Claims that artificial intelligence could become a powerful weapon against climate change are increasingly being challenged, with analysts warning that much of the narrative amounts to greenwashing as energy-intensive AI services expand rapidly across the global economy.
Rising concern over AI’s growing carbon footprint
Industry leaders have promoted AI as a tool for optimising energy grids, modelling climate systems, and accelerating green innovation. But critics argue these benefits are being overstated while the sector’s own environmental impact is rising sharply.
According to recent assessments from the International Energy Agency, electricity demand from data centres, cloud computing, and AI workloads is accelerating faster than most national decarbonisation plans can accommodate. Training large language models, running complex simulations, and generating video content require vast computing power — and in many regions that power still comes primarily from fossil fuels.
Analysts call climate messaging “diversionary”
Climate researchers and sustainability analysts say the AI industry is leaning on selective success stories to distract from a broader structural problem: the rapid growth of energy-hungry infrastructure.
They point to a surge in advanced functions such as deep research tools, synthetic media generation, and always-on AI assistants, all of which drive continuous demand for high-performance servers. While companies highlight efficiency gains per computation, total emissions continue to rise as usage scales.
Environmental groups including Greenpeace argue that this pattern mirrors earlier tech cycles, where marginal efficiency improvements were overwhelmed by explosive growth in overall consumption — a classic rebound effect.
From productivity promise to power-hungry reality
The core issue is not whether AI can assist climate modelling or optimise logistics. It is whether those gains outweigh the expanding energy footprint of the technology itself.
Major AI providers, including OpenAI and hyperscale cloud operators, have pledged to run on cleaner energy over time. Yet new data centres are being built faster than renewable capacity in many markets, forcing operators to rely on existing grids that remain carbon-intensive.
Meanwhile, corporate adoption of AI is accelerating across finance, media, marketing, and research — sectors that previously had relatively modest computing needs. Video generation alone consumes orders of magnitude more energy than text-based applications, adding further strain to already stretched systems.
Climate tech or climate liability?
Experts warn that portraying AI as a climate solution without confronting its energy costs risks delaying more effective action. Investment may be diverted toward speculative AI-driven efficiency tools instead of proven measures such as grid upgrades, storage deployment, and direct emissions reductions.
Some analysts also caution that “AI for climate” narratives can provide political cover for expanding digital infrastructure without robust environmental oversight, particularly in jurisdictions competing to attract data centre investment.
The result is a growing gap between public messaging and physical reality: while marketing materials emphasise sustainability dashboards and optimisation algorithms, emissions linked to digital infrastructure continue to climb.
Implications for investors and policymakers
For investors, the debate highlights a material risk often overlooked in AI valuations: energy dependency. As electricity prices rise and governments tighten climate rules, operating costs for compute-heavy businesses could increase significantly.
For policymakers, the challenge is to ensure transparency. Without mandatory reporting of AI-related energy use and emissions, claims of climate benefit remain difficult to verify.
AI may yet play a role in climate adaptation and mitigation. But critics insist that only a full accounting of its environmental impact — paired with binding commitments to clean power — can move the conversation beyond branding.
Until then, they argue, promises that AI will “fix” the climate look less like innovation — and more like distraction.
Newshub Editorial in Global – 17 February 2026
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