Conceptual

Power BI Copilot Inconsistency Between Vague and Specific Prompts for Total Sales in December

The core principle asserts that non-deterministic behavior in analytical AI systems arises from semantic ambiguity within natural language prompts, creating a variance between user intent and model interpretation across different execution contexts. This phenomenon is defined as "prompt-induced variability," where vague specifications fail to constrain the latent space sufficiently for consistent retrieval of temporal metrics or data subsets. Within the domain of Human-AI Interaction in Analytics, this theory establishes that reproducibility depends on formally specifying boundary conditions (e.g., date ranges) and selection logic rather than relying on semantic inference alone.