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Corrosion costs the global economy upwards of an estimated US$2.5 trillion each year. While significant progress has been made in reducing corrosion risk through improved inspection practices, standards, and monitoring solutions, the industry is now entering a new phase.

The industry is shifting from reactive and preventive approaches toward more prescriptive and autonomous corrosion management. This shift is being driven by the implementation of AI-enabled technologies, with the AI corrosion management market projected to reach $6.9 billion by 2033.

The Cambridge Corrosion Conference was hosted by the global solution provider of Corrosion Under Insulation (CUI) risk monitoring solutions, CorrosionRADAR, and jointly organised by the Institute of Corrosion Midlands Branch and the European Federation of Corrosion WP15. The Conference brought together technology leaders from major energy businesses, such as Equinor, Dow, BP, Moeve, Cenosco, Eddyfi Technologies, Inductosense, Worley, Becht and Emerson.

Dr. Chiraz Ennaceur, Co-Founder and CEO at CorrosionRADAR, opened the event with a keynote address which highlighted how the industry is moving into autonomous operations. Dr. Ennaceur stressed that AI can elevate the way in which the industry manages corrosion, but these exciting technologies for corrosion and asset integrity only create real value when grounded in accurate, verifiable data and human oversight.

The keynote highlighted five foundations for a responsible path towards more autonomous corrosion management practices:

1. Experts are amplified not replaced – AI technology will increase capacity and accelerate output, but human expertise is still essential for judgement, accountability and decision making.
2. Data and domain knowledge is essential – AI without corrosion science at its core is simply pattern recognition without meaning. Real value comes from combining AI with human understanding.
3. Agentic AI will enable full autonomy – AI will increasingly navigate complex problems end-to-end, but humans must define the destination. Agentic systems will begin to automate tasks such as inspection planning, but humans need to guide them by clearly defining context, boundaries, priorities and constraints.
4. Traceability, auditability and explainability – every AI-driven decision must be traceable back to its underlying data and human assumptions. Systems must remain fully auditable to meet safety and compliance requirements.
5. From knowledge to systems of knowledge – by integrating historical and real time sensing data with expert human insight, we can build continuously learning systems that strengthen AI performance and drive ongoing improvement.

Dr. Ennaceur said that by keeping humans, data and domain knowledge firmly involved and using AI to support, not replace, decision-making, the industry can ensure transparency and auditability, and build effective systems that learn over time.

“We are entering a brand-new era of resilience,” she added. “Corrosion Under Insulation is a significant, global problem, but with the ongoing advancements in AI and the wealth of human expertise and knowledge that is characteristic of our industry, we will have more tools than ever to optimise the way we manage CUI in future.

“As we advance, it is more important than ever that the industry works together. This is a journey, not an overnight transformation. Moving beyond reactive approaches to asset integrity management will require careful adoption of new technologies, strong engineering judgement and close collaboration across our sector.

“The future of corrosion management isn’t just about detecting damage faster; it’s about using digital tools thoughtfully to improve resilience and long-term asset performance.”

Read the article online at: /special-reports/30042026/uk-corrosion-conference-establishes-a-vision-for-autonomous-asset-integrity/