The use of digital twins across industry is expanding rapidly as companies move beyond asset visualisation towards predictive maintenance, process optimisation, and knowledge capture.
Software firms say that what was once a design and engineering tool is becoming central to operational strategy, driven by the twin pressures of ageing workforces and rising performance demands.
Speaking at the Schneider Electric Innovation Summit in Copenhagen this week, industrial software specialist AVEVA, which was fully acquired by Schneider in 2023, demonstrated how a global operations dashboard could identify and diagnose an equipment fault at a distant site using the company’s Cloud-based environment, AVEVA Connect.
“We’re seeing customers connect thousands of assets globally through a single digital thread,” Neil McGreevy, Chief Product Officer at AVEVA told Automation News. “The focus now is on prediction, efficiency, and resilience.”
Using live operational data, McGreevy located a failing pump, reviewed its performance history, and initiated a maintenance response directly from the digital interface. By linking multiple sites and systems, operators gain a consolidated view of asset performance across their organisations—an essential step towards predictive maintenance and autonomous decision-making.
The demonstration illustrated how digital twins are closing the gap between monitoring and intervention, transforming how maintenance is managed across distributed industrial assets.
Such applications are already delivering measurable results. UAE-based energy company ADNOC, for instance, has linked more than 75 systems into its Project Panorama digital twin, achieving reported savings exceeding $100 million through improved coordination across its value chain. In the power sector, utilities are deploying digital twins to model generation and demand in increasingly complex networks dominated by intermittent renewables, enabling more efficient scheduling and resource allocation.
McGreevy said one of the main drivers behind this trend is the need to retain knowledge as experienced engineers retire. “The elephant in the room for industry is the loss of expertise,” he said. “People who’ve run these plants for decades just know how to do things—how to manage a changeover, clear a jam, or fine-tune a process. Capturing that know-how digitally is now essential.”
To address this, industrial firms are embedding work procedures, diagnostic steps, and operational insights directly into digital systems, giving newer employees guided, context-aware instructions supported by live data. The approach aims to preserve institutional knowledge and maintain consistency across operations.
Artificial Intelligence is pushing digital twin functionality even further. AVEVA’s Chief Technologist, Arti Garg, highlighted the emergence of agentic AI systems capable of generating and managing sub-agents to carry out operational tasks. In one example, an AI agent could detect anomalies in pump performance, then automatically create another agent to adjust parameters or plan a repair. Garg said this development “moves digital twins from being descriptive to being truly prescriptive.”
However, as digital twins become more deeply embedded in operations, the industry faces challenges around data quality, interoperability, and cybersecurity. Fragmented legacy systems, inconsistent data standards, and poorly managed permissions can all undermine predictive accuracy. Cyber risks are also increasing as more assets come online.
“As we integrate operational, engineering, and enterprise systems, security cannot be an afterthought,” said Garg. “A single vulnerability in a connected asset can cascade across an entire digital twin ecosystem, so governance, encryption, and access controls are critical.”
