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Register and enrich leads, prepare follow-up and propose CRM updates rather than making silent changes.
AI automation for businesses
About this source
Gen8
Source: AI automation for businesses
Managed AI service for SMEs. We set up, connect and manage; you stay in control.
© 2026 Gen8 VOF · Dutch Chamber of Commerce 92978789 · Delft
AI automation
Get work done that gets stuck between systems
AI automation is not one technique or one tool. It is a workflow that picks up a signal, retrieves context, makes a proposal in the system where work happens and lets a person decide where appropriate. We configure and manage it.
- Human approval
- A log of every step
- Processing in the EU
What it is
Remove the handoff instead of typing faster
In most organisations, delays happen between tasks: the email waiting for someone to read it, the report that never becomes a task, the document manually retyped in another system.
AI automation addresses those handoffs. A workflow reads the signal, finds the context, turns it into a concrete proposal and prepares it where the next step should happen. A person reviews and decides; the workflow remembers and records.
Nine types of work
Where AI automation lands in practice
For each group, the site explains what a workflow does, the systems involved, the controls and how well the route is proven. If you prefer to browse by organisation type or see what this looks like in practice, organisation types and cases provide the shorter route.
Classify and route incoming email and propose a draft with the right context.
Meetings
From transcript to decisions and action items with owners and dates.
Documents
Extract data, check it against agreements and prepare it for processing.
Reporting
Fixed questions, fixed sources and an explanation of differences. Read only.
Knowledge
Answer questions from internal sources, with references and within the user's permissions.
Project work
Turn signals from conversations and channels into tasks for the right owner.
Website
Maintain content and keep public pages current, with publication by a person.
Monitoring
Monitor, notify and follow up when something falls outside agreed boundaries.
Technology choice
AI, fixed rules or existing automation
Not every process needs a model. Choosing the wrong technology costs more than doing nothing, so we ask this question before building.
| Fixed rules | Existing integration | AI workflow | |
|---|---|---|---|
| Fits | Work with a limited number of clear situations | Data that only needs to move from A to B | Work with free text, context and exceptions |
| In uncertain cases | Skips or fails | Produces incomplete or duplicate data | Flags it and submits the choice for review |
| Explainability | Fully predictable | Fully predictable | Proposal with source and log, decision by a person |
| Costs | Low and stable | Low and stable | Depends on volume, review and management |
Boundaries
When you should not want this
If a process is undocumented and changes every week, you automate ambiguity. If no one is assigned to review proposals, the output sits unused. And if a mistake has major, irreversible consequences, the action should not happen automatically, however well the model seems to work.
In those cases, the honest answer is to document the process first or solve it with a fixed rule. We prefer saying that before an engagement rather than afterwards.
How much time does it save?
That depends on volume and how many steps the workflow takes over. We only quote a figure once it has been measured for you, and publish customer results only with their permission.
Do we need to get our data in order first?
Not everything, but the source the workflow uses. Often the first benefit is making incorrect permissions or data visible.
Will jobs disappear?
In the processes we work on, what mainly disappears is handoff work: searching, retyping, forwarding and reminding. Assessment remains human work, and additional review work is created.
What happens when the model makes a mistake?
That is why the proposal is visible before anything is written and every step is logged. A person always approves actions with major consequences.
Does this work with our existing systems?
Often yes, through different routes: an existing integration, external MCP server or custom API development. The integration page states the route for each system.