Smart Manufacturing
Beyond PLC Data: An Architecture for Industrial AI
The Stellantis plant in Goiana, Pernambuco, developed a scalable industrial data architecture that now supports more than thirty AI applications. Building on its existing Siemens infrastructure, the team standardized how industrial data is collected, contextualized, and…
How to Classify Risk in Industrial AI
How should a manufacturer decide whether an AI use case carries acceptable risk before deployment? Benson Chan of Strategy of Things answers an audience question on risk classification with a four-quadrant framework that maps decision severity…
How Industrial AI Earns Production Trust
How should manufacturers maintain AI consistency across a global factory network? When a model update resets the trust operators have built, do you interrupt automation to re-validate? Sanjay Mahato of Amazon Web Services and Tauseef Ahmed…
Scaling AI Past the Pilot Stage
Neil Smith of Schneider Electric and Andrew Waycott of TwinThread answer six audience questions on building the CFO business case for industrial AI, data readiness, OEM-operator data sharing, industry-specific adoption barriers, cybersecurity safeguards, and the organizational…
The Human Side of Industrial AI
Who owns the failure when an AI system acts without a human in the loop? How do manufacturers overcome workforce resistance that 25.7% of CPG companies cite as a barrier to AI scaling? Neil Smith of…
Edge AI, LLMs, and Digital Twins in Production
Should manufacturers run domain-specific small language models at the edge? Where do LLMs add value in manufacturing production planning? Can you test AI on a digital twin before production? Neil Smith of Schneider Electric and Andrew…
Edge Security and Lab-to-Factory AI
How should the edge be designed for security when AI applications interact with industrial control systems? Should university-industry projects follow product implementation discipline? Denis Leite, Director of Digital Transformation at Mekatronik, answers these audience questions from…
Why CPG Regulation Is a Data Problem
By 2030, food and beverage manufacturers are projected to lose 36% of potential revenue to inefficiencies, three percentage points more than life sciences. Life sciences companies built digital data infrastructure earlier, correlating with FDA compliance requirements…
Why Factory Data Never Reaches AI
Manufacturers have spent ten to twenty years installing sensors and connecting machines. The data flows, but it rarely reaches AI. At the Industrial AI Summit 2026, Jonathan Alexander of Albemarle Corporation, Peter Sorowka of Cybus, and…
What Plants Need for Prescriptive AI
Prescriptive AI tells plant operators which component to replace, which maintenance action to take, and when. Boris Scharinger, author of Industrial AI: From Pilot to Profit and R&D Excellence, DataOps and Master Data Management at Siemens,…
Should Pharma Build or Buy Explainable AI?
Should pharma build or buy AI explainability? Can you prove a source document was not altered? How do human reviewers keep up with AI output? Adam Procopio of Merck and Kristen Sauter of Adlib Software address…
How Should Pharma Handle Documents for AI?
At the Industrial AI Summit 2026, attendees asked questions about pharmaceutical document integrity that the panel did not have time to answer live. Adam Procopio, Scientific Associate Vice President at Merck, and Kristen Sauter, President and…