Reports and articles
Assuring the safe deployment of AI-enabled robotics in industrial contexts
Published on May 28th 2026
The Global Initiative for Industrial Safety (GIFIS), in collaboration with Cambridge Industrial Innovation Policy, has released a new briefing paper: ‘Assuring the safe deployment of AI-enabled robotics in industrial contexts.’
AI-enabled robotics is rapidly reshaping industrial operations, creating new opportunities for productivity, flexibility, and worker safety. But as robots become more autonomous and increasingly reliant on AI, organisations face a critical challenge: how to deploy these systems safely and responsibly.
This briefing paper introduces the “BIG” safety assurance framework – a Balanced, Integrated, and Grounded approach that combines ethics, system-level safety engineering, and AI assurance into a single safety case.
Drawing on expert input, the paper is intended to inform practitioners, policymakers, researchers, and technology developers interested in the safe deployment of AI-enabled robotics in industry.
Through real-world industrial examples, including autonomous factory vehicles and humanoid robots, the paper explores how organisations can manage the unique risks introduced by AI systems. It argues that safety assurance should not be treated as a barrier to innovation, but as a practical foundation for the responsible adoption of next-generation industrial robotics.
Authors
Richard Hawkins, University of York and John McDermid, University of York.
About the Global Initiative for Future Industrial Safety
Launched in partnership with Cambridge Industrial Innovation Policy, Lloyd’s Register Foundation and the United Nations Industrial Development Organization (UNIDO), the Global Initiative for Industrial Safety unites policymakers, manufacturers, and innovators to drive the safe adoption of technology to tackle industrial safety challenges – advancing a more secure future for every industry.
For further information please contact:
Zongshuai Fan
+44 (0)1223 766141zf272@cam.ac.ukDownload: Assuring the safe deployment of AI-enabled robotics in industrial contexts
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