The Trump administration has taken the unusual step of intervening in an environmental lawsuit against Elon Musk’s AI company xAI, arguing that the data centre at the centre of the dispute is so important to national security that it should be protected from legal action seeking to restrict its power supply.

Dilemma

The case highlights a growing sustainability dilemma facing the AI industry. For example, while artificial intelligence is increasingly being positioned as a tool for solving global challenges, its rapidly growing appetite for electricity is creating new environmental pressures, particularly as operators race to build ever-larger data centres.

Why The Government Has Intervened

The dispute in the U.S. centres on xAI’s Colossus AI facility in Mississippi, which relies on dozens of methane gas turbines to help power the infrastructure used to train and operate Grok, the company’s AI model.

The National Association for the Advancement of Colored People (NAACP), one of the oldest and largest civil rights organisations in the United States, filed the lawsuit. In this case, the NAACP’s Mississippi State Conference filed it. The lawsuit alleges that the turbines are operating without the permits required under the Clean Air Act and are contributing to air pollution that could affect nearby communities.

However, in a court filing submitted on behalf of the United States government, the Department of Justice argued that the lawsuit threatens “American national, economic, and energy security by seeking to shut off the power supply for artificial-intelligence innovation that supports the Department of War’s military operations.”

The filing seeks dismissal of the case and represents an unusually direct intervention by the federal government in support of a private technology company.

Why Grok Is Being Treated As A Strategic Asset

A key part of the government’s argument is that Grok has become integrated into sensitive national security operations. For example, according to a declaration submitted by Cameron Stanley, Chief Digital and Artificial Intelligence Officer at the Department of War (previously known as the Department of Defense), xAI’s Grok is “one of only four proprietary state-of-the-art (‘frontier’) AI models currently capable of supporting national security applications”.

The declaration also states that the Department relies on a specialised version known as Grok Gov Model and that it provides capabilities “found in no other frontier AI model”.

The filing claims that if the Mississippi facility were unable to continue operating at its current scale, the development and improvement of future Grok models could be affected, potentially impacting military and intelligence capabilities.

Whether or not the court ultimately accepts those arguments, the case demonstrates how rapidly advanced AI systems are being reclassified from commercial technology platforms into infrastructure that governments increasingly view as strategically important.

The Environmental Cost Of AI Growth

The environmental concerns at the heart of the case are difficult to ignore. For example, the turbines reportedly emit pollutants including nitrogen oxides and particulate matter, both of which have been linked to respiratory and cardiovascular health problems. Environmental groups argue that communities living near the facility should not bear the environmental cost of powering AI systems.

Also, the growth of AI is creating unprecedented demand for electricity. Modern AI models require vast numbers of processors working simultaneously, and those processors need enormous amounts of power.

The result is that many technology companies are now competing for access to electricity on a scale more commonly associated with heavy industry.

This creates an uncomfortable contradiction. Many of the same companies investing heavily in sustainability initiatives and clean technologies are simultaneously searching for whatever energy sources can support their rapidly expanding AI ambitions.

The Search For Cleaner Alternatives

The controversy also highlights why technology companies and investors are increasingly searching for lower-carbon energy sources capable of supporting AI’s growing power demands. One recent example is Critical Energy, a startup founded by a former SpaceX engineer that has raised $22 million to develop modular geothermal turbines for geothermal power plants. The company argues that geothermal energy could provide reliable, round-the-clock electricity for energy-hungry AI infrastructure years before many advanced nuclear projects become commercially available.

Projects such as these are attracting growing attention because geothermal energy can provide continuous power without the intermittency associated with solar or wind generation.

For the AI industry, that matters because data centres require power around the clock, making reliability almost as important as sustainability.

The challenge, however, is that many cleaner energy projects take years to deploy, while AI demand is growing today.

What Does This Mean For Your Organisation?

This case essentially offers an early glimpse of a debate that is likely to become increasingly common over the next decade. Governments want to lead in AI. Businesses want access to more powerful AI tools. At the same time, communities, regulators, and environmental groups are demanding that growth happens responsibly, and the lawsuit against xAI sits directly at the intersection of those competing priorities.

For organisations investing in AI, the wider lesson is that sustainability is becoming an infrastructure issue as much as a software issue. Questions about where AI runs, how it is powered, and what environmental impacts it creates are likely to become increasingly important alongside discussions about capability, productivity, and security.

The case also suggests that some governments are beginning to treat advanced AI infrastructure in much the same way as power stations, telecommunications networks, and defence assets. If that trend continues, future debates about AI may focus as much on energy policy and environmental impact as they do on the technology itself.

The political backdrop is also difficult to overlook in this particular case. Given Elon Musk’s close relationship with the Trump administration, some critics are likely to question whether the government’s intervention reflects purely national security concerns or whether political considerations may also have played a role. The administration maintains that its position is based on the strategic importance of the AI infrastructure involved.

The outcome of this particular lawsuit remains uncertain at this point. What is already clear, however, is that the race to build more powerful AI systems is creating difficult choices between economic growth, national security, environmental protection, and sustainable energy development, choices that governments, businesses, and communities will increasingly be forced to confront.

Microsoft’s new ‘Cowork’ feature in Copilot lets you assign tasks by simply describing the outcome, with Copilot creating a plan, using your Microsoft 365 data, and carrying out tasks across apps in the background while keeping you in control at every step.

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If Gemini AI prompts in Google Docs are getting in the way of your writing, there’s a quick way to turn them off and regain a cleaner, more focused workspace.

Why This Matters

Google has been steadily integrating Gemini into Google Docs, Sheets, Gmail, and other Workspace applications. While many users find the AI features useful, others prefer a cleaner writing environment without AI prompts appearing on screen.

Reducing these prompts can make documents feel less cluttered, help you focus on writing, and give you more control over when and how you use AI tools.

How To Hide The Gemini Bottom Bar In Google Docs

If you see a Gemini prompt box at the bottom of your document, you can hide it:

• Open your Google Doc.
• Click Gemini in the menu bar.
• Select Bottom Bar Preferences.
• Turn off the Gemini bottom bar.

This removes the AI prompt panel from the bottom of the document while allowing you to access Gemini manually if you need it later.

How To Reduce AI Features Across Google Workspace

You can also disable some Workspace smart features that power AI-driven suggestions and personalisation.

• Open Gmail.
• Click the Settings cog.
• Select See All Settings.
• Scroll down to Google Workspace Smart Features.
• Click Manage Workspace Smart Feature Settings.
• Turn off Smart Features in Google Workspace if you no longer want these features enabled.

This setting affects several Google Workspace applications and may reduce some AI-powered suggestions and prompts.

Things To Keep In Mind

Turning off Workspace smart features does not necessarily remove every Gemini capability from your Google account. Some Gemini features may still be available depending on your Google Workspace subscription, administrator settings, and the specific applications you use.

However, these settings can significantly reduce AI prompts and create a cleaner, less distracting workspace for users who prefer to write and work without constant AI assistance.

A Cleaner Way To Work

AI tools can be useful when you need them, but many people don’t want them appearing every time they open a document. Taking a few moments to adjust these settings can help create a simpler, more focused Google Docs experience while still allowing you to use Gemini when you choose to.

Signal has accused the UK government of proposing a dangerous form of surveillance after ministers announced plans that could require technology companies to prevent children from taking, sharing, or viewing nude images on smartphones and tablets.

What Is The Government Proposing?

The announcement came from Prime Minister Keir Starmer during London Tech Week, where he said the UK would become “the first country in the world to make it impossible for children to take, share or view nude images.”

Under the proposals, technology companies including Apple and Google would be expected to activate existing safety features or introduce new technical measures that detect and block nude images on devices used by children. Adults would still be able to access such content after completing age verification checks.

Three-Month Deadline

The government has given technology companies three months to develop suitable solutions. If they do not, ministers have indicated they are prepared to introduce legislation, financial penalties, and potentially other enforcement measures.

The government argues that stronger intervention is needed because online child sexual abuse, exploitation, and exposure to harmful content remain widespread. Home Office figures cited alongside the announcement indicate that 91 per cent of online child sexual abuse reports recorded in 2024 contained self-generated content from children themselves.

Why Is Signal Opposing The Plan?

Signal, one of the world’s best-known encrypted messaging platforms, has responded forcefully to the proposals. In a public statement, the company said the government’s approach “will not safeguard children. It endangers us all.”

The company’s main concern is not the goal of protecting children, but the technology required to achieve it. Signal argues that forcing devices to scan content before it is viewed, shared, or stored would create a new form of surveillance infrastructure capable of examining private information on users’ devices.

According to Signal, “Forcing all UK residents to prove their age and/or have all their content scanned, simply to exercise their fundamental right to communicate, is a perilous proposition.”

The company also warned that once such capabilities exist, they rarely remain limited to their original purpose. Signal stated: “We know that mass surveillance and censorship capabilities, however sincere-sounding the promises of those who initiate them are, never remain narrowly scoped.”

The Debate Around Client-Side Scanning

At the centre of the controversy is a technology known as client-side scanning.

Unlike traditional content monitoring, which takes place on external servers, client-side scanning operates directly on the user’s device. Supporters argue this provides a compromise between privacy and safety because images do not need to be sent elsewhere for inspection.

Advocates say the approach can prevent harmful content from being created, viewed, or shared while keeping personal information on the device itself.

Critics, however, argue that the distinction is not as clear-cut as it appears.

Although images may never leave the device, the device is still examining content on behalf of a third party. Privacy groups have long argued that this changes the fundamental trust relationship between users and their devices.

Signal’s concern is that the same scanning infrastructure could potentially be expanded in future to identify other forms of content beyond child protection material. Whether or not such powers were ever used, critics argue that the capability itself creates new risks around surveillance, censorship, security vulnerabilities, and public trust.

A Wider Privacy Battle

The disagreement reflects a much broader debate that has been developing for years.

Previous UK legislation, including the Investigatory Powers Act and aspects of the Online Safety Act, has generated similar disputes between governments seeking stronger online protections and privacy advocates concerned about the long-term consequences of expanding monitoring powers.

Technology companies have also faced these questions before. Apple, for example, previously proposed a system for detecting child sexual abuse material on devices before ultimately abandoning the project following widespread criticism from privacy and security experts.

Supporters of the government’s latest proposals argue that child protection must take priority. Organisations including the NSPCC, Internet Watch Foundation, Barnardo’s, and the Children’s Commissioner for England have publicly welcomed the plans.

NSPCC chief executive Chris Sherwood described the proposal as “a major step forward in our fight against online child sexual abuse.”

What Does This Mean For Your Business?

The wider significance of this dispute isn’t really about nude image detection. It is about where governments, technology companies, and citizens draw the line between child protection and personal privacy, particularly when proposals involve technology capable of examining content directly on people’s devices.

The debate also highlights a growing tension that businesses are increasingly encountering across cyber security, compliance, artificial intelligence, and digital regulation. Governments are seeking stronger protections against genuine harms, while technology providers and privacy advocates are warning about the unintended consequences of expanding monitoring capabilities.

The larger issue here is not simply whether children should be protected online, as few would disagree with that objective. The real debate is whether it is possible to achieve those protections without creating technologies that examine private content on personal devices. As governments around the world continue to grapple with that question, the outcome is likely to influence the future of privacy, encryption, and digital communications far beyond the UK.

A small but growing group of businesses is now spending thousands of dollars per employee every month on artificial intelligence, suggesting that AI is increasingly being treated as core business infrastructure rather than simply another productivity tool.

The Rise Of The “AI-Pilled” Company

The findings come from the latest Ramp AI Index, which analyses anonymised spending data from more than 70,000 US businesses to track how organisations are adopting AI.

Until recently, most AI adoption studies focused on whether businesses were using AI or not. Ramp now believes that question is becoming less useful as AI adoption becomes increasingly widespread. Instead, the company is focusing on what it calls the “intensity of adoption”, i.e., how heavily businesses are actually investing in AI.

One of the report’s most eye-catching findings is that the top 1 per cent of firms, described by Ramp as “AI-pilled”, are spending an average of $7,449 per employee per month on AI services. By comparison, the top 10 per cent spend around $611 per employee, while the median business spends just $11.38, roughly equivalent to a single ChatGPT or Claude subscription.

The figures highlight just how wide the gap is becoming between businesses experimenting with AI and those building it deeply into everyday operations.

What Does “AI-Pilled” Mean?

The tech sector term “AI-pilled” essentially describes organisations that have moved beyond occasional AI use and started treating AI as a core operating model.

At Ramp itself, chief product officer Geoff Charles recently outlined how the company achieved 99.5 per cent AI adoption among employees, with more than 1,500 internal applications reportedly created in six weeks by over 800 different staff members.

The goal is not simply to give employees access to chatbots. Instead, it involves embedding AI into workflows, automating routine tasks, building internal tools, deploying coding agents, and allowing staff across multiple departments to use AI as part of their daily work.

In these organisations, AI is increasingly viewed as a business capability rather than a software product.

Still Cheaper Than Hiring People

Despite the impressive spending figures, Ramp’s research suggests that AI has not yet reached the point where organisations are routinely spending more on AI than on employees.

The report notes that “the top 1 per cent of firms spend $7.45K per employee per month” but also points out that this remains less than half the typical monthly salary of a software engineer.

That finding is important because it challenges some of the more dramatic claims surrounding AI adoption.

Recent headlines have highlighted companies spending heavily on AI agents, tokens, and computing power, while some technology executives have suggested AI could eventually become a larger cost centre than human labour.

For now, however, the data suggests that even the most advanced adopters continue to view AI as something that augments employees rather than replaces them entirely.

Why Spending Continues To Rise

Perhaps the most significant finding is not how much these firms are spending, but how quickly that spending is growing. For example, Ramp found that the top 1 per cent of AI users increased spending per employee by 14.1 per cent in a single month.

This is happening despite growing awareness of AI costs and increasing efforts to use cheaper models where possible.

The report notes that many businesses are actively seeking lower-cost alternatives, including open-source models and newer competitors such as DeepSeek, yet overall spending continues to climb.

One explanation is that businesses are moving from occasional AI usage towards much broader deployment. As organisations connect AI into customer service, software development, analytics, administration, marketing, finance, and operations, overall consumption naturally increases.

The more AI becomes embedded into business processes, the more computing power, tokens, APIs, and specialist tools are required to support it.

No Single Vendor Dominates

Another interesting finding is that the most advanced AI users are not putting all their eggs in one basket.

According to Ramp, “advanced usage of AI means using multiple frontier models”, alongside platforms providing access to open-source models and specialist AI-native software.

This suggests that businesses are becoming increasingly sophisticated in how they approach AI procurement.

Rather than committing exclusively to one provider, many organisations appear to be selecting different models for different tasks based on performance, capabilities, security requirements, and cost.

That approach mirrors earlier developments in cloud computing, where organisations often adopted multi-cloud strategies to reduce dependence on a single supplier.

Why This Matters

The wider significance of Ramp’s findings is not really about the $7,500 figure. The more important story here is that a growing number of businesses now appear to view AI as an operational resource that sits alongside software, cloud infrastructure, and human expertise.

For years, technology adoption was largely measured by whether organisations used a tool at all. Increasingly, the competitive gap may depend on how deeply AI becomes integrated into workflows and decision-making processes.

The data also suggests that AI adoption is becoming far more uneven. While many businesses remain at the subscription stage, a small group of early adopters is investing heavily and experimenting with entirely new ways of operating.

What Does This Mean For Your Business?

For businesses, the report highlights an important distinction between using AI and building around AI.

Most organisations are unlikely to spend thousands of dollars per employee each month on AI in the foreseeable future. However, the research suggests that some companies are already treating AI as a strategic capability worthy of significant ongoing investment.

That doesn’t necessarily mean every business should increase its AI budget dramatically. Ramp’s figures measure spending, not outcomes, and high expenditure alone does not guarantee productivity gains or return on investment.

The more useful lesson here may be that leading adopters are moving beyond standalone chatbots and experimenting with AI agents, automation, workflow integration, and multi-model strategies. As the technology continues to mature, the organisations that learn how to apply AI effectively across their operations may gain a greater advantage than those that simply spend the most money on it.

A German court has ruled that Google can be held directly responsible for false information generated by its AI Overviews feature, a decision that could have significant implications for AI-powered search engines and chatbots worldwide.

What Happened?

The case centres on Google’s AI Overviews, the AI-generated summaries that increasingly appear at the top of search results and attempt to answer users’ questions directly without requiring them to visit other websites.

The ruling came after two German publishers discovered that AI Overviews had falsely associated them with scams, subscription traps, and questionable business practices. According to court documents, the AI-generated summaries created links and allegations that did not appear in the sources cited by Google.

The Regional Court of Munich issued an injunction preventing Google from repeating the statements and concluded that the AI-generated content should be treated as Google’s own speech rather than merely a summary of information published elsewhere.

Why The Court Reached This Decision

The most significant aspect of the ruling is the distinction the judges drew between traditional search results and AI-generated answers.

For many years, search engines have generally benefited from limited liability protections because they primarily act as intermediaries, directing users to content created by third parties. If a search result links to an inaccurate webpage, responsibility normally rests with the publisher of that page rather than the search engine itself.

AI Overviews operate differently. According to the Munich court’s judgment, AI Overviews do not simply display links or snippets. Instead, they create “independent, new and substantive statements” that are generated by Google’s AI systems and presented to users as complete answers. The judges noted that Google controls the AI model and the algorithms that produce these summaries and therefore has responsibility for the content they generate.

The court also highlighted that the disputed statements were not simply copied from third-party websites. In several cases, the AI generated connections and allegations that were not present in the source material at all.

Why Google’s Defence Failed

Google argued that users can inspect the sources linked within AI Overviews and therefore verify information for themselves. However, the court rejected that argument.

The judges compared AI Overviews to headlines or teaser text that many readers consume without investigating further. They concluded that if an AI-generated answer is presented as a complete and understandable response, the fact that users could conduct additional research does not remove responsibility from the party that published it.

The court also found that AI Overviews are not essential to the functioning of search in the same way that traditional search results are. Users can still find information through ordinary links without requiring an AI-generated summary.

That distinction helped the judges justify imposing a higher level of responsibility on Google for AI-generated content than has historically applied to search engines.

Google Plans To Appeal

Google has confirmed that it intends to challenge the ruling. A company spokesperson told Reuters that the case focuses on specific errors rather than the fundamental operation of AI Overviews and said the company disagrees with the court’s conclusions.

Google also argued that the overwhelming majority of AI Overviews are accurate, while acknowledging that AI systems can occasionally miss context or misinterpret information. The company says it takes action when policy violations are identified.

The case remains a preliminary injunction rather than a final appellate ruling, meaning the legal position could still change as appeals progress.

A New Liability Challenge For AI

AI systems increasingly generate answers by analysing information from multiple sources and presenting users with a single, consolidated response. That approach is now common across search engines, chatbots, virtual assistants, and business productivity tools.

The Munich court’s reasoning suggests that once an AI system begins creating its own narrative, combining information from multiple sources and generating new conclusions, the provider may no longer be able to rely on the legal protections traditionally available to search engines and hosting platforms.

If that principle survives appeal, it could affect a wide range of AI products, including AI-powered search tools, enterprise assistants, customer service bots, and generative AI platforms.

Also, regulators across Europe are paying closer attention to AI transparency, accountability, and safety. Questions about who should be responsible when an AI system produces false, defamatory, or harmful information are becoming increasingly important as these tools become more widely used by businesses and consumers alike.

What Does This Mean For Your Business?

Most businesses are unlikely to see any immediate operational impact from the ruling, but it highlights an issue that organisations should already be considering.

AI-generated answers can appear authoritative and convincing while still containing errors, misunderstandings, or entirely fabricated information. As AI tools become more deeply embedded into search engines, productivity software, and business workflows, organisations should avoid treating AI-generated content as automatically accurate.

The ruling also serves as a reminder that businesses should monitor how AI systems describe their brands, products, and services online. If an AI-generated summary contains false information, legal avenues for challenging those statements may become clearer if courts increasingly view AI output as the responsibility of the platform that generated it.

More broadly, the case signals that regulators and courts are beginning to move beyond the question of what AI can do and focus instead on who should be accountable when it gets things wrong.