Corrosion is an electrochemical process that degrades materials and has an enormous economic and safety impact. Its global cost is estimated to exceed 3% of the world's GDP, affecting infrastructure, transport, energy, and medicine. Despite its omnipresence, corrosion science is a fragmented field, with scattered data and a lack of standardization that hinders prediction and the development of effective solutions. The scientific community is now seeking to unify these efforts to create a "world model" of corrosion.

This effort involves creating standardized and accessible databases that integrate information on corrosion mechanisms, material properties, operating environments, and experimental results. Digitization and the use of artificial intelligence and machine learning are crucial for analyzing large volumes of data and developing more accurate predictive models. The goal is to move from a reactive to a proactive approach, where corrosion can be predicted and mitigated before it causes significant damage.

Implementing a world model for corrosion would require unprecedented international collaboration among academia, industry, and regulatory bodies. This would allow for the sharing of knowledge, resources, and best practices, accelerating the development of new corrosion-resistant materials and more efficient protection strategies. A unified framework would not only optimize research but also facilitate decision-making in engineering and public policy, with substantial economic and environmental benefits.