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Reshaping Grid and Data Center Power Strategies July 7, 2026 | Control & Safety Systems, Data Centers - Why this matters now The AI revolution is here, and it comes with a very real and growing demand for power. As AI capabilities become embedded into everyday tools and industrial systems alike, the energy required to train and operate these models has grown dramatically. Emerson experts Brett Benson and TJ Surbella explain that the… Read More
Cooling Cannot Run on Guesswork: Why Measurement Confidence Matters from Day One in Data Centers July 3, 2026 | Data Centers, Measurement Instrumentation - As artificial intelligence continues to reshape data center infrastructure, cooling systems are quickly becoming one of the most critical factors in determining performance, efficiency, and uptime. A recent article published on Automation.com, Cooling Cannot Run on Guesswork: Day One Measurement Confidence for AI Data Centers, highlights how rising compute densities are forcing a fundamental rethink… Read MoreLatest Posts
Mining Reliability Starts with Better Data, Not More AI
TL;DR Mining operations generate vast amounts of asset data, but data quality and context remain major challenges. Industrial AI delivers the greatest value when supported by integrated, structured, and governed data. Modern predictive maintenance solutions combine...
Why Data Centers Are Rethinking Measurement Infrastructure
AI workloads are pushing rack densities to 100 kilowatts per rack or more, and the liquid cooling loops that support them add complexity that commercial meters were not built to handle. Any service interruption carries significant financial consequences through service-level agreement penalties. In some AI-focused facilities, cooling accounts for roughly 30 to 40% of total facility energy use, so measurement accuracy directly affects both cost and uptime.
Smart Instrumentation for Specialty Chemical Manufacturing
Unlike large continuous plants, specialty chemical sites often make many products with frequent changeovers, so flexibility, speed, and quality control matter more. Off-spec batches must be downgraded, reworked, or scrapped, and a missing feedstock discovered mid-campaign can be a major loss. Safety risks from toxic, hazardous, and flammable materials are present every day. Accurate, reliable measurement gives engineers the data they need to manage all these pressures at once.
AI Data Centers Need a Different Automation Strategy Than Traditional Data Centers
TL;DR AI training facilities operate very differently from traditional enterprise data centers. High-density AI workloads create dynamic power and cooling requirements that traditional infrastructure was not designed to handle. Many AI data centers rely on...
A Systemic Approach to Optimizing Fleet Efficiency
Most people likely have a fairly simple idea of large ship operations. The schedule to get from point A to B calls for a specific speed to complete the distance on time, so the bridge orders the engine room to run as necessary to maintain the required speed. Done. It...
Turning Asset Health Data into Action with Industrial AI
TL;DR Many organizations collect large volumes of machine data but still struggle to reduce avoidable failures. Reliability teams need actionable insights, not more raw data or disconnected alerts. AI can accelerate reliability workflows, but only when it is paired...
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This blog features expert perspectives from Emerson's automation professionals on industry trends, technologies, and best practices. The information shared here is intended to inform and educate our global community of users and partners.










