Months, in the more aggressive versions. The concern is that AGI isn’t a destination anyone stops at, because the first thing a generally capable system gets pointed at is the research that produced it. Whether that compounding actually happens is genuinely unsettled, and the people arguing about it are not fools on either side.
The tell
AGI compares a machine to a person. ASI compares it to all of us at once.
There’s a second tell in who’s talking. When a company says it’s building AGI, that’s usually a product and fundraising claim with a definition attached that they wrote. When someone says superintelligence, they’re almost always making a safety argument, and the timeline is doing the work in the sentence.
Both terms are predictions dressed as definitions. Neither one has a test you could run tomorrow to settle it, which is worth keeping in mind the next time a headline tells you we’re two years away from one of them.