If you already pay for ChatGPT, Claude or Microsoft 365, the arrival of another AI term can feel like another thing to keep up with.
My starting point is simpler: can your team use what you already have to finish a real piece of work?
“Super Intelligence”, or SI, is getting attention. It is worth understanding the term before changing your tools or spending money around it.
What does SI actually mean?
There are two uses to separate. In research, superintelligence describes systems much smarter than humans, as outlined in OpenAI’s 2023 research note.
In this week’s US announcements, it is also a change in official language. President Trump’s 29 September order directs the executive branch to use “Super Intelligence” and “SI”. Its initial definition includes technologies already covered by the existing AI definition.
The same week brought a safety accord signed by six technology companies and an announced federal coordination task force. These are developments in policy and oversight. They do not, by themselves, show that a new level of capability has arrived in your subscription.
What may change around you?
I expect more SI language in product descriptions, sales pitches and company branding. That is my expectation, rather than a confirmed change across the market. When a vendor uses it, ask them to show what the product can do with your actual work.
The same attention could reach .si domains. They already exist: IANA lists .si as Slovenia’s country-code domain, registered in 1992. It is not a newly launched extension for superintelligence.
Some founders may choose it for the initials. A wider buying rush is still a prediction. I would make that a separate branding decision, after checking whether the address makes sense for your customers.
For a business in Dubai, the immediate opportunity is improving how the team uses AI: shared company context, reusable instructions and an agreed way to review the output.
A practical next step this week
Take one repeated job, such as preparing a customer proposal. Build a shared workflow around it:
- Define the finish line. A proposal ready for review, with the right scope, terms and missing information flagged.
- Give it approved context. Your service details, pricing rules and a good example. Keep customer records in their existing system of record.
- Make the routine reusable. Save the instructions in a shared AI workspace and name the person who approves the result.
- Test three real examples. Check accuracy, time taken and how much correction each draft needs.
A workflow someone else can use tomorrow, with clear inputs, a repeatable output and a review step.
That gives you evidence for the next decision. You can then decide whether a CRM connection, automation or wider rollout is worth adding.
Before buying another subscription, try this with one you already pay for. Bring one recurring task and a sample of a good result. That is where I would start an implementation conversation.