As Global Electricity Consumption Surges, AI Industry Demands Energy Efficiency

The AI and Data Center Boom: Challenges and Solutions for Global Energy Systems

The explosive growth of Artificial Intelligence (AI) and the rapid expansion of data centers are beginning to pose significant challenges to global energy systems, accompanied by skyrocketing electricity demand, escalating energy bills, and an increasingly large environmental footprint. While AI is transforming the world and the economy, this technology can also become a solution to one of the most pressing needs in the energy sector amid rising demand, unstable fossil fuel supplies, and inflation pressures along renewable energy supply chains.

AI can unlock additional energy benefits and drive progress in energy efficiency - an area that has slowed in recent years. The development of AI itself could be a leap forward toward energy efficiency, as data center developers will face negative perceptions about drawing electricity and water resources from communities. With growing NIMBY (Not In My Backyard) movements in rural America opposing data center placement and rising energy costs, AI can partially redeem itself by becoming a key factor driving significant progress in energy efficiency.

AI Supporting Energy Efficiency

"We may be at a moment where we can accelerate the energy efficiency process, particularly in industry, with support from AI," Brian Motherway, head of energy efficiency at the International Energy Agency (IEA), told Financial Times in an interview.

At the end of last year, Motherway stated that "the slow progress in energy efficiency is a missed opportunity," as the world is still off track to double the improvement in energy efficiency to 4% annually by 2030.

According to the latest IEA data, instead of rising to the 4% target, the global energy efficiency progress has slowed in recent years. The annual improvement rate since 2019 has only reached 1.3%, significantly lower than the 2% starting point for the doubling target.

In some regions, rapidly increasing electricity demand has led to a general increase in inefficient power plants, while growing access to air conditioning has pushed electricity demand related to cooling to new highs, not necessarily with the most efficient cooling equipment, Motherway argued.

Furthermore, policy has lagged behind technological advances, "leaving significant savings on the table," the official noted. While energy efficiency improvements remain one of the fastest and most cost-effective ways to enhance energy security, reduce costs, and cut emissions, it has not met expectations or IEA targets.

No one doubts AI's capability to be more efficient than humans in identifying energy waste, particularly in industrial applications. For example, renewable energy companies have invested in AI and digital twin solutions that can see significant benefits in their operational efficiency, a 2025 study published in the Energy Reports journal showed.

However, challenges in bringing AI to mainstream use in energy production, distribution, and transmission remain, "including high deployment costs, cybersecurity risks, and the complexity of integration," scientists noted.

To realize efficiency benefits from AI, companies will need to invest in upgrading equipment that will be costly and often custom-designed, according to analysts.

"Companies need to go plant by plant, investing in equipment that is often custom-designed," Sam Kimmins, energy director at non-profit organization Climate Group, told Financial Times.

Efficiency Cannot Offset AI's Soaring Electricity Demand

While AI can help drive energy efficiency benefits, it may partially offset the global increase in electricity demand. Last year, electricity demand from data centers increased by 17%, and demand from AI-focused data centers grew even faster, surging 50%, according to an IEA report in April. This AI-driven increase in electricity demand far outpaced the 3% growth in global electricity demand.

With the exponential growth in electricity demand, the AI value chain has witnessed a race to secure electricity, grid connections, generation capacity, chips, and capital, the agency noted.

AI not only consumes energy but also uses water and other natural resources, including land. The United Nations University Institute for Water, Environment and Health (UNU-INWEH) warned in a report earlier this month that by 2030, AI's water usage will meet the needs of 1.3 billion people.

AI data centers are projected to consume 945 terawatt hours of electricity globally by the end of this decade. This figure is nearly three times the total annual electricity demand of Pakistan, Bangladesh, and Nigeria - countries with a combined population of over 650 million, UN scientists said.

"This report is not an indictment of artificial intelligence, a technological revolution that is improving the lives of billions of people worldwide," said Professor Kaveh Madani, Director of UNU-INWEH, who led the investigation team. "We have a narrow window to ensure that the backbone of our era's technological revolution develops within planetary boundaries, and that communities providing critical minerals to power AI and where there is AI infrastructure and e-waste are also the ones that benefit from it."

As AI continues to shape the future of technology and the global economy, balancing the benefits of AI with its impact on energy systems will be one of the most critical challenges in the decades ahead. Policymakers, technology developers, and investors will need to collaborate to ensure that AI development is accompanied by progress in energy efficiency and environmental sustainability.