As enterprises grapple with an explosion of data and increasing pressure to make rapid, informed decisions, traditional Business Intelligence (BI) tools are reaching their limits. Static dashboards and complex query interfaces often exclude non-technical users, creating friction between data and action. Enter AI-native analytics—a transformative approach that integrates natural language interfaces (NLIs) with scalable machine learning (ML) to deliver intelligent, conversational decision systems.
This keynote explores how organizations can reimagine their analytics infrastructure by embedding AI into the very fabric of user interaction. Drawing on real-world implementations and cutting-edge research, we’ll unpack the architectural foundations needed to operationalize NLIs at scale—spanning natural language understanding (NLU), data context alignment, governance, and high-performance compute. We’ll address the core challenges of conversational systems in the enterprise: query ambiguity, semantic grounding, explainability, and scalability under dynamic workloads.
With AI-driven interfaces, business users can shift from passively consuming reports to actively engaging with data through dialogue—unlocking faster insight discovery and empowering decision-making at all levels. Attendees will leave with a strategic framework for building next-generation analytics platforms that are intelligent, adaptive, and truly human-centric.