Trump orders US government to call AI ‘Super Intelligence’
President Trump signed an executive order directing federal agencies to replace the term "artificial intelligence" with "Super Intelligence" across official policy documents, websites, and press releases.
Key Takeaways
- Key Highlight：President Trump signed an executive order directing federal agencies to replace the term "artificial intelligence" with "Super Intelligence" across official policy documents, websites, and press releases.
- Innovation & Tech：Highlights advancements in Trump, US, AI, demonstrating rapid progress in model capabilities.
- Industry Impact：Reported via The Verge, offering actionable signals for developers and technology leaders.
A new executive order from the Trump administration mandates that the US government stop using the term "artificial intelligence" in official communications. Going forward, policy websites, documents, and press releases will refer only to "Super Intelligence."
The terminology shift affects how federal agencies frame AI-related policy, regulation, and public messaging. While the underlying technologies and programs remain the same, the rebranding signals a deliberate effort to reshape the narrative around advanced computing systems at the highest level of government.
For AI industry stakeholders, the change could create friction in how companies align their own communications with government standards. Firms engaging with federal agencies on AI procurement, compliance, or research partnerships may need to adapt their language to match the new official vocabulary.
The order also raises questions about whether the rebranding reflects a broader policy posture toward AI governance, or serves primarily as a rhetorical device. Industry observers will be watching for subsequent directives that clarify how the term "Super Intelligence" maps to existing regulatory frameworks and technical definitions.
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Industry Insights & Analysis
As artificial intelligence rapidly evolves, breakthroughs surrounding Trump, US, AI, Super are shifting toward scalable, robust real-world implementations.
Driven by both open-source ecosystems and proprietary model architectures, the integration between compute optimization, data engineering, and agentic workflows is accelerating. This development provides a strategic benchmark for upcoming AI tooling and developer workflows.