Prescriptive AI in the Factory: Accessible for SMEs or Enterprise-Only?
Prescriptive AI—the next wave of artificial intelligence that transforms data into prioritized, actionable recommendations—promises to reshape factories by cutting downtime, optimizing workflows, and even redesigning processes on the fly. But is this transformative power accessible to small and mid-sized manufacturers, or will it remain an enterprise-only advantage? With 98% of U.S. manufacturing firms classified as small businesses (SBA, 2025), yet most citing cost and integration hurdles as top barriers to AI adoption, this discussion goes beyond the hype. Panelists will examine practical requirements, affordability, and risk factors, weighing whether Prescriptive AI can be democratized—or if smaller players risk being left behind.
Data Sovereignty in Manufacturing: Building Trust with EU Reference Architectures
In today’s connected industrial world, data sovereignty is becoming a key differentiator for manufacturers seeking trust, flexibility, and compliance. While the Sovereign Cloud sets the stage for digital independence, the real challenge lies in ensuring sovereignty over industrial data itself.
Join our expert panel as we explore what it truly means not to have data sovereignty — from loss of control and vendor lock-in to limited interoperability — and how these challenges can put innovation and competitiveness at risk.
We’ll discuss how manufacturers can establish true data sovereignty through open technology stacks, interoperable data architectures, and compliance with the European Data Act. Learn how reference architectures in the EU help create trusted, secure, and scalable data ecosystems across the industrial value chain.
Garbage In, Garbage Out: Fixing Industrial Data Before It Hits Your AI Models
AI can’t fix bad data — it amplifies it. On the plant floor, one flawed data stream can cascade into failed AI rollouts, faulty predictions, or million-dollar supply chain disruptions. The real competitive edge isn’t just having AI models — it’s ensuring the data feeding them is accurate, contextual, and trusted.This session brings together leaders tackling the toughest step in industrial AI adoption: how to validate, clean, and structure data before it ever reaches an algorithm. Panelists will dive into:
• Why “data readiness” is now the biggest predictor of AI success.
• How frontline context (not just clean tables) builds trust in outputs.
• Governance frameworks and architectures that make industrial data decision-ready.
If you’re investing in AI for manufacturing, this is the session that shows how to avoid the costliest mistake: feeding your AI the wrong data.
Building Data Infrastructure for Predictive Operations
As manufacturers race to implement AI, predictive maintenance, and digital twins, many discover their biggest obstacle isn’t algorithms—it’s data infrastructure. This panel explores how to build robust time series data architectures that capture, store, and deliver high-velocity industrial data at scale.
Our panelists will discuss bridging OT/IT systems, maintaining data quality across legacy and modern infrastructure, and designing platforms that enable real-time intelligence.
Preparing Your Data Layer for AI-Driven Product and Supply-Chain Decisions
Most manufacturers are trying to “do AI” before they’re RAG-ready. This session explains what it means to have RAG-ready content — normalized, version-controlled, and auditable.
Key talking points:
• What “RAG-ready” means in the context of Digital Supply Chain.
• Why unstructured documents are the biggest blocker to AI adoption.
• Framework: Clean → Contextualize → Govern → Retrieve → Generate.
Closing the Skills Gap Before It Closes Your Factory
By 2030, 2.1 million manufacturing jobs may go unfilled (Deloitte). How can AI copilots, AR/VR training, and digital twins transfer knowledge from retiring experts to a new generation — before the skills gap cripples frontline operations?
Can AI Predict and Prevent the Next Supply Chain Disruption?
Global supply chain disruptions cost companies an average of 45% of one year’s profits over a decade (McKinsey).
Can predictive AI, digital twins, and real-time visibility tools finally give manufacturers the resilience they need — before the next crisis hits?
AI Advantage 2026: How U.S. Manufacturers Can Convert Innovation into Real ROI
HANNOVER MESSE 2026 is where AI meets industry innovation. This presentation features experts with deep experience and firsthand knowledge of the show—from creating buzz on the floor to driving post-event results. This session will share firsthand insights on how U.S. companies can strategically engage with global industry platforms, stand out among competitors, and leverage emerging AI solutions to boost visibility, accelerate customer engagement, and drive real results.
Key Takeaways:
• Leverage AI Innovation to Your Advantage: Position your solutions within the AI-driven industrial narrative to attract the right buyers and partners.
• Convert Conversations into Contracts: Proven methods to move beyond booth traffic and spark high-value discussions that translate into real deals.
• Prioritize Impact: Where U.S. manufacturing leaders should focus their time and resources to amplify visibility and deliver measurable ROI.
The goal is simple: understand how you can maximize your expertise in AI at HANNOVER MESSE for qualified lead generation and new opportunities for your business.
Bridging IT & OT Without Compromising Security: Lessons from the Field
The convergence of IT and OT brings enormous opportunity for efficiency and innovation—but it also introduces identity and trust challenges at scale. From connected devices to digital certificates, organizations must ensure that every system, asset, and user can be authenticated and secured. This session will share field lessons on building secure, interoperable environments that protect industrial operations while enabling the flexibility and agility modern enterprises demand.
