Artificial intelligence dominated conversations at this year’s New York Climate Week, overshadowing even the usual climate-focused discussions. As world leaders gathered for the UN General Assembly, AI’s role in climate solutions—and its potential to worsen the crisis—became the central debate among investors, policymakers, and activists. The tension reflects a broader question: Can AI help meet climate goals, or will its energy demands push emissions further out of reach?
Climate goals are slipping, and AI complicates the picture
The urgency of the moment is undeniable. A recent UN Environment Programme report found the world has nearly passed the point where limiting global warming to 1.5°C above preindustrial levels is still possible. To reverse course, emissions must drop sharply while carbon removal technologies scale up to offset existing pollution. Yet AI’s rapid growth introduces new challenges.
UN Secretary-General António Guterres framed the dilemma in a speech at the assembly’s opening. “The climate crisis fuels instability and displacement,” he said. “Artificial intelligence could help solve all these challenges, or it could make them worse.” The statement captured the divide: AI could accelerate climate research, optimize energy grids, or even design new materials for carbon capture. But its insatiable appetite for power, driven by data centers, risks locking in decades of fossil-fuel dependence.
Data centers already consume vast amounts of electricity. Major tech firms like Microsoft, Google, and Meta have seen their emissions rise despite earlier pledges to go carbon-neutral. The reason? AI training and operations require more power than ever, and the infrastructure to support it is expanding fast. A 2026 report from Currence, a climate-tech finance tracker, shows venture capital investment in climate technologies hit $26 billion in the first half of the year, up 55% from 2025. But the funding isn’t distributed evenly.
Read Also: Lawmaker pushes to scrap U.S. border surveillance towers
While clean energy startups, especially those in nuclear, geothermal, wind, and solar, secure deals with tech giants, other critical areas are starving for capital. Carbon management and low-carbon fuels, essential for meeting emissions targets, saw venture funding plummet this year. The mismatch highlights a core problem: AI’s economic pull is redirecting resources away from solutions that don’t directly power data centers.
Public skepticism grows as emissions rise
The immediate impact of AI’s energy demands is visible. Natural gas plants are being built at record speeds to meet the surging power needs of data centers. These facilities have lifespans measured in decades, meaning even if cleaner alternatives emerge, the emissions from today’s infrastructure will linger for years. Meanwhile, communities near these sites report increased pollution and noise, fueling backlash.
Evelyn Wang, MIT’s vice president for energy and climate, acknowledged the trade-offs in a panel discussion. While AI could accelerate breakthroughs, such as discovering new catalysts for carbon capture, she noted that a whole lot of natural gas is coming online to meet the immediate demand created by new data centers. She puts the timeline at about a decade until data centers no longer add to planet-warming emissions. Yet that timeline feels distant to critics.
Overall, what I’m hearing this week is that many in the climate sector are skeptical of AI, at best. “AI leaders are now on thin ice when it comes to license to operate and sinking deep underwater when it comes to public support,” said UN climate chief Simon Stiell in a speech this week. “Tech titans need to start showing why the benefits of AI outweigh its skyrocketing costs, for the many, not just the tiny few.”
