Smart Manufacturing
From 8 Hours to 20 Minutes: Inside P&G’s Warehouse AI Transformation
Daily workforce planning at Procter & Gamble's manufacturing campuses used to take eight hours per shift. Planners arrived long before their teams to map out inbound deliveries, outbound trucks, production schedules, and variable labor. But within…
How Teva Selects AI for 30 Factories
Teva Pharmaceuticals evaluated approximately 300 technologies in one year while building an open innovation platform across its 30-factory network. Operations account for around 70% of Teva's cost structure, which means efficiency gains in how those factories…
Why Pharma AI Must Pass ALCOA
When an AI agent recommends a process change on a pharmaceutical production line, the recommendation itself is secondary. The defensible record of how the agent reached that recommendation is the product. At the Industrial AI Summit…
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…