aveva.com

As operational data initiatives grow, so does the need to expand who can participate in connecting, configuring, and managing industrial data. In my role at AVEVA, I frequently hear from customers, partners, and AVEVA™ PI System™ administrators who have spent decades turning operational data into business value.

In the north of the Iberian Peninsula, frequent and severe droughts have made water, once abundant, a much scarcer resource. And for Ence, Europe’s largest producer of eucalyptus pulp products, this is an operational liability. A shortage of water doesn’t just stress the system. It shuts it down. In 2023, this lack of water cost them 15 days of downtime. Not a slow-down. Not a near-miss. Fifteen lost days of production.

Industrial innovation holds much potential. The challenge is turning that potential into solutions that can be trusted, adopted and scaled. We often find that technologies perform well in controlled environments but struggle when faced with the realities of live operations, legacy systems and human behaviour. That is why test beds are becoming such an important part of the innovation ecosystem.

Key takeaways from the 2026 AVEVA Utility Executive Summit Utility readiness is no longer defined by how well you can forecast the future—it’s defined by how confidently you can make near-term decisions under uncertainty. At the 2026 AVEVA Utility Executive Summit, executives and regulators described a demand environment shaped by AI-driven large-load growth, accelerating electrification, and rising expectations for reliability, resilience and affordability—all at once.

At AVEVA World 2026 in Milan, attendees were introduced to the next phase of CONNECT’s industrial intelligence journey—an evolution that will make it easier for users to manage, find, and apply industrial information wherever and however matters most. These changes focus on enhancing everyday workflows while also introducing new capabilities that help extract even more value from the platform.

In pulp & paper operations, even small improvements—fewer breaks, reduced variability, better energy intensity—translate into major financial and sustainability outcomes. AI is gaining traction because it can help teams stabilize performance across complex, interconnected processes. But success depends less on algorithms and more on whether the mill is truly data ready.

Chemical manufacturers are being asked to improve asset performance, quality, safety, and decarbonization—often at the same time. AI is becoming a practical lever to meet these demands, not because algorithms are suddenly magical, but because the optimization and diagnostic space has outgrown what manual analysis and point solutions can sustain. The catch: many AI programs stall for a simple reason. The limiting factor isn’t the model—it’s the data.

Read on for: Nutrien: Scaling expertise across facilities How Nutrien centralized its nitrogen production network into a single operations center, giving engineers enterprise-wide visibility and the ability to drill from fleet to facility to individual asset ArcelorMittal: Scaling expertise across operations How ArcelorMittal connected its pit-to-port iron ore network in a single environment, shifting decision-making from local optimization to system-wide coordination ADNOC: Scaling expertise...

Industrial operations teams are under pressure to modernize without disrupting what already works. System integrators and system builders are being asked to deliver projects faster, support more connected architectures, improve cybersecurity posture, and create systems that can scale from edge operations to enterprise-wide visibility.

Posted: July 09, 2026 Across shipbuilding, offshore operations, and maritime infrastructure, organizations are facing mounting pressure to modernize operations, improve efficiency, strengthen sustainability efforts, and navigate increasing project complexity with less resources and time than ever. Digitalization is accelerating rapidly across every segment of the industry, yet amid this momentum, one important question continues to surface: Where is the measurable value?