Rewriting Corrosion Control: How AI and IoT are changing the game

Corrosion may be a centuries-old enemy of infrastructure, but the fight against it is entering a new era — one powered by artificial intelligence (AI), the Internet of Things (IoT) and data-driven materials science. From offshore rigs to refineries, industries are now deploying smart sensors and predictive algorithms to detect corrosion long before it becomes dangerous or expensive.
Dr Satyam Priyadarshy, a global pioneer in applying AI to energy and infrastructure, believes this transformation goes beyond a technical upgrade. “Corrosion is a multi-trillion-dollar problem”, he says. “But AI offers a new lens. It lets us prioritise risks, detect invisible damage and respond before failure occurs — saving time, money and lives”.
Traditionally, corrosion monitoring relied on scheduled inspections and delayed responses, often leading to unplanned downtime and costly failures. Today, AI-driven platforms flip that model. By analysing sensor data, image scans and predictive models, deep-learning systems catch early-stage corrosion patterns that inspectors might miss — and generate reports in minutes. The result is lower maintenance costs, fewer shutdowns and longer asset lifespans.
What was once experimental is now field-proven. Offshore rigs in the Gulf of America have used AI inspection platforms with panoramic imagery and laser scans to cut costs and plan repairs more efficiently. Pipeline operators now rely on sensor networks combined with AI algorithms to deliver early leak warnings and generate corrosion risk scores. These examples show that predictive monitoring isn’t just possible — it’s scalable.
In Oman, where energy infrastructure faces relentless corrosion challenges, the costs are staggering — estimated at hundreds of millions of rials annually. Dr Satyam suggests that smart monitoring could slash those costs by 30–50%. “It aligns perfectly with Oman Vision 2040”, he notes. “By adopting AI-based solutions and upskilling the workforce, Oman can become a regional leader in predictive maintenance and digital asset management”.
Even the most advanced AI is only as strong as the data it consumes. High-quality sensor networks are essential for accuracy. “Think of it as training an athlete”, Dr Satyam explains. “If your sensors are strong, your AI will be too”.
To guide organisations starting their AI journey, Dr Satyam outlines his FIRST framework: First, begin small, piloting AI on high-value assets. Improvise, improving data quality and refining methods iteratively. Revise, adapting workflows to maximise efficiency. Scale, rolling out solutions across the enterprise. Transform, by upskilling leadership and teams in AI, IoT, cloud and digital strategies. “It’s about creating a sustainable digital strategy”, he concludes. “One that turns corrosion from a constant crisis into a manageable, measurable process”.
Across the Gulf, this wave of innovation is gaining momentum. Industry leaders are turning to digital inspection tools, predictive analytics and AI-enhanced asset management — trends that will be under the spotlight at upcoming technical gatherings such as the Oman Corrosion & Materials Innovation Summit (OMCORR) in Muscat. The summit reflects how the sector is moving from reactive maintenance to proactive innovation, setting new benchmarks for asset integrity and sustainability.
As the region undertakes megaprojects in oil, gas, power and desalination, the message is clear: smart corrosion monitoring is no longer optional — it is the next step in future-proofing Gulf infrastructure.