01
Media breaks
Email, Excel, CRM, file store. The same case, four programs, errors included.
AI automation
AI automation for companies
Data transfers, inbound email, approvals and filing often still run by hand. I automate the flow and connect Microsoft 365, APIs or existing tools. Without replacing the IT landscape.
The problem
The same manual work between systems, every day
Someone copies data from the ERP into Excel, files attachments in SharePoint or chases approvals by email. That is not an AI show. That is a process without a fitting interface.
02
AI as the wrong fix
A chatbot does not replace a missing interface. If the trigger is clear, you often need automation rather than a language model.
03
Standard software at its limit
Power Automate or an iPaaS platform covers a lot. The rest is business logic that no standard connector maps.
The solution
Workflows with targeted AI, not AI for its own sake
I describe trigger, data, exceptions and success criteria. Then the tech: Microsoft 365 and Graph, n8n or Make, Python jobs and REST APIs. Where attachments arrive unstructured, a model joins in.
Example invoice intake: detect the email, read the attachment, process structured formats automatically, flag unclear PDFs and write to SharePoint. The business logic stays even if the model used changes.
Typical stack
- Microsoft 365, SharePoint and Microsoft Graph
- n8n, Power Automate or custom jobs in Python
- Extraction with a model when PDF or free text must be processed
- Azure or local infrastructure, depending on data risk
- Tests, logging and documentation so your team can run it later
Process
AI process automation for companies
AI process automation combines classic workflow automation with targeted AI. Clear rules and interfaces take recurring steps. AI joins where content must be understood, classified or extracted from unstructured documents.
That way you can process emails, read documents, move data between systems or route cases automatically. Not every step needs a model. Flows stay traceable and independent of a single vendor.
If the challenge is mainly making internal knowledge findable, an AI knowledge base for companies is a better fit.
In practice
Which business processes can be automated?
Especially interesting are flows with recurring data, a clear trigger and several manual steps in between. The point is not to use as much AI as possible, but to make a process measurably simpler, faster or more reliable.
01
Invoice intake
Inbound by email, detection, filing and status. Unclear cases go to people instead of stalling in the process.
02
Applicants and inbound mail
Detect attachments, classify and route. Less copy-paste in the specialist team.
03
Data between systems
What someone types today runs as an automated job. CRM, ERP and lists are connected instead of exported by hand.
04
Approvals and tickets
Pre-qualify, route and document cases. The decision stays with the human where it belongs.
Questions
Common questions about AI automation
Does every automated process need a language model?
No. Many flows first need an interface and clear rules. I use AI where unstructured content must be processed, for example PDF, email or free text.
Can the existing Microsoft 365 landscape stay?
Yes. Typical is a connection via Microsoft Graph, SharePoint, Outlook or Power Automate. Plus n8n, Python or APIs where standard connectors are not enough.
What is the difference from a chatbot?
A chatbot does not replace a missing interface. If the trigger is clear, you often need automation rather than a chat window.
How do I start without an internal automation team?
With one concrete flow: trigger, data, exception and success criterion. I build, document and hand over so your team can take over operations.
Walk through the process in 15 minutes
Which trigger, which systems, where AI is actually needed. Non-binding. After that you know whether a concrete setup is worth it.