AI that answers cross-functional questions
Per-application AI assistants answer questions about their own application. Business questions are rarely that tidy. This paper examines what is required for an AI layer to reason across HR, payroll, sales, operations and finance simultaneously, and where that changes decisions.
The value of an AI layer is proportional to the breadth of data it can reason over, and inversely proportional to how much you have to check its working.
Overview
Per-application AI assistants answer questions about their own application. Business questions are rarely that tidy. This paper examines what is required for an AI layer to reason across HR, payroll, sales, operations and finance simultaneously, and where that changes decisions.
You'll learn how to
Frame business questions that span multiple functions
Understand the data prerequisites for cross-module reasoning
Evaluate AI answers through citation and traceability
Apply permission scoping so AI respects existing access rules
Key takeaways
- 1
Single-application assistants cannot explain multi-cause outcomes.
- 2
Citations back to source records are essential for trust.
- 3
Permission scoping must apply to AI exactly as it does to users.
The value of an AI layer is proportional to the breadth of data it can reason over, and inversely proportional to how much you have to check its working.