In “2025 an AI Odyssey” we’re back in AI territory — this time fresh off our AI Research Day, where 16 people from 12 organizations came together to compare notes, ideas, and hard-earned lessons from the industrial frontlines.
Christian and Michael unpack what makes industrial AI different from “AI in general”: the stakes are higher, the margins smaller, and “pretty good” isn’t good enough when safety, quality, uptime, and compliance are on the line. We talk about what that means for real-world deployments — especially when models have to operate in messy, legacy-heavy environments.
We dive into the big topics that shaped the day:
Why industrial AI is special — and why consumer-style assumptions don’t transferHallucinations in production: how to reduce them, contain them, and design systems that stay trustworthyReasoning quality as a requirement: what “good enough” reasoning looks like for engineering and operationsReference architectures: do we need one, what should it include, and where do today’s patterns fall shortThe elephant in the room: legacy systems with little to no semantics — and how that blocks real AI valueAnd finally, we tackle the key question: How can we actually leverage industrial data if it doesn’t come with rich meaning?
Our answer: you need a Digital Thread system that introduces semantics, connects context across tools and lifecycle stages, and turns data into something AI can reason over — not just statistically, but engineerably.
If you’re building or evaluating AI for industrial use cases — or you’re wondering why pilots stall after the demo — this episode is your map for the odyssey ahead.
Der Beitrag #22 2025 an AI Odyssey erschien zuerst auf Elevating Patterns.