AVEVA’s AI-powered digital twins blend autonomy with human oversight in factories
AVEVA’s Rob McGreevy describes a new generation of digital twins as ‘living’ systems that adapt to real-time industrial data and can autonomously adjust operations. Unlike earlier static models, these AI-driven twins simulate physical plants with dynamic, high-fidelity representations and intervene in control systems—though human operators still define acceptable performance and validate AI…
Key points
- AVEVA’s ‘living digital twins’ use AI to simulate industrial plants in real time and make autonomous adjustments, with human oversight
- 66% of manufacturers plan to use agentic AI by 2030, but 65% fear operational risks like disruptions or safety failures
- Case studies show energy savings (16%), reliability gains (99%), and ROI (ninefold) from AI-optimized operations
The shift relies on cheaper IoT sensors, predictive AI models, and connected data threads linking design, operations, and maintenance. A 2026 survey found 66% of manufacturers plan to adopt agentic AI, yet 65% cite operational risks as a top concern. Case studies include Saudi Aramco’s closed-loop production adjustments, Nestlé’s 16% energy savings via AI-optimized dryers, and SCG Chemicals’ 99% plant reliability. The EU AI Act now classifies critical infrastructure AI as high-risk, requiring human oversight, while AVEVA’s governance board sets internal principles for responsible deployment.
The headline, key points and digest above were generated by Digest AI's editorial model from the linked sources. Automated summaries can contain errors: the sources are the record. Spotted a mistake? Tell us. Published by Martin K., who runs Digest AI and handles corrections.
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