Timeline for General Availability of SharePoint Data Source in Azure AI Search

hi Sam_Kumar​ The SharePoint Online data source for Azure AI Search is a very important capability for real-world enterprise search + AI scenarios.

Here’s what we know today:

1.Feature is currently in preview
Yes — the SharePoint Online connector is in public preview. It lets the Azure Search indexer crawl SharePoint libraries and lists, which is a big step forward for bringing enterprise content into your AI/semantic search pipelines. That preview has been working for a while and has been steadily improving

2.Microsoft has not published a firm GA date yet
As of now, there is no officially announced General Availability (GA) date in the public docs or Azure roadmap. Microsoft generally does not commit to GA timelines until a feature reaches a certain level of maturity and feedback stability.

This means:

• The feature is likely progressing toward GA, but
• They may be gathering telemetry and customer feedback from preview
• GA timing depends on feedback, quality, and adoption patterns, not just a calendar date

3.Why there’s no GA date yet
Unlike simple features, the SharePoint data source involves:

• Complex authentication models (Microsoft Graph, SharePoint APIs)
• Large data volumes
• Permissions and security trimming
• Complex content types (documents, lists, libraries, metadata)
• Enterprise compliance needs

Because of this complexity, Microsoft often extends the preview phase longer to ensure a solid GA experience.

While waiting for GA, you can:

Fully test in preview

Build your indexer, skillsets, and indexing pipelines now. This helps identify gaps early.

Provide feedback via GitHub / MS Docs

Preview feedback directly influences GA readiness and prioritization.

Monitor the Azure Updates page

Microsoft usually posts GA announcements here:

https://azure.microsoft.com/updates/

Search for:
“SharePoint data source Azure AI Search”

Check the public Azure roadmap

Some new features appear here before GA:

https://www.microsoft.com/azure/roadmap

Customers and partners who need early production support often:

• Use custom ingestion with Graph + Azure Cognitive Search indexer as a fallback
• Stage hybrid pipelines (Blob storage + SharePoint snapshots)
• Implement change tracking via Microsoft Graph webhooks
• Build intermediate ETL pipelines into Azure Data Lake for indexing

These approaches reduce risk while waiting for GA.

Mean while, Start building your indexing and semantic search logic now using the preview. That way, once GA arrives, you can flip the switch — and you’ll already have a tested pipeline.