Process excellence teams are drowning in dashboards but starving for insight. Traditional BI tools surface what happened, not what's about to go wrong or what to do about it. In this session, we explore how combining a semantic layer with AI-native monitoring and Model Context Protocol (MCP) creates a new paradigm: a process intelligence layer that not only tracks KPIs consistently across the organization, but proactively alerts teams, diagnoses root causes, and surfaces recommended actions, all in natural language.
Join this session to learn a concrete framework for embedding AI into their PEX function without rearchitecting their data stack.
Key highlights:
Discover how AI-powered anomaly detection and threshold monitoring can catch process deviations before they become performance crises
Learn how a semantic layer eliminates conflicting definitions so AI agents are reasoning from a single source of truth across every team and tool
understand how AI agents connected to a governed metrics layer can automate routine analysis, freeing practitioners to focus on high-value transformation work
See how Model Context Protocol enables business users to query, diagnose, and act on process data in plain language, without writing a single query
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