Artificial intelligence (AI) is the umbrella term for systems that solve tasks which would otherwise need human thinking; AGI would be an AI that learns and reasons as broadly as a person, and superintelligence (ASI) would be an AI that clearly outperforms people in almost every field. Only the first of the three exists today. What is really changing right now are AI agents: systems that do not just answer, but complete tasks step by step.
In this article we sort out the three terms, explain how an agent works, what computer use agents can do and what all of this means in practice for small and mid-sized businesses.
What is the difference between AI, AGI and superintelligence?
The difference lies in the breadth and level of ability. AI solves individual tasks very well, AGI would learn any intellectual task at a human level, and superintelligence would sit far above that.
| Term | What it means | Does it exist today? |
|---|---|---|
| AI (artificial intelligence) | Systems that solve specific tasks: writing text, recognising images, sorting data | Yes, part of everyday work |
| AGI (artificial general intelligence) | An AI that learns and understands new tasks as flexibly as a person, in almost any field | No, a goal of some research labs, timing disputed |
| ASI (artificial superintelligence) | An AI that clearly outperforms the best people in practically every field | No, so far a theoretical concept |
The philosopher Nick Bostrom made the term superintelligence widely known. He uses it for an intellect that far exceeds human cognitive performance in nearly every domain. That raises serious questions about control and safety, which researchers and policymakers are debating.
What is an AI agent?
An AI agent is a program that uses a language model as its "brain" to pursue a goal on its own. Instead of only writing an answer, the agent decides which steps are needed and uses tools to take them: calendar, email, CRM, database or a search function.
An example: you set the goal "Reply to new appointment requests and book free slots". A chatbot would only give you a reply text. An agent reads the request, checks the calendar, suggests times, books the appointment and sends the confirmation. We explain this in detail in What is an AI agent?.
How does agentic AI work, step by step?
Agentic AI works in a loop of four steps that repeats until the goal is reached or a limit applies.
- Plan: the agent breaks the goal into smaller steps. For example: read the request, find the customer in the CRM, find a suitable slot, draft a reply.
- Choose a tool: for each step it picks the right tool, such as the calendar lookup or the customer search. Standards like the Model Context Protocol (MCP) make these connections easier.
- Act: it carries out the step, such as a lookup, an entry or a draft.
- Check: it evaluates the result. If it fits, it moves on. If not, it plans again or asks a person.
The last step matters most. Because errors can add up over several steps, every agent needs limits: a maximum number of steps, a budget and approvals before important actions. This principle is called human in the loop. For a deeper introduction, read What is agentic AI?.
What are computer use agents?
Computer use agents operate a computer the way a person does: they see the screen through screenshots, move the mouse, click and type. Providers such as Anthropic and OpenAI introduced these capabilities in 2024 and 2025.
The advantage: such an agent can also work with software that has no interface (API), for example an older industry application or a supplier's web portal. The drawback: it is slower and more error prone than a direct connection, and on websites it can run into hidden instructions designed to manipulate it (prompt injection).
What does this mean for your business?
For small and mid-sized businesses, AGI or superintelligence is not a decision you need to make today. What matters is which recurring tasks an AI can already take over reliably.
Good fits are tasks with a clear goal, a lot of text and fixed tools:
- Sorting and answering enquiries: the agent handles routine questions, special cases reach you with a short summary.
- Preparing quotes: the agent gathers data from the enquiry and the CRM and drafts a quote for you to review.
- Reconciling data: comparing invoices, orders or appointments between two systems and flagging differences.
- Summarising research: keeping an eye on suppliers, tenders or competitors.
Less suitable are high risk decisions without human review, such as payments, contract changes or HR matters. The legal side counts too: the EU AI Act sets requirements for transparency and oversight. This article is not legal advice.
Checklist: is a task ready for an AI agent?
- The task comes up regularly, at least several times a week.
- The goal can be described in one sentence.
- The data needed is digital (email, CRM, calendar, spreadsheet).
- A mistake can be spotted and corrected before it causes harm.
- Someone will review and approve the results at the start.
- You know where the data is processed and have a data processing agreement.
Conclusion: do not wait for superintelligence, start smart
AI is a tool today; AGI and superintelligence remain open questions about the future. What already pays off are AI agents for clearly defined tasks, with limits and human approval. If you start now with one small, measurable task, you build experience and stay flexible, however fast the technology moves.
If you would like to know which processes in your business suit an agent, take a look at our AI automation service or tell us about your project.
