AI Glossary
Artificial general intelligence (AGI)
AGI, artificial general intelligence, general AI
Artificial general intelligence (AGI) is a hypothetical system that matches humans in breadth — capable of any intellectual task. Today's AI systems are narrow: very good at specific tasks, but not universal.
- AGI is a hypothetical concept — no existing system meets it.
- Its defining feature is breadth: the ability to handle any intellectual task at a human level.
- Today's models are narrow AI, fluent at specific tasks but without general flexibility.
Artificial general intelligence (AGI) is a theoretical system that would match humans in the breadth of its mental abilities — able to learn and solve any intellectual task, transfer knowledge across domains, and act beyond a narrowly defined goal. It is a concept, not an existing technology: as of 2026, no system meets this definition, and the very moment of reaching it remains a matter of dispute.
The key is the distinction between breadth and fluency. Today's systems are what's called narrow AI: a model can generate text, recognize images, or write code at a very high level, but each one operates within the tasks it was prepared for. Large language models and generative AI impress with their versatility in working with language, yet they lack the general, autonomous flexibility that the definition of AGI assumes.
From a company's perspective, this distinction has practical importance, because it guards against mistaken assumptions in deployments. Current machine learning systems require a clearly defined scope, data, and oversight — they're designed for a specific process, not as a universal employee. The term AGI is sometimes used as marketing, so it's worth treating it as a research horizon and basing decisions on the real, measurable capabilities of today's models rather than on the promise of general intelligence.
Related terms