AI and Energy for a Sustainable Future

POWERING POSSIBLE


AI and Energy: Partners for a sustainable future.

At the intersection of three megatrends – rising global energy demand, the shift towards net-zero emissions, and rapid AI development – there is a unique chance to reshape the future of energy. With the right investment in clean energy, smart policies, and AI innovation, we can create a more sustainable, efficient, and equitable energy system for all.


This paper from ADNOC, Masdar and Microsoft outlines seven key areas for collaboration between the energy and technology sectors to accelerate the transition to a net-zero energy system. By harnessing AI’s capabilities, from methane reduction to grid resilience, these industries can address growing energy demands and drive an inclusive transformation.

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Rising AI demand for electricity is putting pressure on the global power grid

Data centers’ energy demand is expected to grow by 8-23% by the end of 2026. While AI has the power to drive the energy transition, its energy consumption is increasing, even as nearly 750 million people still lack basic electricity access. With global electricity demand set to rise by up to 4% annually by 2030, urgent action is needed to prevent AI from overwhelming ageing grids and widening energy inequalities.

The seven priority areas

Increased collaboration between the energy and technology sectors can transform the energy system and unlock the full potential of AI.

 

Increasing collaboration between technology and energy companies

A total of 94% of leaders agree on the need for greater collaboration between energy, AI and climate. Collaboration between the energy and technology sectors could include commercial partnerships for co-investing in carbon-free energy projects, joint ventures – like Microsoft’s investment in G42 – to combine expertise, and sectoral initiatives that promote best practices, such as the First Movers Coalition and the Oil and Gas Decarbonization Charter.

 

Investing in AI for the energy transformation

 

Private investment in AI for energy has declined by over 30% in the last three years. Energy investment needs to be focused in four key areas: reducing methane emissions, utilizing carbon capture and storage, building a resilient grid and tripling the availability of renewable energy company.

Expanding and enhancing grid capacity

Today, AI is already being piloted to support the expansion of transmission networks and the integration of renewable energy, but greater deployment is required. By 2040, electricity grids require the addition or refurbishment of 80 million kilometres of networks to cater to rising demand and diversified power supply.

Building workforce capacity

Approximately 78% of leaders consider talent and training a challenge to adopting AI. Technology companies can deliver AI solutions if they have a better understanding of energy systems, while energy companies have a responsibility to upskill a wide range of personnel for successful AI implementation across the entire value chain.

Developing AI with and for emerging economies

By 2050, approximately 80% of electricity demand growth will come from developing countries. Emerging markets and developing countries (EMDC) are vital for green energy supply and need tailored AI solutions. With nearly 85% of data centers outside of EMDCs (excluding China) and projected growth favoring developed economies, diversifying data center development is crucial for sustainability.

Establishing data standards

A unified framework is critical to AI for efficient data flow across the energy system and its stakeholders. Regulations improve comprehensive analysis and seamless data exchange – facilitating decision making – while protocols focus on protecting proprietary data.

Advancing policy and governance principles

Thoughtful standards and policy frameworks that govern the use of AI in the energy sector are important to ensure its safe, secure and responsible use. Collaboration among companies, researchers, scientists, and policymakers would open a path to a regulatory sandbox that collectively addresses sustainability challenges, and funds interdisciplinary projects that combines AI expertise with policy and social justice.

Innovation is driving solutions

Energy for AI. AI for Energy.

Reducing downtime
by up to 20%

at a wind farm can be achieved through AI-driven predictive maintenance, lowering costs significantly.

Detecting methane leaks
20% more accurate

The University of Oxford has developed an AI tool that improves accuracy when scanning geospatial data to detect methane leaks.

Discovering material for carbon capture
120,000

promising material candidates for better CO2 capture were discovered by Argonne National Laboratory in just 30 minutes utilizing AI.

Identifying Battery Materials
32 million

candidates for solid-state electrolytes were scanned and identified using AI by researchers, including Microsoft, to find a better battery material.

Predicting changes with
99% accuracy

An AI algorithm was developed by researchers from Purdue University that predicts changes in Small Modular Nuclear Reactors (SMR) performance.

Reducing electrolyzer costs
by up to 25%

is possible using AI-enabled digital twins for membrane-less electrolyzers, developed by researchers including Harvard.

Explore AI and Energy for a sustainable future

Join us on this journey of Powering Possible

We invite you to view our full report on the AI-energy nexus prepared in partnership with ADNOC, Masdar and Microsoft.

Download the report