Tech
Report Questions Evidence Behind AI Industry’s Climate Claims
A new report by German non-profit Beyond Fossil Fuels has raised concerns about the strength of evidence supporting claims that artificial intelligence can significantly reduce global carbon emissions.
The group reviewed more than 150 climate-related statements made by leading AI companies and organisations, including the International Energy Agency. It found that only 26 per cent of the claims cited published academic research, while 36 per cent did not reference any evidence at all. The remaining claims relied on corporate reports, media coverage, NGO publications or unpublished academic work.
According to the report, many corporate sources lack peer-reviewed data or primary research to substantiate their projections. “The evidence for massive climate benefits of AI is weak, whilst the evidence of substantial harm is strong,” the authors wrote.
Estimates of AI’s environmental footprint vary widely. A January study published in the journal Patterns suggested that data centres alone may have emitted between 32.6 million and 79.7 million tonnes of carbon dioxide in 2025, roughly comparable to the annual emissions of a small European country.
By contrast, the International Energy Agency has argued that AI could cut global emissions by up to 5 per cent by 2035 by accelerating innovation in the energy sector. The agency has pointed to applications such as testing new battery chemistries and materials for solar power as examples of how AI might support cleaner technologies.
Beyond Fossil Fuels examined high-profile industry claims, including a projection cited by Google that AI could reduce global greenhouse gas emissions by 5 to 10 per cent by 2030 if widely adopted. The report traced the estimate back to a 2021 blog post by consulting firm Boston Consulting Group, which based the figure on client experience rather than peer-reviewed global analysis. Researchers described the claim as an extrapolation built on limited evidence.
The report also reviewed assertions that smaller, narrowly trained AI models are more environmentally efficient. It concluded that there is insufficient peer-reviewed research demonstrating that such systems can deliver measurable emissions reductions at scale.
In addition, the analysis said it found no verified example of generative AI systems such as OpenAI’s ChatGPT, Google’s Gemini or Microsoft’s Copilot producing substantial, measurable emissions cuts. Even if certain efficiencies exist, the report argues that they may be outweighed by the rapid expansion in energy use linked to data centre growth.
The authors said their findings do not suggest AI lacks climate benefits altogether, but they contend there is limited evidence that current applications can offset the sector’s growing energy demands. Requests for comment were sent to major AI firms and the International Energy Agency.
Tech
Global Rights Groups Call for AI Companies to Be Held Responsible for Children’s Safety
Tech
Study Says EU Regulations Are Slowing Rollout of Advanced AI Models
A new study by Governance.AI has found that European Union regulations are delaying the rollout of advanced artificial intelligence models, with technology companies increasingly pointing to the bloc’s regulatory framework as a key obstacle to launching new AI products in Europe.
The report examined 375 large language models (LLMs) released between June 2018 and May 2026, comparing their availability across the United States, the European Union and the United Kingdom. According to the findings, at least 11 percent of advanced AI model releases were either delayed or never launched in the EU compared with the United States. In the UK, the figure stood at 7 percent.
Researchers said they identified 68 cases in which AI models experienced delays or were withheld from specific markets. Regulatory factors were cited as the primary reason in 56 of those cases, making them the most common cause of restricted availability.
The study reviewed releases from major AI developers, including Meta, Google, OpenAI and Anthropic. Meta recorded the highest proportion of delayed or unavailable releases, with 26 percent of its AI models delayed or withheld in the EU and 15 percent in the UK. Anthropic’s Claude 3 Opus was highlighted as one example, with its web application arriving in the EU 71 days later than in the United States.
According to the report, data protection rules have emerged as the biggest regulatory hurdle, particularly for AI systems capable of processing images, audio and real-time video rather than text alone.
The researchers argued that uncertainty surrounding the application of the General Data Protection Regulation (GDPR) to AI model training and deployment has created additional challenges for developers. They also said enforcement of data protection rules has generally been stricter within the EU than in the UK, despite both jurisdictions sharing similar legal foundations following the adoption of the GDPR before Britain’s exit from the bloc.
The report noted that the full impact of newer legislation, including the Digital Markets Act, which began taking effect in 2023, and the Artificial Intelligence Act, adopted in 2024, has yet to be fully reflected in the data.
At the same time, the European Union is reviewing proposals aimed at making data rules more practical for AI development through its Digital Omnibus initiative. Lawmakers are also considering changes to copyright legislation and the AI Act’s copyright provisions to strengthen protections for creators, measures that researchers say could affect future AI model availability if implemented too strictly.
John Lidiard, a UK AI policy researcher and one of the report’s authors, said policymakers should consider the impact that regulatory barriers can have on businesses and consumers seeking access to the latest AI technologies. He said balancing innovation with effective oversight would remain a key challenge as governments continue to develop AI regulations.
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