John Rinaldi to Address Industrial Data Chaos at Automate 2026

The gap between theoretical AI potential and plant-floor reality remains a persistent bottleneck for modern industry. While manufacturers invest heavily in advanced algorithms, they frequently struggle with legacy equipment that lacks standardized naming, consistent units, and necessary context. Rinaldi argues that this "data noise" causes AI models to drift and eventually fail at scale, effectively wasting the 60% of operational technology data that currently goes unanalyzed.

During his presentation, "Beyond the Algorithm: Standardized Manufacturing Data Models as the Foundation for Scalable Industrial AI," Rinaldi will offer a roadmap for moving past raw, context-free PLC inputs. He intends to demonstrate how implementing metadata, schemas, and standard APIs like OpenAPI can transform fragmented information into structured, actionable intelligence. Attendees can expect a technical breakdown of how to govern data models across entire enterprises, along with a critique of legacy historian systems that often trap users in inefficient subscription cycles. The session takes place June 23rd at the Automate Innovation Stage, supplemented by live demonstrations of modern historian software at RTA’s Booth 3723.