The language around AI changed noticeably this week.
On 29 September 2026, the White House issued an Executive Order directing the U.S. executive branch, to the maximum extent permitted by law, to use:
“Super Intelligence” and “SI”
instead of:
“Artificial Intelligence” and “AI”
in official correspondence, websites, reports, policy documents and other non-statutory communications.
Source: https://www.whitehouse.gov/presidential-actions/2026/09/inaugurating-the-era-of-super-intelligence/
That raises an obvious question for companies:
Should we start calling our AI strategy “SI” too?
For most businesses, our answer is:
Not yet.
The terminology is worth watching.
But changing the label does not yet require changing the business architecture.
The U.S. terminology changed before the underlying definition did
There is an important detail in the Executive Order.
For now, “Super Intelligence” is defined by reference to the existing U.S. statutory definition of artificial intelligence.
The Order also asks for proposed legislation that could later create a distinct federal definition of Super Intelligence.
In other words:
the terminology has changed inside the U.S. executive branch,
but the technical and legal meaning is still evolving.
That makes it too early for most companies to treat “SI” as a universally accepted replacement for “AI”.
Source: https://www.whitehouse.gov/presidential-actions/2026/09/inaugurating-the-era-of-super-intelligence/
Europe is still using AI
International businesses also need to consider that terminology is not changing uniformly.
The European Union's AI Act continues to use terms such as:
- artificial intelligence,
- AI systems,
- general-purpose AI models,
- and general-purpose AI models with systemic risk.
For example, Article 51 of the AI Act defines when a general-purpose AI model may be classified as having systemic risk.
Source: https://eur-lex.europa.eu/eli/reg/2024/1689/2026-07-27/eng
So a company operating across the U.S., Europe and Asia may increasingly encounter different terminology around overlapping technologies.
That is not necessarily a problem.
But it does mean companies should distinguish between:
policy language
and
business-system architecture.
A new name does not change what a company must design
Whether a business calls the technology:
AI,
SI,
an agent,
an assistant,
or an intelligent system,
management still needs to answer the same operational questions.
What business outcome should the system improve?
What information can it access?
What may it decide?
What may it execute?
Where is human approval required?
What happens when the underlying model changes?
Who owns the workflow?
How does the system interact with the rest of the company?
Those questions matter much more than the current label.
Terminology should not become strategy
Imagine a company with fifteen disconnected AI tools.
Marketing uses one.
Sales uses another.
Operations has built several automations.
Customer information is still fragmented.
Employees still move information manually between systems.
Changing “AI Strategy” to “SI Strategy” on the presentation does not solve any of that.
The business still has an architecture problem.
That is why companies should be careful not to confuse:
a change in technology terminology
with:
a change in how the business actually operates.
More capable systems make architecture more important, not less
There is, however, one part of the terminology shift that businesses should take seriously.
AI systems are becoming more capable.
They can increasingly:
- assemble information,
- interpret complex context,
- recommend actions,
- interact with tools,
- and execute parts of business workflows.
As capability increases, the question becomes less:
“Can AI generate this?”
and more:
“What role should increasingly capable systems have inside our business?”
That brings companies back to architecture.
Access.
Permissions.
Data.
Decision authority.
Human oversight.
Actions.
Monitoring.
Accountability.
The terminology may continue to evolve.
Those responsibilities will remain.
The Leading Space perspective
At The Leading Space, we will continue to use AI Business Systems as our primary terminology for now.
It remains the clearest language across the markets in which our clients operate.
More importantly, our focus is not the name attached to the technology.
It is what the technology does inside the business.
A durable AI Business System should be designed around:
the business outcome,
the company's context and data,
clear ownership,
defined decision authority,
appropriate human control,
and an architecture capable of evolving as technology changes.
Whether the market ultimately calls the next generation AI, SI or something else, the core principle remains:
Build the business system so the architecture can outlive the terminology.
If the technology is evolving faster than your business architecture
When increasingly capable AI affects several departments, shared data, permissions, integrations or critical workflows, the challenge is no longer simply choosing another AI tool.
It becomes an Enterprise AI Systems question.
For a genuinely bounded business outcome, an AI Systems Build may still be the appropriate scope.