Apparently, artificial intelligence has been promoted. Obviously, whether its access privileges should follow is another matter...
On September 29, 2026, US President Donald Trump signed an executive order introducing “Super Intelligence,” or SI, as the executive branch's term for AI. Meanwhile, our agents still need permission to query databases, execute code, and touch production.
There’s an interesting conversation here, one far more important than naming conventions - and this is coming from a guy who works in the marketing department. A new name doesn’t tell us what a system can reliably do, or what we should authorize it to do. Let’s take a little peek behind the smoke and mirrors.
What Trump’s AI executive order actually changes
The September 29 executive order directs executive agencies to use the new terminology in official communications and other non-statutory documents, where legally permitted.
Previously issued contracts, regulations, and historical documents don’t require rewriting. Initially, “SI” covers technologies within the existing statutory definition of AI. Proposed legislative language for a federal definition is due within 60 days.
So, we have an administrative terminology change. We haven’t acquired scientific proof of artificial superintelligence through presidential stationery.
Nor does the order require every business to rename its AI security program.
What is artificial superintelligence?
Artificial superintelligence, or ASI, describes systems whose intellectual capabilities substantially exceed human abilities across a broad range of demanding tasks. A 2026 Oxford University Press chapter emphasizes superior reasoning across diverse sophisticated activities.
In actuality:
- AI (artificial intelligence) is the broad category.
- Generative AI produces content, including text, images, and code.
- Agentic AI uses tools and takes actions toward objectives.
- AGI (artificial general intelligence) describes broadly transferable, human-level capability, although definitions differ.
- ASI goes substantially beyond human intellectual performance.
These aren’t neatly numbered software releases. Agency describes how a system operates; intelligence describes capability. Neither automatically establishes trustworthiness.
That’s why AI agent security matters before anyone settles the AGI debate. An ordinary agent with extraordinary permissions can already make an extraordinary mess.
Why Mr. Trump, and why are technology leaders joining in?
The White House’s stated rationale emphasizes innovation, American leadership, and technological opportunity. Trump also dislikes “artificial” because it suggests something fake, a connection he made in his September 29 remarks.
Some executives have adopted the language. Axios reported Jensen Huang using “SI” during an event that also introduced a separate voluntary industry oversight agreement.
Supporting optimistic branding and maintaining relationships with Washington are plausible incentives. They remain interpretation, not established private motives.
Using the president’s terminology also isn’t scientific agreement that ASI has arrived. A shared TLA (three-letter acronym) is considerably easier to negotiate than a shared definition.
Have we actually reached superintelligence?
No. And the evidence demands a whole lot more consideration than the branding.
Stanford’s 2026 AI Index reports agent accuracy reaching 66.3% on OSWorld, a computer-task benchmark. That’s substantial progress, and roughly one unsuccessful attempt in three within that evaluation.
The report also describes “jagged” intelligence: impressive mathematical performance alongside difficulty with apparently simpler tasks. These findings summarize earlier evaluations, not a live measurement of every current model.
Better models could accelerate investigation, software analysis, and research. But benchmark success doesn’t establish dependable performance in our environment. The International AI Safety Report 2026 explicitly identifies that evaluation gap.
We should ask for evidence of breadth, reliability, and performance on unfamiliar tasks. “Super” isn’t a test result.
AI capability and access authority are different decisions
The conversation I’d like to see Washington having goes more like this:
Consider a hypothetical incident-response agent reading an attacker-controlled ticket. The ticket instructs it to export diagnostic data to an external destination.
That’s prompt injection: untrusted content attempting to become an instruction. The potential damage depends on the agent’s tools, credentials, data access, and network reach.
This is where AI access controls become concrete. We need to examine four things:
- Capability: What can it demonstrably accomplish?
- Autonomy: Which actions can it take without review?
- Authority: Which resources can its credentials reach?
- Observability: Can we reconstruct and stop its actions?
Good service account security still matters when the account’s operator can reason. Likewise, broad permissions remain broad permissions, no matter how eloquently the agent explains why it needed them.
What we should check before granting access
Start with the principle of least privilege: authorize the task, resource, and duration required. Work toward zero standing privileges where practical, instead of leaving administrative access available between tasks.
Preserve identity provenance, linking permissions to their origin, owner, and approval. Correlate that information with agent runs and downstream actions.
For data retrieval, verify that source permissions survive indexing, caching, and output generation. For shutdown, test deprovisioning against active sessions, delegated credentials, and queued work. Closing the chat window isn’t an incident-response strategy.
Use applicable AI cybersecurity standards to organize evidence and accountability, and reassess workflows when models or tools change.
These controls reduce enterprise exposure. They don’t solve every hypothetical superintelligence problem.
Whatever we call the technology, our authorization decisions need to remain specific, testable, and revocable. “Super” can stay in the announcement. Production access still needs a reason.
Artificial superintelligence still needs to prove itself
Artificial superintelligence is a claim about extraordinary capability, and it deserves extraordinary scrutiny. We can take its potential seriously while asking whether the evidence supports the label. For now, Washington has changed its vocabulary; the scientific question remains open. If we’re entering an era of systems that can outthink us, we’ll need a much better understanding of their capabilities, limitations, and behavior. Calling them “super” is the easy part.
Give agents boundaries before giving them privileges
Try our FREE Trustle trial to reveal excessive permissions, review agent access, and introduce time-limited privileges across supported integrations. Reducing unnecessary access helps limit the damage a compromised or misdirected AI agent can cause, whatever we’re calling it this week.
