AI is reasonably accurate at picking a category or an urgency level: in my experience, right about 19 times in 20. When it rewords original text, it can introduce subtle data loss or errors. The occasional junk is foundational to how the maths works, so I don’t think that problem goes away with the next model.
What it’s good at
- Triage. Read incoming tickets and emails, assign them to the right person, and raise critical ones to high priority. It augments the person doing triage; it doesn’t substitute for them.
- Metadata. Fill in the columns that replace folder paths and drive search, filtering and navigation. Tagging is what turns a library into something you can browse with refiners.
- Review flags. Audit policy content and flag what’s due for review.
- Extraction. Pull a date, an amount or a party name out of a document into a column.
Where to find it in Microsoft 365 and Dynamics 365
- SharePoint autofill columns, the one people forget. In a library, add a column and choose Autofill > Set up. You write a prompt per column, and the answer for each file lands in that column. They work with choice and managed metadata columns, so the answer comes from your list (overview). With Microsoft 365 Copilot licences, autofill is included in Copilot in SharePoint, formerly Knowledge Agent. Real-time autofill across a whole site costs Copilot Credits. Without Copilot, it’s pay-as-you-go document processing, the old Syntex, and so is taxonomy tagging against your term store.
- AI Builder in Power Automate. Category classification comes as a standard model that sorts customer feedback into six fixed categories, or a custom one trained on your own labelled data. Either returns a confidence score with each label. A prompt does the same job when you can’t label enough examples. Check the licensing: new customers buy Copilot Credits, and new or renewed licences stop including AI Builder credits from 1 November 2026.
- Dynamics 365 Customer Service. Unified routing can attach skills to incoming work with the intelligent skill finder, an AI Builder classification model, and Copilot labels incoming emails as positive, negative or neutral. For drafting, Microsoft says to “always review the response” before a Copilot-drafted email goes to a customer.
Rules that keep it honest
- Give it a fixed list. A choice column, a term set or a set of queues. A free-text answer is back to rewording.
- Use the confidence score. Below your threshold, a person decides.
- Keep the original. The label sits next to the source text. It never replaces it.
- Design the categories yourself. Machine learning can’t yet work out what’s important to your business. AI-made structure is better than the mess most organisations have, but it’s not as good as structure people designed. It’s why I think information architecture will be one of the last jobs to go.
- Treat the content as untrusted. Text inside a document or email can carry instructions, and there’s no fully safe way to screen for that. Don’t let a label trigger anything you can’t undo.
- Don’t send unreviewed AI output to people, internally or externally. Drafts are fine; a person checks them and sends them.