The phrase “super intelligence” entered U.S. AI policy discussions after President Donald Trump used it during his September 22, 2026 address to the United Nations General Assembly.

Trump said U.S. government documents would use “super intelligence” instead of “artificial intelligence.” The State Department subsequently instructed diplomats in its international organizations bureau to use the new terminology in communications.

But “superintelligence” already means something

There is an important technical distinction.

In AI research, superintelligence generally refers to a hypothetical system whose intellectual capabilities substantially exceed those of humans across a broad range of tasks.

That is not the same thing as artificial intelligence as a general category.

Today's AI systems, including language models and AI agents, are generally not considered superintelligent in that technical sense.

Why did the terminology change?

Trump said the word “artificial” makes AI sound fake and argued that the technology should instead be called “super intelligence.”

The change is therefore primarily a terminology and government-communications issue.

It does not change the technical definition of artificial intelligence.

Why does terminology matter?

Words influence how people understand technology.

Calling a chatbot, recommendation system or AI coding assistant “super intelligence” could blur the distinction between current AI capabilities and hypothetical future systems.

For businesses and researchers, technical precision remains important.

An AI model can be highly capable without being superintelligent.

An AI agent can perform autonomous tasks without possessing general human-level intelligence.

What should businesses use?

Organizations should continue using established technical terminology in product documentation, contracts, compliance frameworks and engineering discussions.

“Artificial intelligence,” “generative AI,” “AI agent” and “superintelligence” describe different concepts.

The U.S. government's evolving terminology may become a political and communications issue, but businesses still need precise language when defining what their AI systems actually do.

In a rapidly changing industry, clear terminology matters because you cannot govern a technology properly if you cannot clearly define it.