Superintelligence and the Executive Order

The order defines "Super Intelligence" more narrowly than the technical concept implies. It applies the label to systems already covered under the existing statutory AI definition, meaning, as Schmitter puts it, "your billing chatbot effectively received a promotion without a raise in capability." 

That distinction matters more than it might first appear. A naming change in federal policy doesn't alter what a system can do, what risks it carries, or what oversight it requires. It changes vocabulary, not capability. 

The term "superintelligence" didn't originate with any government order. Philosopher Nick Bostrom coined it in 1998, describing an intellect that greatly exceeds the cognitive performance of humans across virtually every domain of interest. His original work remains the foundational reference point for the concept. 

Google DeepMind's 2023 "Levels of AGI" framework places Artificial Superintelligence (ASI) at the top tier, a system that outperforms 100% of humans. Although crucially, DeepMind's own authors stamp that level as "not yet achieved." 

According to Patel, current AI remains far from even general intelligence. Today's systems are built on probability and statistics, rely on massive datasets, hallucinate frequently, and struggle to transfer knowledge across domains or retain context over time. 

Schmitter is direct about the terminology gap: "SAI" (Super Artificial Intelligence) has no established technical grounding. The accepted shorthand in research circles remains ASI. The 2026 International AI Safety Report describes today's general-purpose AI as "jagged", excelling at some tasks while failing badly at others. That unevenness is a far cry from the uniform superiority that superintelligence implies. 

Both Schmitter and Patel are skeptical the industry will adopt the new vocabulary in any lasting way. 

Public reaction has already been mixed. A September poll by Data for Progress found 68% support vs. 25% opposition for legislation that would pause advanced AI development and ban superintelligence outright. Historian Thomas Haigh has suggested that rebranding the technology as superintelligence is unlikely to calm a public that is more fearful than excited. 

Reporting cited by PolitiFact found little to no change in how AI industry leaders describe their technology in public-facing material since the order. Even high-profile commitments to rename AI products have stalled in practice, with websites and branding left unchanged weeks later. 

Patel adds a sharper point for compliance teams: the rebranding doesn't correspond to any technical milestone. It doesn't change existing threat models, risk assessments, or capability benchmarks. What it may change is terminology across jurisdictions — some regulators continuing to use "AI," others adopting "SI." That divergence creates a real risk of regulatory ambiguity, not technical transformation. 

There's a slower effect worth watching, too. Schmitter points to a pattern of federal agencies flagging or discouraging specific words in grant and research proposals. If funding bodies begin favoring "SI" language in grant narratives, expect the term to live in formal documentation even while practitioners continue to say "AI" in everyday conversation. Language habits, once established, are notoriously sticky.

Flag when a denied request later succeeds through another route and question any claim a system makes about its own limits

Decide, in writing, which decisions an agent can make alone and which require a human, and revisit that list whenever capability changes. 

Maintain a full list of every agent and every credential it holds, and trace where its output enters a business decision. 

Assign a named human owner to every agent, use an auditor who has no product to sell, and document who gets notified and how quickly.