Why data centres are becoming a flashpoint in US towns

As AI and cloud computing drive unprecedented demand for digital infrastructure, Big Tech’s rapid expansion of data centres is increasingly colliding with resistance at the local level. Across the United States, communities are pushing back against large-scale facilities they say threaten their quality of life, environment, and local character.

Data centres, massive complexes packed with servers and supported by vast energy and water resources, are multiplying quickly as companies race to secure computing power and proximity to electricity grids. But as developers look beyond traditional tech hubs and into suburbs, small towns, and rural areas, they are finding residents far less welcoming than anticipated.

What were once quiet municipal board meetings are now drawing standing-room-only crowds. Residents argue that data centres bring few local jobs while consuming enormous amounts of electricity and water, generating constant noise, and relying on diesel generators that can affect air quality. In farming communities, the loss of open land and agricultural space has become a significant concern, as homeowners worry about declining property values and potential health risks.

Opposition efforts are becoming more organised and widespread. Community groups increasingly share tactics online, learning from similar struggles in other states. Yard signs, door-to-door campaigns, and legal challenges have become common tools for advocacy. According to industry observers, the level of resistance has reached unprecedented heights in infrastructure development.

Tracking groups report that dozens of proposed data centre projects worth tens of billions of dollars have recently been delayed or blocked due to local opposition and regulatory hurdles. In some US states, more than half of proposed developments are now encountering significant pushback, forcing developers to reconsider timelines, locations, or even entire projects.

Electricity costs are a major concern, fueling public anger. In regions already experiencing rising utility bills, residents fear that large data centres will further strain power grids and push prices even higher.

Water use is another flashpoint, particularly in areas that rely on wells and aquifers. Environmental advocates warn that long-term impacts are still poorly understood, leaving communities to shoulder the risks.

The growing resistance is having tangible consequences for the industry. Developers say uncertainty around zoning approvals and public support is reshaping investment strategies. Some companies are choosing to sell sites once they secure access to power, often the most valuable part of a project, rather than risk prolonged local battles that could ultimately derail construction.

Major technology firms, including Microsoft, Google, Amazon, and Meta, have largely avoided public comment on the mounting opposition. However, Microsoft has acknowledged in regulatory filings that community resistance and local moratoriums now represent a material risk to its infrastructure plans.

Industry representatives argue that misinformation has contributed to public fears, claiming that modern data centres are far cleaner and more efficient than critics suggest. In response, trade groups are urging developers to engage with communities earlier, be more transparent, and highlight the economic benefits, such as tax revenue and infrastructure investment. Promises of water conservation, energy efficiency, and community funding have become central to outreach efforts.

In some communities, frustration has been amplified by revelations that plans were discussed quietly among government agencies and utilities long before residents were informed. Once disclosed, these projects have sparked accusations of secrecy, accelerating public distrust and mobilisation.

Despite concessions and promises of further dialogue, many opponents say their fight is far from over. As demand for data centres continues to grow, the clash between global technology ambitions and local community concerns is shaping up to be one of the defining infrastructure battles of the digital age.

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Gmail enters the Gemini era with AI-powered inbox tools

Google is reshaping Gmail around its Gemini AI models, aiming to turn email into a proactive assistant for more than three billion users worldwide.

With inbox volumes continuing to rise, the focus shifts towards managing information flows instead of simply sending and receiving messages.

New AI Overviews allow Gmail to summarise long email threads and answer natural language questions directly from inbox content.

Users can retrieve details from past conversations without complex searches, while conversation summaries roll out globally at no cost, with advanced query features reserved for paid AI subscriptions.

Writing tools are also expanding, with Help Me Write, upgraded Suggested Replies, and Proofread features designed to speed up drafting while preserving individual tone and style.

Deeper personalisation is planned through connections with other Google services, enabling emails to reflect broader user context.

A redesigned AI Inbox further prioritises urgent messages and key tasks by analysing communication patterns and relationships.

Powered by Gemini 3, these features begin rolling out in the US in English, with additional languages and regions scheduled to follow during 2026.

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EU faces pressure to strengthen Digital Markets Act oversight

Rivals of major technology firms have criticised the European Commission for weak enforcement of the Digital Markets Act, arguing that slow procedures and limited transparency undermine the regulation’s effectiveness.

Feedback gathered during a Commission consultation highlights concerns about delaying tactics, interface designs that restrict user choice, and circumvention strategies used by designated gatekeepers.

The Digital Markets Act entered into force in March 2024, prompting several non-compliance investigations against Apple, Meta and Google. Although Apple and Meta have already faced fines, follow-up proceedings remain ongoing, while Google has yet to receive sanctions.

Smaller technology firms argue that enforcement lacks urgency, particularly in areas such as self-preferencing, data sharing, interoperability and digital advertising markets.

Concerns also extend to AI and cloud services, where respondents say the current framework fails to reflect market realities.

Generative AI tools, such as large language models, raise questions about whether existing platform categories remain adequate or whether new classifications are necessary. Cloud services face similar scrutiny, as major providers often fall below formal thresholds despite acting as critical gateways.

The Commission plans to submit a review report to the European Parliament and the Council by early May, drawing on findings from the consultation.

Proposed changes include binding timelines and interim measures aimed at strengthening enforcement and restoring confidence in the bloc’s flagship competition rules.

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Netomi shows how to scale enterprise AI safely

Netomi has developed a blueprint for scaling enterprise AI, utilising GPT-4.1 for rapid tool use and GPT-5.2 for multi-step reasoning. The platform supports complex workflows, policy compliance, and heavy operational loads, serving clients such as United Airlines and DraftKings.

The company emphasises three core lessons. First, systems must handle real-world complexity, orchestrating multiple APIs, databases, and tools to maintain state and situational awareness across multi-step workflows.

Second, parallelised architectures ensure low latency even under extreme demand, keeping response times fast and reliable during spikes in activity.

Third, governance is embedded directly into the runtime, enforcing compliance, protecting sensitive data, and providing deterministic fallbacks when AI confidence is low.

Netomi demonstrates how agentic AI can be safely scaled, providing enterprises with a model for auditable, predictable, and resilient intelligent systems. These practices serve as a roadmap for organisations seeking to move AI from experimental tools to production-ready infrastructure.

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Samsung puts AI trust and security at the centre of CES 2026

The South Korean tech giant, Samsung, used CES 2026 to foreground a cross-industry debate about trust, privacy and security in the age of AI.

During its Tech Forum session in Las Vegas, senior figures from AI research and industry argued that people will only fully accept AI when systems behave predictably, and users retain clear control instead of feeling locked inside opaque technologies.

Samsung outlined a trust-by-design philosophy centred on transparency, clarity and accountability. On-device AI was presented as a way to keep personal data local wherever possible, while cloud processing can be used selectively when scale is required.

Speakers said users increasingly want to know when AI is in operation, where their data is processed and how securely it is protected.

Security remained the core theme. Samsung highlighted its Knox platform and Knox Matrix to show how devices can authenticate one another and operate as a shared layer of protection.

Partnerships with companies such as Google and Microsoft were framed as essential for ecosystem-wide resilience. Although misinformation and misuse were recognised as real risks, the panel suggested that technological counter-measures will continue to develop alongside AI systems.

Consumer behaviour formed a final point of discussion. Amy Webb noted that people usually buy products for convenience rather than trust alone, meaning that AI will gain acceptance when it genuinely improves daily life.

The panel concluded that AI systems which embed transparency, robust security and meaningful user choice from the outset are most likely to earn long-term public confidence.

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Cloud and AI growth fuels EU push for greener data centres

Europe’s growing demand for cloud and AI services is driving a rapid expansion of data centres across the EU.

Policymakers now face the difficulty of supporting digital growth instead of undermining climate targets, yet reliable sustainability data remains scarce.

Operators are required to report on energy consumption, water usage, renewable sourcing and heat reuse, but only around one-third have submitted complete data so far.

Brussels plans to introduce a rating scheme from 2026 that grades data centres on environmental performance, potentially rewarding the most sustainable new facilities with faster approvals under the upcoming Cloud and AI Development Act.

Industry groups want the rules adjusted so operators using excess server heat to warm nearby homes are not penalised. Experts also argue that stronger auditing and stricter application of standards are essential so reported data becomes more transparent and credible.

Smaller data centres remain largely untracked even though they are often less efficient, while colocation facilities complicate oversight because customers manage their own servers. Idle machines also waste vast amounts of energy yet remain largely unmeasured.

Meanwhile, replacing old hardware may improve efficiency but comes with its own environmental cost.

Even if future centres run on cleaner power and reuse heat, the manufacturing footprint of the equipment inside them remains a major unanswered sustainability challenge.

Policymakers say better reporting is essential if the EU is to balance digital expansion with climate responsibility rather than allowing environmental blind spots to grow.

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Xi Jinping hails breakthroughs in China’s AI and semiconductor sectors

Chinese President Xi Jinping said 2025 marked a year of major breakthroughs for the country’s AI and semiconductor industries. In his New Year’s address, he said that Chinese technology firms had made significant progress in AI models and domestic chip development.

China’s AI sector gained global attention with the rise of DeepSeek. The company launched advanced models focused on reasoning and efficiency, drawing comparisons with leading US systems and triggering volatility in global technology markets.

Other Chinese firms also expanded their AI capabilities. Alibaba released new frontier models and pledged large-scale investment in cloud and AI infrastructure, while Huawei announced new computing technologies and AI chips to challenge dominant suppliers.

China’s progress prompted mixed international responses. Some European governments restricted the use of Chinese AI models over data security concerns, while US companies continued engaging with Chinese-linked AI firms through acquisitions and partnerships.

Looking ahead to 2026, China is expected to prioritise AI and semiconductors in its next five-year development plan. Analysts anticipate increased research funding, expanded infrastructure, and stronger support for emerging technology industries.

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Data centre cluster in Tennessee strengthens xAI’s compute ambitions

xAI is expanding its AI infrastructure in the southern United States after acquiring another data centre site near Memphis. The move significantly increases planned computing capacity and supports ambitions for large-scale AI training.

The expansion centres on the purchase of a third facility near Memphis, disclosed by Elon Musk in a post on X. The acquisition brings xAI’s total planned power capacity close to 2 gigawatts, placing the project among the most energy-intensive AI data centre developments currently underway.

xAI has already completed one major US facility in the area, known as Colossus, while a second site, Colossus 2, remains under construction. The newly acquired building, called MACROHARDRR, is located in Southaven and directly adjoins the Colossus 2 site, as previously reported.

By clustering facilities across neighbouring locations, xAI is creating a contiguous computing campus. The approach enables shared power, cooling, and high-speed data infrastructure for large-scale AI workloads.

The Memphis expansion underscores the rising computational demands of frontier AI models. By owning and controlling its infrastructure, xAI aims to secure long-term access to high-end compute as competition intensifies among firms investing heavily in AI data centres.

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New plan outlines how India will democratise AI infrastructure

India is moving to rebalance access to AI infrastructure as part of a new national push to close gaps in computing power and data availability.

A white paper released in December 2025 by the Principal Scientific Adviser outlines a strategy to treat AI compute, datasets and models as Digital Public Goods, rather than resources concentrated in a handful of urban hubs.

Despite generating nearly one-fifth of the world’s data, India currently hosts only a small share of global data centre capacity. The paper outlines plans to nearly tenfold capacity expansion by 2030, alongside the rollout of national computing resources through the IndiaAI Mission.

A central pool of GPUs and TPUs is being offered at subsidised rates to researchers and startups, aiming to reduce dependence on foreign cloud providers.

Data access and sovereignty form another pillar of the roadmap. Platforms such as IndiaAIKosh and Bhashini are being developed as shared repositories, hosting thousands of datasets and models across sectors including healthcare, agriculture and Indian languages.

High-performance computing initiatives, including the AIRAWAT supercomputer, are supporting large-scale research in areas such as climate modelling and drug discovery.

The strategy also emphasises regional and state-led infrastructure, with initiatives like Telangana’s federated data exchange seeking to decentralise AI development. Sustainability requirements are also being introduced, as data centres are expected to account for an increasing share of electricity use.

Policymakers view the approach as crucial to developing a form of sovereign AI that fosters innovation beyond major technology hubs and across the broader economy.

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Agentic AI plans push US agencies to prioritise data reform

US federal agencies planning to deploy agentic AI in 2026 are being told to prioritise data organisation as a prerequisite for effective adoption. AI infrastructure providers say poorly structured data remains a major barrier to turning agentic systems into operational tools.

Public sector executives at Amazon Web Services, Oracle, and Cisco said government clients are shifting focus away from basic chatbot use cases. Instead, agencies are seeking domain-specific AI systems capable of handling defined tasks and delivering measurable outcomes.

US industry leaders said achieving this shift requires modernising legacy infrastructure alongside cleaning, structuring, and contextualising data. Executives stressed that agentic AI depends on high-quality data pipelines that allow systems to act autonomously within defined parameters.

Oracle said its public sector strategy for 2026 centres on enabling context-aware AI through updated data assets. Company executives argued that AI systems are only effective when deeply aligned with an organisation’s underlying data environment.

The companies said early agentic AI use cases include document review, data entry, and network traffic management. Cloud infrastructure was also highlighted as critical for scaling agentic systems and accelerating innovation across government workflows.

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