As large language models become embedded in enterprise workflows, analytics is shifting from static dashboards to AI-driven, conversational decision systems. Traditional metrics and reports were designed for human interpretation, not for reasoning by intelligent agents.

This session explores how LLMs are transforming analytics by acting as a semantic and reasoning layer over governed data. We’ll examine how natural language queries, automated insights, and AI-generated explanations are changing how teams consume metrics and make decisions. The talk will also address critical challenges such as data trust, hallucination risks, metric consistency, and governance in AI-powered analytics systems.

Attendees will gain practical insights into building analytics platforms that remain accurate, auditable, and decision-ready in an AI-native enterprise.