Allocators are under growing pressure to put AI to work on manager due diligence, and the natural first move is to point it straight at the documents on file: compliance manuals, completed DDQs, and policies. The assumption is that a capable enough model can read those documents and answer questions about them as well as a person would.
Whether that works depends less on the model than on how the underlying data is held. Any AI agent can only hold so much information in front of it at one time, so pointed at a stack of source documents, it reasons over the few it manages to take in and nothing beyond them. Hold the same information as structured data instead, with the key responses and figures pulled out of those documents and stored as discrete data points the tool can query, and it can work across every manager you oversee in a single pass.
That intermediate layer, the structured data layer, is what decides whether AI gives you answers you can rely on.