Editorial illustration for AI boom could lift US carbon output; PJM cuts grid‑energy forecasts
AI Prompts Emit 50x More Carbon Than Expected
AI boom could lift US carbon output; PJM cuts grid‑energy forecasts
The surge in artificial‑intelligence workloads is reshaping how power planners think about future emissions. Companies racing to train ever larger models are building data‑center campuses that gobble megawatts, and those numbers are feeding into national carbon‑accounting debates. Yet the picture isn’t crystal‑clear; the electricity grid’s own demand forecasts have been in flux, prompting analysts to question whether the AI boom will simply add to the nation’s carbon tally or if smarter scheduling could blunt the impact.
While the technology promises efficiency gains, the underlying infrastructure still leans on fossil‑fuel generation in many regions. That tension becomes concrete when a major regional transmission organization revisits its outlook for how much power the system will need in the next few years. In order to get an accurate read on this, U
(Earlier this month, PJM, one of the largest regional transmission organizations in the country, downgraded its projections of how much energy the grid is going to need over the next couple of years after more carefully vetting some data center proposals.) In order to get an accurate read on this, UCS modelers used middle-range electric growth scenarios and assumed that just half the projects publicly announced in the pipeline would actually be built. But the Trump administration has moved so aggressively against both renewable energy and climate policies in the past year that the analysis likely underestimates how high emissions from data center demand could actually be.
Will the AI surge overwhelm the grid? The Union of Concerned Scientists warns that U.S. electricity demand could climb 60 to 80 percent by 2050, driven largely by data centers powering generative models.
Such growth would likely push carbon emissions higher and lift consumer bills, unless corrective steps are taken. Yet the analysis notes that modest policy tweaks—targeted efficiency standards, cleaner power procurement, or carbon pricing—could blunt both the emissions spike and the cost surge. PJM’s recent downgrade of its short‑term energy forecasts, after a tighter review of data‑center proposals, suggests that demand may be more nuanced than early estimates implied.
However, the report doesn't detail which specific measures would be most effective, leaving the policy path uncertain. Consequently, the projected carbon increase remains contingent on how quickly and comprehensively the recommended policies are adopted. The stakes are clear, but the timeline for meaningful action is still ambiguous.
Policymakers will need to balance growth with climate goals.
Further Reading
- AI: Five charts that put data-centre energy use – and emissions into context - Carbon Brief
- Explained: Generative AI's environmental impact - MIT News
- The AI-energy nexus will dictate AI's future. Here's why - World Economic Forum
- 'Roadmap' shows the environmental impact of AI data center boom - Cornell News
- AI's Carbon Problem Is Really a Grid Problem - American Enterprise Institute
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Common Questions Answered
How is the AI boom affecting electricity demand in the PJM grid region?
[Reuters.com](https://www.reuters.com/sustainability/boards-policy-regulation/americas-largest-power-grid-is-struggling-meet-demand-ai-2025-07-09/) reports that electricity bills are projected to surge by more than 20% this summer in PJM's territory, which covers 13 states and serves 67 million customers. The surge is primarily driven by data centers and AI chatbots consuming power faster than new plants can be built, creating significant strain on the power grid.
What challenges is PJM Interconnection facing with the growing AI and data center demand?
PJM is experiencing multiple challenges, including an 800% jump in prices at its annual capacity auction and criticism for delaying auctions and pausing new plant applications. The grid operator is struggling to balance the explosive growth of data centers, particularly in "Data Center Alley" in Northern Virginia, with the need to build new power generation capacity to meet increasing electricity demands.
What are the potential long-term implications of AI's energy consumption according to the IMF report?
[IMF.org](https://www.imf.org/-/media/Files/Publications/WP/2025/English/wpiea2025081-print-pdf.ashx) research suggests that under scenarios with constrained renewable energy capacity and limited transmission infrastructure, U.S. electricity prices could increase by 8.6%. The report also projects that U.S. and global carbon emissions could rise by 5.5% and 1.2% respectively under current policies, highlighting the need for aligned energy policies to support technological development while mitigating environmental impacts.