ব্যঙ্গাত্মক বর্ণনা এবং ফরেক্সের প্রবেশদ্বার বিন্যাস

Oil and gas industry seeks autonomy beyond automation

The oil and gas sector is accelerating its digital transformation by significantly increasing investments in cloud technology, artificial intelligence, and advanced analytics, according to a report by Bernstein. Companies are moving from basic automation to more autonomous and intelligent operations, focusing on technologies that promise to enhance the efficiency of extraction and production processes.

Richard Nguyen, an analyst at Bernstein, noted that energy groups are increasingly directing capital and operational expenditures toward digital solutions, aiming to make their businesses less reliant on manual management and more resilient to operational disruptions. Data from Gartner reveals that IT spending in oil and gas is expected to grow at an average rate of 7.4% per year from 2025 to 2029—slightly below the corporate average, but sufficient to indicate systemic modernization within the industry.

However, the implementation of AI remains in its early stages. Bernstein estimates that only 13% of oil and gas companies have already deployed agent-based AI, while nearly half plan to do so by 2026. Major barriers to adoption include cybersecurity concerns, data management issues, and protection of intellectual property, particularly in operational technology systems where the cost of errors is traditionally high.

The potential impact, however, appears substantial. According to Rystad, digital initiatives could save the industry approximately $320 billion between 2026 and 2030, with the highest returns expected in drilling, predictive maintenance, reservoir management, logistics, and autonomous robotics. One of the early examples of the shift toward agent-based AI was the launch of the SLB Tela platform, described by Bernstein as the first commercially available tool of its kind.

Cloud and edge computing platforms are already being integrated across the entire value chain—from extraction to processing. Companies such as Shell, BP, and TotalEnergies are utilizing these technologies to reduce costs and enhance productivity. Bernstein indicates that about two-thirds of operators have already integrated their IT and operational technology stacks, enabling the implementation of predictive maintenance and remote asset management.

By leveraging generative AI and real-time data streams, companies are beginning to create digital twins of assets and processes, simulating "what-if" scenarios and assessing future outcomes based on current conditions. Besides digital twins, such immersive technologies have the potential to enhance efficiency and safety in field operations, delivering significant cost savings.

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