The Four Stages of a Chatbot’s Business Intelligence Evolution
I see four stages in the progression of chatbot-like AIs interacting with business systems for the purpose of providing actionable business intelligence.
Stage 1) Single Numeric Response
Bob, can you give me the order number that corresponds to customer number XYZ123?
Method: simple SQL query on one table. No need for translating back to natural language
Stage 2) Multiple Numeric Response
Bob, can you tell me if any orders shipped late yesterday?
Method: SQL query with some simple summarization. Possibly more than one table involved. Output will be in the form of a list
Availability: 6 months
Stage 3) Predictive Numeric Response
Question: Bob, how many of the orders we received today will meet the 2 day shipping window?
Method: predictive analytics applied to data queried from multiple databases. Response will need to be translated back to natural language to convey the nuanced nature of the response
Availability: 6 months to 1 year
Stage 4) Predictive Question Generation
Bob, what should I be worried about today in the shipping and customer service departments?
A combination of various machine learning techniques including deep learning (neural networks), analysis of unstructured data, k means clustering, regressions, and random forest.
Availability: 2 to 5 years