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Devavrat Shah, chief scientist of enterprise AI at Celonis, argues that enterprise AI and agents must be connected to operational processes and data to provide useful, constrained recommendations. He recommends starting with specific business decisions, measuring speed and value gains, and investing in workforce education so employees can understand and appropriately act on AI outputs.
Arti Garg, chief technologist at AVEVA, discusses accelerating industrial AI—including foundation models, physical AI, and agentic systems—and describes AVEVA’s responsible-AI framework that emphasizes security, efficiency, human safety, and oversight. She also notes participation in an IEEE working group developing a standardized methodology to measure AI’s environmental impact across energy, resources, water, and carbon.
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