I've been thinking about the potential of integrating our internal documentation and code into a Retrieval-Augmented Generation (RAG) system, especially since I've recently set one up for our team's wikis and resources that has received positive feedback. I'm curious why more teams haven't adopted this approach. What are some of the barriers or challenges stopping your organization from making this shift?
5 Answers
Honestly, the setup can be tricky! I’m curious about how you handle updates to ensure your RAG system stays current with your documents. Do you do regular rebuilds, or is it more of an incremental change process?
There are several reasons! First, compliance issues can make companies hesitant to adopt AI tools. Many also don’t fully trust AI, even when it’s hosted internally. Plus, getting a system set up can require extra manpower that teams may not be willing to allocate right now.
For a lot of teams, it's just not a priority right now. They’re focused on more immediate needs like reducing manual processes instead of implementing a system that, while searchable, might not seem essential right away.
There’s a lot of skepticism about AI. Many feel it can’t provide reliable results compared to traditional methods. Investing time and resources into a system that might not get reliable outputs can be daunting, especially when existing tools already perform similar functions.
If companies have Microsoft 365 with a Copilot license, they can easily integrate SharePoint and utilize it as a data source. It seems that’s a great starting point for building these sorts of systems.

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