Trump Orders US Agencies to Rebrand AI as 'Super Intelligence'

What happened

US President Donald Trump has signed an executive order directing the federal government to replace the term "Artificial Intelligence" with "Super Intelligence" (or "SI") across executive branch communications, "to the maximum extent permitted by law." The order states that modern AI systems "far exceed what was envisioned when the term 'Artificial Intelligence' first came into use" and now represent "a new era of Super Intelligence."

Despite the rebrand, the order leaves the legal and statutory definition of AI unchanged — Section 3 defines "Super Intelligence" by reference to the existing legal meaning of artificial intelligence. The order also signals that Washington will continue to lean on industry self-regulation rather than new binding rules for how AI is developed and deployed, according to Computerworld's reporting on the order.

Why it matters

The move is largely symbolic but carries real signalling weight for how AI is governed in the United States. By changing the label while keeping the underlying legal definition intact, the administration is shaping public and industry perception of the technology's maturity without introducing new obligations on developers or deployers of AI systems.

For organisations building AI-enabled products and services, the substantive takeaway is that the US policy environment continues to favour voluntary, industry-led standards over prescriptive regulation — at least for now. That keeps compliance burdens relatively light in the near term, but it also means the responsibility for safe, trustworthy and well-governed AI deployment sits more squarely with individual companies and the standards bodies they choose to follow.

The Renascence take

Renaming a technology doesn't change what it does — but it does change how people feel about it, and that is squarely a behavioural-economics question.

Labels are framing devices, and framing shapes trust. Calling a system "Super Intelligence" primes users and regulators to expect more capability and more agency than the underlying technology may actually deliver — a gap that, left unmanaged, becomes a customer-experience liability the moment the system underperforms expectations. Operators relying on AI in customer-facing services should treat this as a reminder to govern by function, not by nomenclature: be precise about what a system can and cannot do, test how new terminology changes user expectations, and resist the temptation to let branding outrun capability.