AI Transforming Energy Sector
When considering AI applications in the energy sector, use cases that come to mind normally include predictive analytics, reporting, and the automation of back-office processes and operations. Modern forecasting models now rely on machine learning (ML) techniques, while Generative AI (GenAI) supports middle-office tasks and market research. Natural Language Processing (NLP) applications also add value across front, middle, and back-office functions. Further use cases would include interfacing and user trainings.
But I was excited to find out that there are more tasks for AI to be considered. According to Financial Times publication https://emea01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fon.ft.com%2F4adsq1p&data=05%7C02%7C%7C5ffb169c83234cb9eac508dcff23e713%7C84df9e7fe9f640afb435aaaaaaaaaaaa%7C1%7C0%7C638665776868003073%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C0%7C%7C%7C&sdata=1ufvFNy%2BOcafmiOpYCE6vETdB%2BQQTPNiJsU9kfY4UBs%3D&reserved=0
leading energy companies are deploying distinct AI applications to address industry-specific challenges. One example is in emissions monitoring. Shell, for instance, has developed an AI tool to track methane emissions, which, as Dan Jeavons, Shell’s vice-president of computational science and digital innovation, explains, “uses wind and concentration data to help us understand the origin and quantity released.” Jeavons notes that AI will optimize energy system efficiency by “reducing the amount of power needed to be generated” and could lead to the creation of “entirely new low carbon-footprint energy systems,” while enabling suppliers to monitor greenhouse gas sinks.
AI is also expected to enhance the cost-effectiveness and precision of energy infrastructure. For instance, engineers working on pipelines and power lines can now use AI to “generate a viable route shortlist in seconds,” a process that previously took several days, according to Gert Vermeiren, European managing director of environment, water, and energy at the global infrastructure consulting firm Aecom. Additionally, AI is anticipated to play a larger role in grid design and planning.
Mona Schroedel, managing associate at UK law firm Freeths, suggests that AI could aid energy companies in monitoring and detecting cybersecurity threats—a critical function given that modern software systems leveraging big data and AI often operate in the cloud and are therefore vulnerable to cyber-attacks. AI capable of identifying and preventing such threats would be a valuable asset not only in the energy sector but across industries.
The energy market appears to be on the brink of a new revolution, poised to transform business practices and redefine the skills required across the industry. This shift will impact jobs in the sector by creating new opportunities in some areas while reducing demand in others. For software solutions, this revolution offers significant opportunities for growth and competitive advantage, driven by modern architectures and AI-based applications.
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