Topics gives people and digital colleagues one place to work together. Not scattered chatbots, but teammates that can actually carry work forward.
Watch how Topics AI and digital coworkers are featured in the national Dutch television program 'De AI Storm'. Discover the future of agentic collaboration in practice.
Knowledge work shifts toward direction and judgment
People stay responsible for choices and quality. Digital colleagues take on more of the execution.
Digital colleagues handle repetitive tasks while people set priorities, review outcomes and decide what happens next.
Teams step in for approval, nuance and judgment instead of manually pushing every task forward.
Specialists spend more time keeping sources current and usable, and less time repeating manual work.
From chat streams to work built on context
Messages drift away. Structured context stays useful for both people and AI.
| Legacy platforms (Teams/Slack) | Topics (Native AI) | |
|---|---|---|
| Primary unit | Ephemeral channel (communication) | Topic (workspace with context and memory) |
| AI integration | Add-on chatbot | Part of the team and the workflow |
| Memory | Linear / token loss | Relevant context when it is needed |
| Automation | Rigid RPA scripts | Workflows that respond to events |
Someone still has to prompt each next step before work moves on.
Specialized digital colleagues can pick up full tasks and work alongside people.
Where context, work and execution meet
Topics gives every subject a fixed place so people and digital colleagues work from the same context.
Each subject gets its own environment with the documents, context and discussions that belong there.
Digital colleagues can work from Topics while using the systems your organization already depends on.
Digital colleagues can divide work among themselves and bring in the right specialist when needed.
You define behavior in plain language instead of custom code.
Who is this digital colleague and what are they allowed to handle?
What instructions, tone and guardrails define the role?
Which skills and events start the work?
Which systems and sources may this colleague use?
Triggers and feeds that keep processes going
Let digital colleagues act when something changes, instead of waiting for someone to type the next prompt.
Once AI starts doing real work, a feed gives more control than a chat window.
The feed shows what happened, in which order, and why.
People can monitor the work without interrupting every step.
Digital colleagues continue at system speed while people step in when needed.
People set direction. Digital colleagues take care of execution.
Less time goes to execution. More time goes to judgment, alignment and choices.
Offload repetitive work: Recurring analysis and information synthesis move to digital colleagues, so people can focus on the decisions that matter.
Always ready to help: Not waiting for prompts, but watching for signals and stepping in when the work calls for it.
You can see what an action or answer is based on. That is what makes AI usable in serious operations.
Each answer or proposal points back to the information it used.
You can trace which document, event or decision influenced the outcome.
Confidence comes from being able to verify the basis, not from taking the system at its word.
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If you want to see what this looks like in practice, we can show you where to start and what can deliver value quickly.
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