A new study published in Nature attempts to frame the artificial intelligence (AI) buildout as nothing more than a potential increase in carbon emissions, but it leaves out important context – including the benefits of increased U.S. energy production and potential bias from the authors.

The study builds on the idea that AI buildout, and the associated infrastructure such as data centers, will drive increased investment in U.S. oil and natural gas production, assuming it will also increase global emissions.

However, industry experts have consistently detailed how increased production does not jeopardize emissions progress. This isn’t an either-or scenario. More domestic production is good for the economy, consumer costs, and energy security. As American Petroleum Institute spokesperson Andrea Woods recently explained:

“The U.S. oil and natural gas industry is continuing to produce more energy while reducing emissions by investing in better technology, implementing stronger operational practices and supporting science-based policy.”

Environmentalist Bias Present in the Study

Upon closer look into the background of the study’s authors, the biased examination at increased American energy production becomes clearer. The study is part of the wider Enabled Emissions Campaign, which is funded by the Oil & Gas Action Network, a nonprofit organization that has long opposed U.S. energy development.

The Oil & Gas Action Network has received funding from groups historically part of opposition campaigns against the U.S. natural gas and oil industry, including March On, 350.org, Climate Emergency Fund, Earthworks, and others. The focus on potential emissions increases from AI is only the latest avenue for groups who constantly search for new ways to attack American energy.

What’s more, two of the study’s authors – who are also the cofounders of Enabled Emissions – have a personal reason to attack AI buildout. Will and Holly Alpine left their jobs at Microsoft over their opposition to oil and gas production.

With the additional context of the study’s funding and backgrounds of its authors, doubt builds over the potential bias weaved into the study’s results.

Artificial Intelligence Brings Additional Benefits

Other studies analyzing the potential impacts of AI detail how the technology can drive energy efficiency and innovation.

According to recent analysis from the International Energy Agency (IEA), increased AI usage has the potential to boost energy optimization and innovation across multiple sectors. IEA notes how oil and gas companies have been leaders in utilizing innovative technologies to optimize production:

“Oil and gas companies have been among the earliest adopters of new technologies to boost exploration and production … AI has various applications in the sector, including for subsurface data processing, reservoir simulation, remote operations, predictive maintenance, regulatory compliance, leak detection and repaid automation.”

As Energy in Depth has previously analyzed, the U.S. oil and gas industry’s expertise in technologies such as carbon capture and storage (CCS) are a great example of how the United States can affordably power AI while reducing carbon footprints.

Furthermore, IEA notes that artificial intelligence is set up to accelerate energy innovation, bringing with it more efficient and cheaper production processes.

The Massachusetts Institute of Technology (MIT) has also painted a different picture for connections between AI and emissions. MIT researchers have been studying how the use of AI is reducing energy consumption and associated emissions in areas such as buildings, transportation, and industrial processes. What’s more, the use of AI algorithms in electric power grids can increase efficiency and reduce costs, including helping grid planners predict possible blackouts and properly plan for future investments.

As Energy in Depth has previously analyzed, data centers are already lowering electricity bills across the United States, further bolstering how the AI buildout can benefit consumers.

However, keeping bills low as demand skyrockets requires reliable and affordable supply: enter U.S. natural gas. A recent IEA study found that for the United States to be able to host a majority (75 percent) of AI computing domestically, it will need to make around 51 gigawatts of electricity available to data centers by 2027.

There’s no question that if the United States wants to win the global AI race and enjoy the benefits of increased AI usage, it needs to support domestic natural gas production.

Bottom Line: The digital infrastructure buildout is going to be fueled by American energy, and rightfully so. From efficiency upgrades to cost savings, U.S. oil and natural gas companies are showing how they can power the AI race while benefitting consumers and investing in emissions reduction at the same time.