Generative AI

New Trends & Opportunities for Gen AI in Energy and Natural Resources

Publish Date: January 21, 2025

Generative AI (Gen AI) is reshaping business conversations globally, with its potential to revolutionize industries and unlock unprecedented opportunities. From Silicon Valley to boardrooms worldwide, leaders see its power to redefine processes and drive innovation. In the energy and oil and gas (O&G) sectors, the technology is already streamlining operations—automating tasks, predicting maintenance, and optimizing resource exploration. Gartner’s 2024 CIO Insights ranks AI and Gen AI as the top game-changing technologies for the O&G sector by 2026.

By filtering valuable insights from vast information, Gen AI enables informed decisions, yet its true value lies in mitigating risks like transparency, data security, and privacy issues. Its strong cybersecurity and digital capabilities enable organizations to leverage large language models (LLMs) to unlock broader, more productive applications.

How Energy, O&G, and Natural Resources Companies Leverage GenAI

As utility organizations have large enterprise asset bases and manage complex operations, Gen AI and IoT sensors will play a vital role in asset optimization and predictive maintenance. AI algorithms learn from historical data, analyze real-time conditions, and predict potential failures, filtering out false alarms and optimizing maintenance schedules for uninterrupted service. Maintenance procedures streamlined by Gen AI also improve safety and minimize the industry’s environmental impact.

In another use case, Gen AI is capable of helping enterprises manage new energy resources and deploy them efficiently. It will, therefore, accelerate the development of renewable power generation systems such as solar panels and wind turbine networks. NRG Energy has recently partnered with Google Cloud to use AI and predictive analytics tools to effectively anticipate wind and solar energy outputs. This enables the power company to improve productivity and adjust for fluctuating energy inputs.

Moreover, the potential of Gen AI to analyze geological, physical, and operational data will empower O&G players to forecast reservoir performance and estimate hydrocarbon reserves, enhancing exploration efficiency. By simulating various extraction scenarios, Gen AI also helps to identify the most productive, agile, cost-effective, and environmentally sustainable drilling methods. Based on information analyzed by AI algorithms, field teams get to drill faster, reduce equipment wear, increase precision, save costs, improve resource recovery, and ensure compliance with regulatory standards. BP has already turned to AI software systems to enhance decision-making based on automated data analysis.

As in other industries, Gen AI strengthens supply chain management in energy, O&G, and natural resources by analyzing consumption patterns, transportation costs, and inventory levels to ensure timely, cost-effective resource delivery. Through real-time data processing, companies quickly identify and resolve supply chain bottlenecks, improve decision-making, and reduce operational environmental impact.

In addition, the industry has scope to harness AI algorithms for optimizing chemical processes and product development, personalized energy and resource management solutions, and operations safety monitoring.

Overcoming the Challenges to Gen AI Adoption

All disruptive tools have challenges that must be addressed for long-term successful usage. Unlike traditional AI, Gen AI is designed for widespread, direct use by employees, making AI literacy and identifying relevant use cases crucial. Fortunately, with the highly technical nature of their tasks, this is not problematic for employees in the energy, O&G, and natural resources sectors.

Gen AI also needs to be trained on high-quality data for informed decisions. By identifying and addressing any shortcomings in data availability, cohesiveness, and integration, users must ensure that it is clean, comprehensive, and accessible to support business processes. What’s more, to smoothly integrate Gen AI’s capabilities with their workflows, many companies are moving their legacy IT systems to cloud platforms.

Identifying and realizing early use cases is another issue that needs attention. As the opportunities presented by Gen AI are attractive and the technology is evolving rapidly, organizations cannot afford to wait for comprehensive, enterprise-wide solutions that demand heavy inputs. While creating a solid data foundation, they must identify discrete initial use cases and experiment with the technology. The idea is to get measurable, quick wins that eventually build momentum. Companies should prioritize the domains that directly impact their costs, risks, revenue, and other tangible outcomes.

Energy, O&G, and natural resources companies must also safeguard the integrity of their data and algorithms, establishing clear governance for solution development, deployment, and upgrades. Identifying and mitigating risks related to Gen AI models requires special attention. Users must remember that these models have the tendency to hallucinate and generate outcomes that look authoritative but are not factual—human intervention is necessary to address the issue.

Emerging Gen AI Trends in the Sector

Gartner projects global AI spending in the energy, O&G, and natural resources industry to grow at a 25.2% CAGR, reaching $2.9 billion by 2027. Here’s a look at key trends expected to reshape the sector further:

Improved asset lifecycle management: Gen AI-driven platforms offer comprehensive insights throughout an asset lifecycle. They identify maintenance needs, balance resource allocation, and augment operational safety. As quantum and edge computing sharpen Gen AI’s data processing capabilities, it will drive continuous monitoring and enable timely interventions to minimize disruption and extend asset life.

Autonomous supply chain optimization: Gen AI can fully automate supply chain systems, allowing them to adapt to real-time market conditions and demand forecasts. This will reduce costs and boost agility in distribution and inventory management, making companies more responsive to fluctuations in supply and demand.

Intelligent environmental monitoring: Advanced Gen AI algorithms can continuously analyze environmental data to assess a company’s operations’ ecological impact and identify regulatory compliance issues. This proactive monitoring will help to avoid penalties and lawsuits. More importantly, it will enhance sustainability efforts and improve public perception of organizations in the industry, culminating in better stakeholder relationships.

Collaborative AI ecosystems: Gen AI will also facilitate deeper collaboration among industry players through shared platforms that integrate data from various sources for real-time data sharing and analysis. It can accelerate knowledge-sharing and open more doors for innovation while fostering transparency across the sector. Enterprises can drive greater operational efficiencies through insights into technological advancements.

Personalized energy management solutions: Deploying Gen AI in the energy and natural resources sector will provide individual and institutional customers with tailored energy management tools to control their consumption based on their needs and preferences. Personalization will enhance energy efficiency, lower user costs, and promote broader sustainability initiatives in the industry.

Harnessing Gen AI Responsibly: A Blueprint for Transformation

The public release of ChatGPT in 2022 popularized the concept of Gen AI, and while the technology is still in its early stages, it is maturing rapidly. By understanding its potential benefits and risks, energy, O&G, and natural resources enterprises can open new doors to transformation for their operations. Data governance and cybersecurity must be their business imperatives while using Gen AI engines for automation and analytics.

Value-delivering Gen AI must stay unbiased, robust, transparent, safe, accountable, and respectful of privacy. By embarking on the exploration and deployment of trustworthy Gen AI now, energy, O&G, and natural resources, enterprises will acquire valuable insights, adapt to its nuances, and evolve alongside the technology.