I work at Retool, and probably the majority of our business today is "replacing SaaS with citizen-developed apps". I think that a lot of these CRUD-y SaaS products (which is, really, what BI is) will disappear over the next few years. The bottlenecks I see:

* Data quality — we've seen Databricks / Snowflake schemas with 10^5 tables. Just putting a LLM on that doesn't work - you do need some sort of semantic layer. This is especially bad since LLMs are like slop cannons — if you ask it to prove X with the data, it will build you an app / visualization that proves X.

* Deduplication — it turns out many people want moderately different views of the same data. How can you host everything centrally and DRY everything out such that you can guarantee correctness?

* Writing data back — this is where it gets really hairy. Dashboards that only read data from Databricks is dangerous insofar that data can leak. But once you start needing to write data back, you need access to APIs / MCPs... and then you want some sort of authorization layer (since many SaaS apps don't have great authorization within themselves).

Obviously we work on quite a bit of this at Retool, but we are always looking for ideas on how to make this better. We believe that many things should be in a platform (e.g. centralized data connectivity, authentication, authorization, etc.) setup by engineering, and then non-developers can go crazy generating safe apps.