Living digital twins are helping industrial plants operate more like adaptive systems, according to an MIT Technology Review Insights article. The piece says earlier digital twins lagged physical reality, could not analyze data in real time, and could not act on problems they detected. Newer versions combine a dynamic digital model of a facility with control systems that can intervene in operations.
Rob McGreevy, chief product officer at AVEVA, describes these AI-infused twins as adaptive, evergreen models of a plant's assets and processes. He says they connect systems that once ran in isolation.
The article says agentic AI is beginning to move industrial systems from diagnosis and suggestions toward independent action. Human operators still define what healthy performance looks like and flag when AI systems drift out of alignment, the article says.
Citing a 2026 Manufacturing Leadership Council survey, the article reports that 66% of manufacturers are using or plan to use agentic AI in their operations, and 40% expect some degree of factory autonomy by 2030. It also cites a Deloitte 2025 smart manufacturing survey in which 65% of executives ranked operational risk, including business disruption, among their top concerns.
McGreevy expects AI to work mostly in an advisory role for the foreseeable future, with full autonomy limited to narrow, highly repetitive tasks. He compares this path to SCADA systems, noting that "supervisory" implies a human in the middle.
The article says governance is lagging. In a recent AVEVA and IMD study, 43% of organizations said AI has changed decision-making and accountability across ecosystem partners only slightly or not at all, while 23% reported a significant or fundamental change. The article also notes that the EU AI Act classifies certain AI safety components in critical infrastructure as high-risk and requires human oversight.