AVEVA outlines framework for safer industrial AI automation
AVEVA, an industrial AI firm with decades of experience, is navigating the shift toward autonomous systems powered by foundation models, physical AI, and agentic AI. These technologies enable automation in physical environments—where mistakes can have severe safety or reliability consequences—but also promise efficiency gains and sustainability benefits. Arti Garg, AVEVA’s chief technologist,…
Key points
- AVEVA’s framework for industrial AI prioritizes security, efficiency, and human safety with guardrails for autonomous systems
- IEEE’s P7100 standard aims to measure AI’s environmental impact across electricity, energy, resources, water, and carbon
- SCG Chemicals achieved 9x ROI with AVEVA’s AI-driven predictive analytics, reducing unplanned downtime to planned maintenance
A key challenge is measuring AI’s environmental impact, which varies widely due to factors like model size and compute requirements. Garg chairs an IEEE working group developing standardized methods to assess AI’s electricity, energy, resource, water, and carbon footprints. She also highlights the potential of AI to optimize power grids for renewable energy integration while reducing operational risks. Case studies, like SCG Chemicals’ 9x ROI from an AI-driven reliability platform, demonstrate the tangible benefits of responsible AI adoption. Garg warns that hesitation to adopt AI risks falling behind, but advises cautious experimentation with safeguards to mitigate risks in high-stakes industrial settings.
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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