If 90% of operational truth lives in documents that AI cannot read, how do manufacturers move from insight to action? This AI Manufacturing Day 2026 panel tackled the brownfield reality: plants never designed for AI, critical data trapped in unstructured formats, and why 60% of agentic AI projects are projected to be abandoned this year. Hamish Mackenzie (IIoT World) moderated a discussion with Chris Huff and Anthony Vigliotti (Adlib Software) and Mathias Oppelt (Siemens). The panel dissected where AI stalls in industrial environments and what it takes to build a trust layer for agentic workflows. Mathias Oppelt explained why general purpose AI falls short in industrial settings. Large language models trained to generate plausible text are not sufficient for industry, where reliability must be proven and a wrong answer can cause physical harm. Industrial AI must speak the language of engineers: understanding drawings, simulation models, and technical context beyond words. He shared a recent example where an 86-year-old engineer had to be hired back to resolve a line shutdown that cost $1.5 million over four weeks, because no current staff had the legacy system knowledge. Chris Huff outlined the shift from systems of insight to systems of action. Agentic AI is real today for high-volume, lower-stakes work like procurement, contract review, and supplier onboarding. It is not yet real for high-stakes, low-volume decisions where a wrong answer means a recall or safety event. He identified three places where pilots consistently stall: ingestion of messy multi-format documents, validation and traceability back to source, and integration into PLM, ERP, and QMS systems. Anthony Vigliotti proposed treating manufacturing documents as evidence, applying standards of relevance, reliability, authenticity, and chain of custody. He highlighted a problem many overlook: AI systems forced to clip relevant information due to context window overruns, leading to incomplete outputs that drive real operational consequences when acting on those outputs. This session was sponsored by Adlib Software. Editorially independent.

Behind the headlines and policy debates, a wave of technical advances — from additive manufacturing to a surprising stainless steel alloy — is steadily expanding what clean hydrogen can do.

Before David Erhard was building communities for one of the world's largest industrial companies, he was doing it for EA Sports and FIFA. His path from Nuremberg to the gaming industry and back again turns out to be surprisingly relevant, and it shapes how he thinks about everything SXC is trying to do.

We are launching a new community survey to understand your perspective on the intersection of AI and workforce transformation.

Digital twins are being put to work across industrial operations, aerospace, healthcare, and everything in between. This edition of Industry Signals revisits the topic with a focus on deployment of this technology as use cases grow more demanding, as well as what technology leaders get wrong at the start of a digital twin investment.

Siemens has launched Eigen Engineering Agent, a purpose-built AI that connects directly to TIA Portal and understands your actual project context to deliver ready-to-use PLC code, HMI scripts, drive configurations, and more. Unlike generic AI tools, Eigen uses multi-step reasoning and self-correction to complete engineering tasks end-to-end, not just generate suggestions. Piloted with over 100 companies across 19 countries, it delivers up to 5x faster execution and 50% greater efficiency — and TIA Portal users on V19, V20, or V21 can sign up for a trial now.

Every spring, Stanford's Human-Centered AI Institute releases its AI Index: a comprehensive, data-driven look at the state of artificial intelligence across research, industry, policy, and public opinion. The 2026 edition, published this month, draws on data from McKinsey, GitHub, Lightcast, Epoch AI, and dozens of other sources. The headline finding is not that AI is plateauing. It is accelerating, and the implications are spreading well beyond the lab.

Robots are leaving the lab and entering factories, logistics operations, and public spaces faster than most predictions anticipated. This edition of Industry Signals examines what is driving the numbers and what still needs to fall into place before the next growth threshold is crossed.