In a recent LinkedIn article, Emerson’s Gertjan van der Ven, Vice President of Global Project Pursuit, argues that while boardrooms stay fixated on foundational models and enterprise chatbots, Artificial Intelligence (AI) is already doing the harder work on the plant side of the fence. He frames the shift as a quiet revolution playing out across seven distinct battlegrounds, from subsurface analysis to the data fabric that ties everything together.

Why It Matters

For automation project leaders and process operations leaders, the practical question is no longer whether AI belongs in industrial operations. Gertjan makes the case that unplanned downtime, slow exploration cycles, manual risk management, and disconnected supply chains have persisted for decades because the available solutions were not mature, reliable, or connected enough to work as a system. What has changed is not the pain point but the integration. The seven areas he outlines now function together, backed by an AI layer built for mission-critical environments.

Key Takeaways

• AspenTech Subsurface Intelligence (ASI), launched in September 2025, is a cloud-native, agentic environment that collapses multi-disciplinary subsurface silos from months into days.
• AI-driven real-time drilling optimization is producing measurable reductions in Non-Productive Time (NPT) and drilling cost per foot, with Emerson instrumentation and DeltaV control systems feeding the data.
• Aspen Mtell‘s January 2026 release added asset-specific templates, direct integration with Emerson’s AMS Machine Works and vibration monitoring, and seamless handoff into enterprise asset management systems.
• The Guardian Virtual Advisor, introduced in September 2025, delivers AI-powered guidance in plain conversational language, drawing on more than two decades of domain knowledge and troubleshooting data.
• The AspenTech Inmation OT Data Fabric unifies OT data across edge, on-premise, and cloud, applying consistent context and governance so trusted information reaches the right people.
• Emerson was named 2026 Industrial IoT Company of the Year for the seventh time, cited for the only full stack spanning intelligent devices, secure control systems, and enterprise optimization software.

From Seismic Data to Decision Without the Silo Tax

The upstream industry’s problem, Gertjan writes, isn’t a data problem. It’s a silo problem. Geophysicists, reservoir engineers, and production teams have historically worked in separate disciplines, on separate software, across separate geographies, and by the time an insight traveled the chain, the decision window had closed.

ASI’s cloud-native, agentic domain agents automate subsurface workflows and shorten the path from raw seismic data to investment decision, turning multi-disciplinary silos that used to cost months into work that collapses into days.

Drilling and Maintenance Shift from Reactive to Anticipatory

On the rig, periodic checks, reactive fixes, and schedule-driven maintenance were built for a world with lower day rates and more margin for error, and neither exists anymore. AI-driven real-time optimization now provides drilling engineers with a continuous view of bit wear, formation pressure, and trajectory deviation before indicators become incidents.

The same shift plays out in asset integrity. Aspen Mtell, trained on actual failure signatures, spots anomalies well ahead of failure, prioritizes alerts by severity, and prescribes corrective action before an operator knows there is a problem. As Gertjan puts it, the move from reactive firefighting to proactive performance is no longer a concept. It is a product release.

Production, Safety, and Supply Chain, Connected

On mature fields, real-time production data feeding physics-based optimization models lets operators continuously tune pump performance, choke settings, and gas injection rates without the lag of manual review. Emerson’s Boundless Automation vision connects the field instrument to the enterprise optimization layer, which Gertjan describes as the architectural story behind the AspenTech acquisition.

Health, Safety, and Environment (HSE) follows the same pattern. Paper-based systems often flagged risk only after it materialized, while Guardian Virtual Advisor and anomaly detection surface hazardous conditions before they become incidents. In the supply chain, AI-driven demand forecasting and inventory optimization give planners an edge that manual models cannot replicate at scale, provided the underlying data is not stuck in silos.

The Data Fabric That Makes Any of It Work

All six operational areas generate enormous amounts of data, and the question Gertjan poses is whether that data is informing decisions or just filling storage. The AspenTech Inmation OT Data Fabric is positioned as the foundational enterprise-scale intelligence layer, unifying OT data across edge, on-premise, and cloud with consistent context and governance.

The Inmation Data Platform builds on that foundation with modules for virtualization, workflow engines, and private cloud deployments that scale across legacy and modern environments without disruption. As Gertjan writes, the AI in a sensor is only as valuable as the decision it shapes when the right data reaches the right person at the right moment.

Read the Full Perspective

The industrial world isn’t waiting for AI to arrive. It arrived. Read Gertjan van der Ven’s full article, “AI Isn’t Disrupting the Industrial World. It’s Running It,” to see the seven battlegrounds in his own words and consider where your operations are positioned to use them.