AI in SharePoint: What It Does and How to Use It

What it is

AI in SharePoint started life in September 2025 as ‘Knowledge Agent’. In March 2026, Microsoft rebranded and refreshed it as AI in SharePoint, expanded its capabilities, and rolled it to Public Preview. It went generally available in May 2026. The headline capability: SharePoint sites, libraries, pages, and lists can now be built using natural language. Tell SharePoint what you want (‘a site for our HR team with a policies library and an onboarding page’); AI in SharePoint plans and builds it.

For SharePoint admins and site owners, this is meaningful. Building a well-structured SharePoint site has historically required technical knowledge, time, and judgement about information architecture. AI in SharePoint compresses the technical knowledge requirement — the structural decisions are made by AI, the user describes intent in plain English. The judgement still matters (and AI sometimes gets it wrong), but the floor of who can build SharePoint just dropped considerably.

The more strategically interesting part: AI in SharePoint automatically extracts and applies metadata to content. Upload files into a library, and AI in SharePoint reads them, identifies their type, department, status, topic — and applies metadata columns accordingly. The library adapts as content evolves. This is one of the first SharePoint features that genuinely makes metadata ‘just happen’ rather than requiring users to tag manually. Verify the auto-applied tags against your standards before fully trusting — AI gets it right often but not always — but the direction of travel is unmistakable.

Why it matters

Three reasons this is significant for any SharePoint user or admin:

• Non-technical users can now build sites. The ‘I need IT to set this up’ bottleneck shrinks. Marketing, HR, project teams can describe what they need and get a functional site without a SharePoint expert.
• Metadata auto-application is real. The biggest barrier to good SharePoint structure has been users not tagging content. AI in SharePoint tags it for them. This dramatically improves Copilot accuracy across the tenant — because Copilot relies on metadata to find and rank content.
• Existing SharePoint expertise is more valuable, not less. AI in SharePoint accelerates the build, but architectural decisions (information architecture, governance, lifecycle, permissions) still benefit from human judgement. The skill is moving from ‘how to click through SharePoint setup’ to ‘how to design SharePoint structures the AI then builds’.

When to use this

• When you need a new SharePoint site and don’t want to build it manually.
• When you have a library full of untagged content and want metadata applied retroactively.
• When you’re evaluating whether AI in SharePoint can solve your team’s structural problems before reaching for the File Sanity Kit’s Container Method.
• When you’re explaining to leadership why SharePoint is getting more usable without a major investment in admin tools.
• When you’re preparing for Copilot rollout and need metadata in place fast.

How to do it

1. Confirm AI in SharePoint is enabled in your tenant. It went GA in May 2026 but rollout is staged. Check SharePoint admin centre → Settings → AI in SharePoint.
2. Start small. Create a non-production test site (e.g. a sandbox site you can delete). Use AI in SharePoint to build something simple — a library with three columns and a page. Watch what it produces.
3. Try natural-language site building. In SharePoint Start page → Create site → Use AI in SharePoint. Describe the site you want in detail: who uses it, what it stores, what structure it needs.
4. Review the build before publishing. AI in SharePoint will make architectural choices (folder structure, column types, permissions defaults) that match its interpretation of your prompt. Some may not match your standards. Review every part before committing.
5. Test metadata auto-application. Upload a small set of files to an AI-managed library. Check what metadata it applied. Verify accuracy on a representative sample (10-20 files) before trusting at scale.
6. Pair with your existing methodology. If you’ve already invested in the Container Method, document types, or naming conventions, give AI in SharePoint examples or prompts that align with your standards. It learns from explicit instruction better than it guesses.
7. Document what works for your organisation. The first AI-built site that works well becomes a reference. The first auto-metadata pattern that works becomes a model. Build internal patterns rather than starting fresh each time.

Best practices

• Treat AI in SharePoint as augmentation, not replacement, for SharePoint design skill. Architectural judgement still matters; AI handles execution.
• Verify auto-applied metadata on representative samples before trusting at scale. Don’t assume because AI tagged 50 files correctly that it tagged all 5,000 correctly.
• Build clear governance around AI-generated sites and metadata. Decide who reviews, who approves, who can override.
• Use AI in SharePoint to accelerate routine builds; reserve human design for mission-critical sites with strict information architecture or compliance needs.
• Combine with the structural metadata patterns from the Metadata deck (Document Type, Department, Status). The patterns work whether metadata is applied by humans or by AI.

Common mistakes

• Letting AI in SharePoint build production sites without review. Even when it gets the structure right, the judgement calls (who has Edit, what’s the lifecycle, what’s the retention) need human ownership.
• Assuming auto-applied metadata is right just because it’s applied. Verify on samples; spot-check periodically.
• Skipping the information architecture conversation because ‘AI will figure it out’. AI in SharePoint executes architecture; it doesn’t replace architectural thinking.
• Letting AI in SharePoint loose on legacy libraries with thousands of files without testing on a subset first. Mass auto-tagging can produce mass mis-tagging if the AI’s defaults don’t match your context.

FAQ