Trump Says US to Rename AI as Super Intelligence
President Donald Trump told the United Nations General Assembly on Tuesday morning that the United States is officially renaming artificial intelligence to "super intelligence." The Verge
Trump said that from this point forward, all United States documents, and hopefully the world's, will be changed to use the term "super" as opposed to "artificial" for super intelligence. He said the word "artificial" makes intelligence sound fake and described "super intelligence" as more accurate and better sounding.
The remarks sit alongside other recent statements on AI governance. Trump has said the United States already has guardrails in place to regulate and prosecute AI companies. Reuters He has also said he plans to appoint a new artificial intelligence adviser known as an "AI czar." Reuters
Looking at what this means for people who build, buy and regulate these systems, language is operational infrastructure. Model cards, procurement specifications, compliance filings, export controls and internal risk reviews all depend on shared terms. Change a core term and every downstream reference needs interpretation. That creates work. It creates ambiguity about scope.
In my view, the specific substitution adds friction. Artificial intelligence names a field of methods and systems. Super intelligence names a capability level. Practitioners treat those as different categories. One describes how systems are built. The other describes how far their capabilities extend. Using the second label for the first erases a distinction that safety evaluations, access controls and deployment policies rely on.
Worth flagging for documentation owners in particular is the question of versioning. Federal paperwork does not update by declaration alone. Forms, guidance, contract clauses and technical standards point to each other. If wording shifts in one place but not in others, teams must decide which term governs. Vendors selling into government, auditors checking conformance, and legal teams interpreting liability language would face parallel vocabularies until alignment arrives. That is manageable, but it is not costless.
The broader context here is adoption. AI systems are now ordinary enterprise tooling. They sit inside help desks, code editors, call centers, design pipelines and data analysis workflows. My kids learned to treat autocomplete and voice assistants as background utilities years ago. Enterprise users have followed a similar path with larger models. When a technology moves from novelty to utility, naming fights often follow. People argue less about whether it works and more about what to call it and who sets the terms.
In the long arc, clearer public language around these systems would help. Artificial never meant fake in the engineering sense. It meant built rather than biological. Super implies a performance threshold most deployed systems do not claim to cross. Neither shorthand is perfect. In this author's view, the useful outcome would be more precise use of existing distinctions between narrow systems, general-purpose frontier models, and hypothetical higher-capability successors, rather than a single replacement label. Precision helps buyers specify requirements, helps engineers scope evaluations, and helps regulators write enforceable rules.
