Energy & Renewables

Intelligent Energy: AI’s Role in Powering the Future

• AI, particularly machine learning (ML), is driving energy transition from fossil fuels to renewable energy sources across the whole supply chain, from power generation and distribution to consumption.
• Throughout the industry, particularly in oil & gas, AI and ML are delivering improved business performance and asset management, and reduced carbon emissions. The result is a fundamental change in how the energy industry operates, creating a more efficient, sustainable and secure future.
• With safety in the DNA, trust is a key element: trust that AI can deliver value efficiently, securely and safely, meeting stakeholder expectations in a verifiable way. Validation and verification of AI algorithms and AI-enabled infrastructure are therefore critical.
• While AI is leading to innovations such as smart grids, predictive analysis, energy storage and customer management, it is also driving significant opportunity in oil & gas.
• The global market for AI applications in the oil & gas value chains is estimated at over $3 billion in 2024, reaching $5.7 billion in 2029; this would deliver a CAGR of more than 12 percent over the five years, according to Mordor Intelligence.
• While AI is transforming the future of energy, it is also addressing legacy issues, in particular decommissioning of oil rigs (through Rahd AI, owned by Ventex). Breakthrough technology could see AI saving tax payers and the oil & gas industry £10 billion / $12.6 billion / €12 billion, with pilot decommissioning capabilities leveraging proprietary data management and privately trained large language models (LLM).
• AI is driving grid resiliency and power availability, as greater amounts of fluctuating renewable energy is added to the mix.
• Virtual power plants represent a paradigm shift from traditional energy systems. They leverage AI to aggregate and optimize the output of distributed energy resources and adjust to fluctuating renewable energy inputs.
• AI’s ability to analyze vast amounts of historical data and real-time weather information is revolutionizing power demand forecasting and energy efficiency for homes and businesses. In the dynamic energy industry, AI’s role extends to the wholesale market, predicting peak demand and assisting energy asset owners in maximizing returns.
• AI Power Consumption is a key issue and compelling growth opportunity, given its voracious appetite for power.
• With AI now embedded into most online searches, demand for hardware to accommodate data storage is leading to huge growth in data centres.
• In powering these data centres, electrification can barely keep up with demand. S&P Global Ratings predicts US data centres will need 150-250 terawatt hours of incremental power per year to 2030, with grid infrastructure likely to be the biggest hurdle. For comparison, New York City currently uses 50 terawatt hours per year. 
• Generative AI has therefore intensified the need to accelerate the pace and scale of energy generation and distribution. Demand for data centres has revealed gaps in energy supply and infrastructure, both crucial to future reliability and affordability. Outside the US, Amsterdam, Dublin, and Singapore have put a moratorium on new data centre builds primarily due to the lack of supporting power infrastructure.
• Chip efficiency is also struggling to keep up with gains in computing capabilities driven by AI and quantum technologies. The amount of time for central processing units to double their performance efficiency has increased from two to nearly three years. Supplying the 50 GW of additional data centre capacity needed in the United States by 2030 (up from 25 GW in 2024) would need an investment of more than $500 billion in data infrastructure alone.
• The lack of power in most markets is driven more by lack of connectivity to the transmission grid and lengthening time scales, than by power generation itself. Current capacity is constrained by fossil-fuelled plants operating below maximum levels in a drive to net zero, while AI needs are exacerbating a shortfall in computing capacity.
• Expansion of the data center ecosystem will drive significant capital deployment in equipment and services across a broad value chain. Across the power value chain, investors can participate in and enable solutions to meet the demand for data centers and accelerate growth. Major opportunities for investment will be in the areas of 1) Power generation and access 2) Power Equipment 3) Construction and supporting service trades and technicians. (from Mckinsey)

Navigating the Shift: Talent & Leadership for AI-Enabled Transformation

“The data intensity across a broad variety of mechanical, chemical and electrical processes sets up the energy industry to be a major beneficiary of AI technology. Creating a unique AI based algorithm to process existing data streams has the potential for big impacts on predictive maintenance, process efficiency, emissions, reduction, safety, grid performance / power allocation, etc. As a tool that is a quantum leap forward in its ability to process huge amounts of data, AI will free up managers at all levels to focus on higher level questions. The leaders who thrive will blend technical expertise with geopolitical awareness, a clear vision of energy as a commodity in its many different forms and the foresight to see new opportunities in a rapidly changing environment.”

Thomas Zay
Managing Partner, United States
Global Sector Leader, Energy

• Net zero is driving a sharper focus on clean thermal energy in many countries, bringing geologists, advanced biologists and AI experts into the industry to work with engineers in shaping future energy generation.
• AI and ML are increasing demand for skills across every area of the energy sector, from data security to software engineering in both core and evolving areas.
• As AI frees people from repetitive tasks, it provides opportunity for more critical thinking and creativity, leading to an evolving workforce where more holistic approaches are needed beyond technical silos. Leaders are therefore reshaping both management teams and the overall workforce, encouraging a blend of technical and soft skills, and a greater focus on the end consumer at every level.
• Energy forms part of every nation’s critical infrastructure. In an era of geopolitical complexity, specialist technological skills, such as cybersecurity, are in huge demand, leading to increased hiring from the technology sector. Historically, energy leaders found it difficult to compete with the tech sector for the brightest and best, but with energy set in a geopolitical context and occupying the central role in our planetary well-being, the needle is moving.
• In addition to tech-based roles, finance roles are also in the spotlight as AI drives evolution in the business model, leading to a sharper focus on roles such as chief revenue officer. AI is enabling agile decision-making through real-time data on demand, supply and pricing, as well as market volatility and geopolitical uncertainty.
• The best board directors and leaders today are using the convergence of energy transition and AI to drive a better future for their organisation, nation state and the wider world. Energy leadership demands politically savvy, technical understanding, robust people leadership and recognition of the pivotal role they play in the future of the planet.

Read more on the topic: 

• RMI: Clean Energy 101: Virtual Power Plants
• Energies Media: Why We Need AI-Driven Virtual Power Plants: A Step Towards Sustainable Energy
• Det Norske Veritas (DNV): AI spells opportunity and management risk for oil & gas
• Mordor Intelligence: AI in oil and gas market size
• Energy Digital: Top 10 applications of AI and robotics in energy sector
• Daily Business Group: AI could save billions in decommissioning costs
• McKinsey: S&P Global: Data centers rapid growth creates opportunities and issues
• World Energy Council: AI-driven leadership impact on energy transition