At the Baku Energy Forum, industry experts highlighted a pressing challenge: roughly 500,000 kilometres of oil and gas pipelines worldwide require renovation, rebuilding, or upgrades. Leaks, ruptures, and other incidents already cost the sector more than $7 billion (€6 billion) each year, and about 40% of failures go undetected within the first 24 hours. This scale of risk is driving rapid adoption of sensors, machine learning, and real-time monitoring systems designed to anticipate failures rather than simply respond to them.
The shift represents one of the most significant technological transformations in the energy sector, according to a panel led by Euronews at the forum. Modern smart pipelines can provide real-time awareness, predictive maintenance, leak detection, and operational optimisation, creating what industry leaders describe as an intelligent infrastructure ecosystem. However, speakers also warned that the industry faces a deeper challenge alongside ageing infrastructure: the people who know how to manage it are leaving.
The 'Silver Tsunami' and the Knowledge Gap
“We believe there is a silver tsunami happening in our industry,” said Gaurav Singh, Head of Integrity Management Systems for Europe at ROSEN. Experienced engineers and specialists are retiring, while fewer young professionals are entering the sector. There is a concern that decades of practical knowledge built through field experience will be lost. “If we don't utilise that knowledge, we're losing 80 years of experience that has been built over time,” Singh told Euronews.
For Singh, digitalisation is about preserving the accumulated expertise on which technology depends. AI relies on historical data and accumulated knowledge to recognise patterns and generate accurate predictions. Without that knowledge base, machine-learning systems become significantly less effective. “Knowledge is data,” Singh explained. “It feeds into the system and helps create the efficiency around these new digital solutions.”
Companies such as ROSEN are already building vast data warehouses containing information from more than 26,000 inspection runs, billions of recorded anomalies, and millions of kilometres of inspected pipelines. That information can then be used to train predictive models capable of identifying corrosion risks, estimating the condition of uninspected pipelines, and supporting future decision-making.
Security, Resilience, and Trust in Digital Systems
The growing dependence on digital systems raises its own questions. As experienced workers retire and their expertise is encoded into software, operators risk becoming dependent on tools they no longer fully understand — a development debated across aviation, healthcare, defence, and manufacturing. Christopher Wiig, Vice President of Energy Transition at ABB Energy Industries, believes the answer lies in balance. “The fear that machines will take over has existed since the Industrial Revolution,” he told Euronews. Rather than replacing people, he argued, digital systems should support them. “We actually need more people to do more jobs than we currently have the capability to do,” Wiig said.
The conversation around smart pipelines extends far beyond maintenance to include security, resilience, and trust. “I think there are three aspects mainly to look into,” said Wiig. “Personnel security, physical security and cyber security.” He added, “In the end, it's about financial benefits.”
Major energy corridors such as the Baku-Tbilisi-Ceyhan pipeline and the Southern Gas Corridor are critical components of international energy security, carrying oil and gas across thousands of kilometres to global markets. Industry forecasts suggest that smart pipeline investment across the region could reach $2.4 billion (€2 billion) by 2030, while predictive analytics may reduce operating costs by up to 30%.
These developments are particularly relevant for Europe, which relies on a network of pipelines connecting the Caspian region to European markets. As the continent seeks to diversify its energy sources and enhance security, the integration of AI and digital systems into pipeline management becomes a strategic priority. For more on how digital systems are transforming these corridors, see AI and Digital Systems Transform Energy Corridors Linking Caspian to Europe.
The broader implications of AI in critical infrastructure also intersect with debates on data centre energy use and synthetic DNA risks, as highlighted in UN Report: Data Centers' Energy Use Rivals Nations, AI Users Urged to Be Less Polite and AI Leaders Warn of Bioweapon Risks from Unregulated Synthetic DNA Sales. Meanwhile, the economic impact of energy disruptions is evident in Eurozone GDP Shrinks 0.2% in Q1 2026 as Iran War Disrupts Energy Markets.
In summary, the adoption of AI and smart monitoring systems is not just a technological upgrade but a necessary response to the dual pressures of ageing infrastructure and a retiring workforce. The success of these systems depends on preserving and digitising the knowledge of experienced engineers, ensuring that Europe's energy lifelines remain secure, resilient, and efficient for decades to come.
