The Ultimate Spark – AI Drives Data Center Investment and Demand for Electricity
AI is causing major ripples throughout the Energy/Power industry with increased need for data centers
The growing market for artificial intelligence (AI) and cloud computing is driving unprecedented demand for data centers. In 2024, global data center investments eclipsed $455 billion, a 51% year over year increase. The largest infrastructure spenders—Google, Microsoft and AWS—accounted for more than 36% of all data center spending and are notable leaders in cloud and AI development. Considering the demand for these emerging technologies, tech giants are at the forefront of an industry-wide push, causing massive reverberations for data center construction and the electric power they so heavily rely on.
In fact, it is projected data centers could use up to 12 percent of all the electricity the U.S. produces by 2030, sparking both hesitation and opportunity for innovation. As such, the Energy, Power and Utilities industry will play a pivotal role in facilitating the expansion of AI, cloud, and overall digital transformation. Let’s take a closer look at the connection between AI adoption, data center investment and the impact it has on the power/energy industry.
AI Adoption Reverberates Across the Energy/Power Industry
With significant headway made last year, through expanding accessibility and functionality, it is safe to assert we are officially in the Age of AI. Carefully developed for decades, with exposure reserved to advanced technologists, savvy adopters, and sci-fi thrillers, 2024 by all metrics was a breakout year in bringing AI to the masses. Whether for business or individual-use, generative AI has bridged the artificial intelligence gap to the everyday person, providing efficiencies through content creation, problem solving, data analysis, business strategy and more, optimizing processes that increase service delivery speed and overall bandwidth for individuals and enterprises. The success of gen AI has energized tech innovators to further explore optimizations for key business processes, as seen in the rise of agentic AI, AI-empowered cybersecurity, and customized machine learning solutions.
Yet, as the International Energy Agency (IEA) pointedly reports, “There is no AI without energy—specifically electricity.” To leverage and unlock the full scale of AI, it relies on massive computing and storage power harnessed by data center facilities. These data centers are at the heart of AI growth, cloud computing and digital transformation. Due to the rate of AI development and adoption, proper infrastructure is needed to keep pace with this demand, as highlighted in the investment boom for data centers in the past year.
According to McKinsey, the data center market is expected to grow from 25 GW of demand in 2024 to over 80 GW in 2030. The central driving force behind this increase is the rate of digitalization and scaling AI across the business and technology landscape. Projections indicate gen AI can potentially create over $4 trillion in value throughout the global economy during this timeframe, but to reach this potential, an extra 60 GW of data center infrastructure would need to be developed in the U.S. alone. This is no small task, hinged on deep collaboration with the power/energy sector to provide the natural resources needed to create larger amounts of reliable electricity.
As such, there’s a twofold challenge that must be addressed to support the rise of AI. The first is to increase capacity through computing power, developing better, smarter chips, or central processing units (CPUs) that can handle increased data processing demands. This alleviation will help minimize stress on the second and most important challenge—delivering reliable energy from sustainable sources that can power the expansion of data centers while remaining committed to emission goals and carbon footprint reduction. Fittingly enough, experts cite AI as an innovative solution to address sustainable, clean energy goals, further underscoring the nuanced relationship between AI and power/energy.
Problem and Solution – AI Ups Energy Usage with Emission Reduction Potential
According to the recent IEA report, the expanding adoption of AI has, “huge implications for energy.” A data center supporting AI technology usually requires the same amount of energy it takes to power 100,000 households, and the larger buildouts are expected to consume 20 times as much. With the rise of data center investments in the U.S. and across the globe, there is legitimate concern around the power/energy sector’s ability to keep up with rising demand as well as sustainable initiatives.
This challenge offers opportunity for power/energy providers to elevate their current capabilities and generate creative solutions in the renewables space. By 2030, half of data center energy demand from around the globe will come from renewables. Successfully harnessing clean energy such as solar, wind, hydropower, etc., in combination with improved CPUs, will play a key role in solving the heightened energy demand caused by data center investment while also protecting against rising greenhouse gas emissions.
While the IEA projects AI to impact energy demands through data center expansion, it could also, “drive significant efficiencies across the energy sector.” This includes grid outage protection, innovation within energy and transportation, as well as optimization in harnessing natural resources. To this point, the efficiencies driven by AI-applications may lead to emissions reductions that outpace the rate of emissions released through data center expansion. Several ways for AI to help reduce emissions include:
- Demand Forecasting and Load Management – AI models predict electricity demand to optimize generation schedules, run renewables as primary energy sources before leveraging sources like coal/diesel, and enhance smart grids to better balance electric supply and demand.
- Renewable Energy Integration – AI adjust to the natural variance of renewable energy, improving dispatch planning, predictive maintenance to keep carbon-free sources online longer and storage optimization to guide when to release surplus energy to the grid.
- Power Plant Efficiency – AI enhance the combustion process to burn fuel more cleanly and efficiently as well as empower adaptive control systems to continuously monitor and tune operations towards reducing fuel consumption and emissions.
- Design and Planning – AI models enhance grid expansion and energy system design, configured to maximize clean energy and minimize emissions.
Properly configured AI can curtail waste, predict energy demand and improve the overall infrastructure of power/energy providers. As AI continues to advance, it has the potential to address some of the very issues exacerbated by its use, helping reduce carbon footprint and better protect our planet’s interconnected ecosystems.
Trusted Partner for Power/Utilities Industry
Seneca Resources has served the Power, Energy and Utilities industry for over 14 years, as a trusted partner delivering expert Staffing and Consulting services. This includes IT, Engineering and Business opportunities, which support mission-driven strategic goals and objectives for our clients. These valued customers range across the public and private sector, including State, Local and Federal Government, as well as Fortune 500 entities. We are privileged to be a long-standing partner to organizations such as Con Edison, PIKE, Dominion Energy, Southern Company and more.
Furthermore, Seneca Resources has proven expertise in data center and AI/ML capabilities, deeply understanding the competitive advantage of strategic AI solutions and the data center processing and storage it relies on for success. To learn more our industry experience or proven solutions, please contact Seneca Resources at info@senecahq.com.