Artificial general intelligence (AGI): Artificial general intelligence (AGI) is a hypothetical AI that could learn and perform any intellectual task a human can, across domains, rather than being built for specific tasks. It does not exist today, and its definition is contested.
There is no agreed test for AGI. Some definitions focus on matching human performance at most cognitive tasks. OpenAI's charter describes it as highly autonomous systems that outperform humans at most economically valuable work. Others focus on the ability to learn new skills from little experience, the way people do. Because the definitions differ, claims that AGI is close or far often disagree mostly about what the word means.
Today's models are broad, in that one system can write, code, analyze images, and reason about many subjects, but they are not general in the full sense. They do not learn from experience between training runs, they fail on some tasks a child handles, and they remain tools that act only when prompted. Serious researchers disagree about whether current methods scale to AGI, and about when, if ever, it arrives. Treat confident timelines from any side with skepticism.
For your work, AGI is a distraction from the real question, which is what today's systems can do on Monday. The capabilities that matter to you arrive incrementally, model by model, and the practical skills of prompting, verifying, and automating transfer regardless of how the philosophical debate resolves.
Example at work
A CEO reads an interview claiming AGI is two years away and asks the operations lead whether the company should pause a systems project. The lead reframes: the current assistants already draft the reports and summarize the calls the project is meant to speed up, so the question is how to use those now, not what a future system might do.
Why it matters
AGI dominates headlines and fuels both hype and fear. Understanding that it is undefined and unbuilt helps you tune out predictions, evaluate vendors on what they ship, and focus your time on capabilities you can actually use.
Related terms
- Narrow AINarrow AI is artificial intelligence designed and trained for a specific task or a limited set of tasks, such as filtering spam, recognizing faces, or recommending products. Every AI system in use today is narrow in this sense.
- Artificial intelligence (AI)Artificial intelligence (AI) is software that performs tasks that normally need human judgment: understanding language, recognizing images, making predictions, or generating text. Today it usually means systems built with machine learning.
- Large language model (LLM)A large language model (LLM) is a neural network trained on enormous amounts of text to predict the next word, then tuned to follow instructions and hold a conversation. LLMs power ChatGPT, Claude, Gemini, and Microsoft Copilot.
- AI safetyAI safety is the field concerned with preventing AI systems from causing harm, from everyday failures like confident errors and biased outputs to misuse by bad actors and risks from highly capable future systems.
- Reasoning modelA reasoning model is a large language model trained to work through a problem step by step before answering, spending extra computation (often called thinking) to improve accuracy on math, code, logic, and multi-step tasks.