Data centers are moving from monolithic electrical plants to modular power building blocks - standardized units that scale capacity faster while supporting higher-density, more dynamic loads.

Industrial Software‑Defined Automation (ISdA) refers to the execution of industrial control and automation functions, such as PLC logic, motion control, robot control, and process control, as software applications running on standardized hardware platforms rather than dedicated, proprietary controllers.

To provide our Advisory Service clients with holistic coverage of the various industrial and automation markets we cover, ARC publishes indices of revenues from automation and machinery companies as well as indices of revenues and CapEx from end user industries on a quarterly basis. This report is concise and focuses more on the quantitative than the qualitative aspects of the automation, end user, and machinery industrial markets.

Between 2024 and 2025 aerospace and defense companies accelerated their smart manufacturing initiatives progressing from experimental pilots to essential, scalable capabilities.

Cyber incidents are now a major cause of unplanned downtime in manufacturing, leading to significant financial and safety concerns. Consolidation of cybersecurity tools into unified platforms is a practical strategy to enhance detection, response, and compliance across IT and OT environments. Acronis is a supplier that has adopted a platform-centric approach that also leverages AI.

This report outlines the critical role of modern networks in enabling AI-ready manufacturing, the challenges involved, and the solutions that can help organizations successfully navigate the transition.

In a presentation at the ARC Industry Forum 2026, Jacco Opmeer, Principal Automation Engineer at Shell, discussed how owner-operators are moving from open-automation intent to implementation. He also described how Shell aligns architecture choices with engineering practice, supplier capability, and operational expectations.

Industrial AI does not eliminate control. It increases the importance of trusted, software-defined execution. ARC expects AI adoption to remain uneven and use case specific through the remainder of this decade, with measurable value delivered incrementally rather than through broad, synchronized shifts in spending away from control systems.

This year's workshop, sponsored by Valmet Automation, provided a wealth of insights from participants and ARC analysts alike. The emphasis was on viewing sustainability performance through the lens of operational decision-making quality. Progress in reducing emissions, waste, and energy use hinges significantly on an organization's ability to consistently make well-informed decisions, not just at the equipment level, but across facilities and throughout the entire value chain.

The automotive industry is changing rapidly in the face of new cost structures driven by the electric vehicle transition and fierce competition from China. In Audi’s view, the traditional model of delivering production equipment floor is outdated, and the future is software-driven production.

It’s been over three years since the Ethernet-APL specification was announced, so it’s time for an update!

DCS lifecycle services are key to managing modern industrial complexities and turning challenges into competitive advantages through expert support, seamless integration, and ongoing optimization.

Artificial intelligence is no longer an experimental add‑on for oil and gas manufacturers; it is rapidly becoming a defining capability for how operations are run, risks are managed, and value is created. The organizations that succeed will be those that integrate AI deliberately into their operating model—rather than treating it as a collection of disconnected pilots.

Industrial plant operations are evolving from traditional control systems to advanced AI-enabled automation. Dynamic digital twins, such as OmegaLand V4, play a key role in this evolution, supporting autonomous plant operations by enabling real-time analysis, simulation, and decision making. Dynamic digital twins can also address current industry challenges like non-steady operations, labor shortages, and environmental concerns.

The automotive industry is changing rapidly in the face of new cost structures driven by the electric vehicle transition and fierce competition from China. In Audi’s view, the traditional model of delivering production equipment floor is outdated, and the future is software-driven production.