Tech
European executives warn AI growth is outpacing infrastructure, Nokia survey finds
More than 1,000 business and technology leaders across Europe have raised serious concerns about the continent’s readiness to support the rapid expansion of artificial intelligence, according to a new study by Nokia. Executives identified energy supply, network capacity, and secure connectivity as the most pressing challenges that could slow the adoption of AI across industries.
The survey found that AI is already widely used by European companies, with 67% reporting that they have integrated the technology into their operations. Another 15% are running pilot projects, indicating that adoption is expected to grow significantly in the coming years. Many businesses see AI as essential for improving efficiency, automating processes, and strengthening innovation.
Cybersecurity emerged as the leading application area, with 63% of companies using AI to protect systems and data. Automation of business processes followed at 57%, while customer service tools such as chatbots and virtual assistants accounted for 55%. Companies are also using AI for product development, predictive analytics, robotics, and supply chain management.
Despite strong adoption, executives warned that infrastructure is struggling to keep pace with demand. Nokia’s report, titled “AI is too big for the European internet,” highlighted that Europe’s digital backbone is not yet equipped to handle large-scale AI workloads. The report noted that connectivity remains fragmented and security concerns persist, creating obstacles to expansion.
Energy supply was identified as the biggest constraint. About 87% of executives said they were worried that Europe’s energy infrastructure cannot meet rising AI demand. More than half said energy systems are already under strain or at risk. One in five companies reported delays to AI projects due to energy shortages, while others said they had to adjust project timelines or choose different locations because of limited power availability.
High electricity costs were also cited as a major concern, with 52% of executives saying Europe’s energy prices are not competitive compared to other regions. Limited grid capacity, slow approval processes, and restricted access to renewable energy sources were also highlighted as barriers.
As a result, 61% of executives said they are considering relocating data-intensive operations to regions with lower energy costs or have already taken steps in that direction. Only 16% said they plan to keep operations in Europe regardless of energy constraints.
Connectivity issues are also affecting companies. More than half reported network performance problems, including delays and downtime linked to increasing data traffic. Around 86% of executives expressed concern about internet reliability as AI usage continues to expand.
The report warned that global data traffic is expected to increase sharply by 2033, placing additional strain on existing networks. Business leaders called for greater investment in energy infrastructure, improved network capacity, and clearer regulations to support Europe’s ability to compete in the global AI race.
Tech
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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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