IIoT World Energy Day 2026

Air-gapped environments in power generation and water facilities cannot afford patching delays, unmanaged update pathways, or exposure to modern cyber threats. Yet maintaining security without disrupting operations remains a major challenge. Join cybersecurity experts from OPSWAT and Emerson as they explore how managed patching for air-gapped critical systems strengthens resilience while preserving operational continuity. Energy operators will learn how to modernize their cybersecurity strategy without compromising safety, uptime, or compliance.

As modern grids absorb unprecedented volumes of data from BESS, solar, wind, EV charging, and other distributed energy resources, the industry faces a critical challenge: how to transform raw industrial data into real-time operational intelligence. The shift toward decentralised, software-defined energy systems demands high-performance edge platforms capable of unifying diverse protocols, executing analytics at the point of control, and scaling across thousands of assets.

Virtual Power Plants coordinate tens of thousands of batteries, EVs, and smart devices as single grid resources—but the data complexity is staggering. Panelists will discuss handling unreliable edge connectivity, out-of-order data, and the shift from site-level to fleet-level intelligence. Learn how companies architected for scale, maintained compliance with grid operator telemetry requirements, and turned distributed chaos into coordinated flexibility worth billions in grid services.

Most energy enterprises have already invested in historians, ALM/ALIM, EHS platforms, content repositories, and even AI, yet teams still rely on people to manually clean, transform, and validate operational documents as they move between systems. That's where errors creep in, cycle times stretch, and compliance exposure grows.

The grid is the primary bottleneck for the global AI economy. With data center loads forecast to double by 2030 and interconnection queues stretching beyond a decade, the business-as-usual model of grid planning has collapsed. This session brings together the hyperscalers demanding power and the utilities tasked with delivering it to discuss the new commercial reality: who pays for rapid upgrades, how capacity is reserved, and what happens to the rest of the queue when a gigawatt-scale project moves in.

As grid constraints intensify, utilities and energy operators are increasingly dependent on high-quality, consistent operational data to understand how assets perform across sites, vendors, and environments. IIoT platforms and AI systems rely on access to reliable, normalized data from the edge to enable accurate analysis of utilization, constraints, and operational risk. Without a common data foundation, scaling analytics and decision-making across fleets remains a significant challenge.

Driven by the rise of edge AI, machine health monitoring in the energy industry is undergoing a major transformation — enabling real-time intelligence where it matters most across power plants, grids, and critical energy assets. This session explores how edge computing and AI are converging to deliver immediate insights at the point of generation and distribution, reducing latency and improving response times in high-demand environments.