What a future Business Intelligence can look like? Usually, I'm skeptical about "disruptive" ideas like natural language queries or automatically generated analytical narrations (although, I respect the research effort), but recently I saw something that for the first time looked really interesting, if you apply it to data analysis. I will tell what it is shortly, but first I have to explain my skepticism.
Typing in natural language queries won't work because it's no better than writing SQL queries. Syntax is surely different, but it still has to be learned. It doesn't provide the expected freedom, like SQL didn't. Besides unexpected syntax restrictions (which has to be learned by user), queries quickly become long and complicated. I played a bit with NLP (natural language processing) queries done in Prolog in my school years and have a bit of understanding of the complexities related to NLP.
This can be somewhat mitigated by voice input, however virtual assistants like Siri/Alexa/Cortana are built around canned responses so it won't work either, because analytical ad hoc queries tend to be very different, and they always have a context.
Now, here is the promising technology. It's called Viv and I highly recommend watching its demo (it's about 30 minutes):
Two things that make Viv different: self-generating queries and the the ability to use a context. This can potentially make voice-based interactive data analysis finally possible. Not only can a service like Viv answer queries, e.g. "How many new customers did we get since January", you should be able to make it actionable. How about setting up alerts, like this: "Let me know next time when monthly sales in the West region drop below 1mln. Do it until the end of this year"? Or, sharing "Send this report to Peter and Jane in Corporate Finance department". Such virtual data analyst can participate in meetings, answer spontaneous questions, send out meeting results -- all done by voice. Quite attractive, isn't it?
Data analysis is a favorable area for artificial intelligence because it has a relatively small "universe" where entities (customers, transactions, products, etc.) are not so numerous, and their relationships are well understood. If you ever tried to design or analyze a conceptual data warehouse model, then most probably you have a good picture of that "universe".
And it seems like right technology to operate with this "universe" might arrive soon.