Anthropic’s Pentagon dispute and military AI governance in 2026

On 28 February 2026, Anthropic’s Claude rose to No. 1 in Apple’s US App Store free rankings, overtaking OpenAI’s ChatGPT. The surge came shortly after OpenAI announced a partnership with the US Department of Defense (DoD), making its technology available to the US Army. The development prompted discussion among users and observers about whether concerns over military partnerships were influencing the shift to alternative AI tools.

Mere hours before the USD $200 million OpenAI-DoD deal was finalised, Anthropic was informed that its potential deal with the Pentagon had fallen through, largely because the AI company refused to relinquish total control of its technology for domestic mass surveillance. According to reporting, discussions broke down after Anthropic declined to grant the US government unrestricted control over its models, particularly for potential uses related to large-scale surveillance.

Following the breakdown of negotiations, US officials reportedly designated Anthropic as a ‘supply chain risk to national security’. The decision effectively limited the company’s participation in certain defence-related projects and highlighted growing tensions between AI developers’ safety policies and government expectations regarding national security technologies.

The debate over military partnerships sparked internal and industry-wide discussion. Caitlin Kalinowski, the former head of AR glasses hardware at Meta and the hardware leader at OpenAI, resigned soon after the US DoD deal, citing ethical concerns about the company’s involvement in military AI applications.

AI has driven recent technological innovation, with companies like Anduril and Palantir collaborating with the US DoD to deploy AI on and off the battlefield. The debate over AI’s role in military operations, surveillance, and security has intensified, especially as Middle East conflicts highlight its potential uses and risks.

Against this backdrop, the dispute between Anthropic and the Pentagon reflects a wider debate on how AI should be used in security and defence. Governments are increasingly relying on private tech companies to develop the systems that shape modern military capabilities, while those same companies are trying to set limits on how their technologies can be used.

As AI becomes more deeply integrated into security strategies around the world, the challenge may no longer be whether the technology will be used, but how it should be governed. The question is: who should ultimately decide where the limits of military AI lie?

Anthropic’s approach to military AI

Anthropic’s approach is closely tied to its concept of ‘constitutional AI’, a training method that guides how the model behaves by embedding a set of principles directly into its responses. Such principles are intended to reduce harmful outputs and ensure the system avoids unsafe or unethical uses. While such safeguards are intended to improve reliability and trust, they can also limit how the technology can be deployed in more sensitive contexts such as military operations.

Anthropic’s Constitution says its AI assistant should be ‘genuinely helpful’ to people and society, while avoiding unsafe, unethical, or deceptive actions. The document reflects the company’s broader effort to build safeguards into model deployment. In practice, Anthropic has set limits on certain applications of its technology, including uses related to large-scale surveillance or military operations.

Anthropic presents these safeguards as proof of its commitment to responsible AI. Reports indicate that concerns over unrestricted model access led to the breakdown in talks with the US DoD.

At the same time, Anthropic clarifies that its concerns are specific to certain uses of its technology. The company does not generally oppose cooperation with national security institutions. In a statement following the Pentagon’s designation of the company as a ‘supply chain risk to national security’, CEO Dario Amodei said, ‘Anthropic has much more in common with the US DoD than we have differences.’ He added that the company remains committed to ‘advancing US national security and defending the American people.’

The episode, therefore, highlights a nuanced position. Anthropic appears open to defence partnerships but seeks to maintain clearer limits on the deployment of its AI systems. The disagreement with the Pentagon ultimately reflects not a fundamental difference in goals, but rather different views on how far military institutions should be able to control and use advanced AI technologies.

Anthropic’s position illustrates a broader challenge facing governments and tech companies as AI becomes increasingly integrated into national security systems. While military and security institutions are eager to deploy advanced AI tools to support intelligence analysis, logistics, and operational planning, the companies developing these technologies are also seeking to establish safeguards for their use. Anthropic’s willingness to step back from a major defence partnership and challenge the Pentagon’s response underscores how some AI developers are trying to set limits on military uses of their systems.

Defence partnerships that shape the AI industry

While Anthropic has taken a cautious approach to military deployment of AI, other technology companies have pursued closer partnerships with defence institutions. One notable example is Palantir, the US data analytics firm co-founded by Peter Thiel that has longstanding relationships with numerous government agencies. Documents leaked in 2013 suggested that the company had contracts with at least 12 US government bodies. More recently, Palantir has expanded its defence offering through its Artificial Intelligence Platform (AIP), designed to support intelligence analysis and operational decision-making for military and security institutions.

Another prominent player is Anduril Industries, a US defence technology company focused on developing AI-enabled defence systems. The firm produces autonomous and semi-autonomous technologies, including unmanned aerial systems and surveillance platforms, which it supplies to the US DoD.

Shield AI, meanwhile, is developing autonomous flight software designed to operate in environments where GPS and communications may be unavailable. Its Hivemind AI platform powers drones that can navigate buildings and complex environments without human control. The company has worked with the US military to test these systems in training exercises and operational scenarios, including aircraft autonomy projects aimed at supporting fighter pilots.

The aforementioned partnerships illustrate how the US government has increasingly embraced AI as a key pillar of national defence and future military operations. In many cases, these technologies are already being used in operational contexts. Palantir’s Gotham and AIP, for instance, have supported US military and intelligence operations by processing satellite imagery, drone footage, and intercepted communications to help analysts identify patterns and potential threats.

Other companies are contributing to defence capabilities through autonomous systems development and hardware integration. Anduril supplies the US DoD with AI-enabled surveillance, drone, and counter-air systems designed to detect and respond to potential threats. At the same time, OpenAI’s technology is increasingly being integrated into national security and defence projects through growing collaboration with US defence institutions.

Such developments show that AI is no longer a supporting tool but a fundamental part of military infrastructure, influencing how defence organisations process information and make decisions. As governments deepen their reliance on private-sector AI, the emerging interplay among innovation, operational effectiveness, and oversight will define the central debate on military AI adoption.

The potential benefits of military AI

The debate over Anthropic’s restrictions on military AI use highlights the reasons governments invest in such technologies: defence institutions are drawn to AI because it processes vast amounts of information much faster than human analysts. Military operations generate massive data streams from satellites, drones, sensors, and communication networks, and AI systems can analyse them in near real time.

In 2017, the US DoD launched Project Maven to apply machine learning to drone and satellite imagery, enabling analysts to identify objects, movements, and potential threats on the battlefield faster than with traditional manual methods.

AI is increasingly used in military logistics and operational planning. It helps commanders anticipate equipment failures, enables predictive maintenance, optimises supply chains, and improves field asset readiness.

Recent conflicts have shown that AI-driven tools can enhance military intelligence and planning. In Ukraine, for example, forces reportedly used software to analyse satellite imagery, drone footage, and battlefield data. Key benefits include more efficient target identification, real-time tracking of troop movements, and clearer battlefield awareness through the integration of multiple data sources.

AI-assisted analysis has been used in intelligence and targeting during the Gaza conflict. Israeli defence systems use AI tools to rapidly process large datasets for surveillance and intelligence operations. The tools help analysts identify potential militant infrastructure, track movements, and prioritise key intelligence, thus speeding up information processing for teams during periods of high operational activity.

More broadly, AI is transforming the way militaries coordinate across land, air, sea, and cyber domains. AI integrates data from diverse sources, equipping commanders to interpret complex operational situations and enabling faster, informed decision-making. The advances reinforce why many governments see AI as essential for future defence planning.

Ethical concerns and Anthropic’s limits on military AI

Despite the operational advantages of military AI, its growing role in national defence systems has raised ethical concerns. Critics warn that overreliance on AI for intelligence analysis, targeting, or operational planning could introduce risks if the systems produce inaccurate outputs or are deployed without sufficient human oversight. Even highly capable models can generate misleading or incomplete information, which in high-stakes military contexts could have serious consequences.

Concerns about the reliability of AI systems are also linked to the quality of the data they learn from. Many models still struggle to distinguish authentic information from synthetic or manipulated content online. As generative AI becomes more widespread, the risk that systems may absorb inaccurate or fabricated data increases, potentially affecting how these tools interpret intelligence or analyse complex operational environments.

Questions about autonomy have also become a major issue in discussions around military AI. As AI systems become increasingly capable of analysing battlefield data and identifying potential targets, debates have emerged over how much decision-making authority they should be given. Many experts argue that decisions involving the use of lethal force should remain under meaningful human control to prevent unintended consequences or misidentification of targets.

Another area of concern relates to the potential expansion of surveillance capabilities. AI systems can analyse satellite imagery, communications data, and online activity at a scale beyond the capacity of human analysts alone. While such tools may help intelligence agencies detect threats more efficiently, critics warn that they could also enable large-scale monitoring if deployed without clear legal and institutional safeguards.

It is within this ethical landscape that Anthropic has attempted to position itself as a more cautious actor in the AI industry. Through initiatives such as Claude’s Constitution and its broader emphasis on AI safety, the company argues that powerful AI systems should include safeguards that limit harmful or unethical uses. Anthropic’s reported refusal to grant the Pentagon unrestricted control over its models during negotiations reflects this approach.

The disagreement between Anthropic and the US DoD therefore highlights a broader tension in the development of military AI. Governments increasingly view AI as a strategic technology capable of strengthening defence and intelligence capabilities, while some developers seek to impose limits on how their systems are deployed. As AI becomes more deeply embedded in national security strategies, the question may no longer be whether these technologies will be used, but who should define the boundaries of their use.

Military AI and the limits of corporate control

Anthropic’s dispute with the Pentagon shows that the debate over military AI is no longer only about technological capability. Questions of speed, efficiency, and battlefield advantage now collide with concerns over surveillance, autonomy, human oversight, and corporate responsibility. Governments increasingly see AI as a strategic asset, while companies such as Anthropic are trying to draw boundaries around how far their systems can go once they enter defence environments.

Contrasting approaches across the industry make the tension even clearer. Palantir, Anduril, Shield AI, and OpenAI have moved closer to defence partnerships, reflecting a broader push to integrate advanced AI into military infrastructure. Anthropic, by comparison, has tried to keep one foot in national security cooperation while resisting uses it views as unsafe or unethical. A divide of that kind suggests that the future of military AI may be shaped as much by company policies as by government strategy.

The growing reliance on private firms to build national security technologies has made governance harder to define. Military institutions want flexibility, scale, and operational control, while AI developers increasingly face pressure to decide whether they are simply suppliers or active gatekeepers of how their models are deployed. Anthropic’s position does not outright defence cooperation, but it does expose how fragile the relationship becomes when state priorities and corporate safeguards no longer align.

Military AI will continue to expand, whether through intelligence analysis, logistics, surveillance, or autonomous systems. Governance, however, remains the unresolved issue at the centre of that expansion. As AI becomes more deeply embedded in defence policy and military planning, should governments alone decide how far these systems can go, or should companies like Anthropic retain the power to set limits on their use?

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GitHub malware campaign uses SEO tricks to steal browser data

Cybersecurity researchers have uncovered a malware campaign spreading through over 100 GitHub repositories disguised as free software tools. Hackers used SEO-heavy descriptions to make their fake repositories appear high in search results, close to legitimate software.

Users searching for popular programs were directed to counterfeit download pages. These pages offered ZIP files containing BoryptGrab, a malware designed to steal data from infected Windows systems. The files were disguised as cracked software, gaming cheats, or utility tools.

The malware collects sensitive information, including browser passwords, cookies, and cryptocurrency wallet details. It can access nine major browsers, including Chrome, Edge, Firefox, Opera, Brave, and Vivaldi, and bypass some security protections.

Certain variants also install additional tools allowing remote access and persistent control over infected machines. However, this enables hackers to run commands, maintain ongoing access, and steal more information without the user’s knowledge.

Trend Micro, the cybersecurity firm that reported the campaign, noted some code and logs suggest a possible Russian origin, though attribution is not confirmed. Experts warn that GitHub and search engine manipulation make this attack method especially dangerous.

Users are advised to download software only from trusted sources and to verify the authenticity of the repository. Organisations should follow security best practices such as software allowlisting, maintaining inventory, and removing unauthorised applications to prevent similar attacks.

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Chinese tech hubs promote OpenClaw AI agent

Technology hubs in China are promoting the OpenClaw AI agent as part of new local industry initiatives. Officials in China say the open source tool can automate tasks such as email management and travel booking.

Cities including Shenzhen, Wuxi and Hefei are drafting policies to build an ecosystem around OpenClaw. Authorities in China are offering subsidies, computing resources and office support to encourage AI-driven one-person companies.

OpenClaw has grown rapidly since its release and has become one of the fastest-expanding projects on GitHub. Technology groups say the tool could allow individuals to operate businesses with far fewer employees.

Regulators have also warned about security and data protection risks linked to AI agents. Draft rules in China propose limits on access to sensitive data and stronger oversight of cross-border information flows.

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Canada warns about AI-generated scams targeting citizens online

Authorities in Canada have issued a warning about the growing use of AI in impersonation scams targeting citizens. Fraudsters increasingly deploy advanced tools capable of mimicking politicians, government officials and other public figures with convincing realism.

Deepfake videos, synthetic audio and AI-generated messages allow scammers to create convincing communications that appear to come from trusted authorities.

Such tactics are often used to persuade victims to send money, reveal personal information, install malicious software or engage with fraudulent investment offers.

Officials also warn about fake government websites created with AI-assisted tools that imitate official pages by copying national symbols and similar domain names. Suspicious websites often use unusual web addresses, extra characters, or unfamiliar domain endings to mislead visitors.

Authorities advise Canadians to verify unexpected messages through official channels rather than clicking links or responding immediately.

Suspected impersonation attempts should be reported to the Competition Bureau or the Canadian Anti-Fraud Centre.

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Dutch intelligence warns about phishing attacks on Signal and WhatsApp

A large-scale cyber campaign linked to state hackers is targeting accounts on the messaging platforms Signal and WhatsApp.

Intelligence services warn that phishing attacks aim to gain access to communications belonging to diplomats, military personnel and government officials.

The warning was issued by the Dutch intelligence agencies, General Intelligence and Security Service and Military Intelligence and Security Service, which confirmed that several government employees in the Netherlands have already been targeted during the campaign.

Security officials believe the operation forms part of a broader intelligence effort focused on individuals considered valuable to foreign state interests.

Journalists and other public figures may also be potential targets as attackers attempt to monitor sensitive conversations or gather confidential information.

Authorities advise users to remain cautious when receiving unexpected messages or login requests on encrypted messaging platforms.

Phishing attempts designed to capture account credentials remain one of the most effective methods used in cyberespionage campaigns.

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Microsoft launches Copilot Cowork to automate tasks across Microsoft 365

AI is moving from assistance to execution as Microsoft introduces Copilot Cowork, a system designed to perform tasks across the Microsoft 365 environment.

Instead of simply generating text or suggestions, the feature allows users to delegate real work by describing a desired outcome.

Copilot Cowork converts requests into structured plans that run in the background. The system analyses signals from workplace tools such as Microsoft Outlook, Microsoft Teams and Microsoft Excel to understand schedules, documents and ongoing projects.

Users can approve or modify each step while the AI coordinates actions across meetings, files and messages.

Several enterprise scenarios illustrate the system’s capabilities. Cowork can reorganise calendars by analysing meetings and automatically proposing schedule changes.

It can also prepare complete briefing materials for customer meetings by collecting relevant emails, files and data before generating presentations and research summaries.

The technology also supports deeper analysis tasks. Users can request company research and receive structured outputs that include summaries, financial data and supporting documents.

In product launch planning, Cowork can compile competitive intelligence, build presentations and outline project milestones, creating a coordinated workflow for teams.

Microsoft emphasises that the system operates within enterprise security boundaries. Identity, compliance policies and data permissions remain enforced while tasks execute in a protected cloud environment.

The platform also reflects a multi-model strategy, combining Microsoft AI capabilities with Anthropic technology through the integration of the model behind Claude.

Copilot Cowork is currently available to a limited group of customers through a research preview.

Wider availability is expected later in 2026 through Microsoft’s Frontier programme as the company expands AI-driven workplace automation.

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Smart Classrooms initiative transforms learning in 10 Thai pilot schools

Ten pilot schools in Buriram and Si Sa Ket provinces have launched Smart Classrooms under the UNESCO–Huawei TEOSA initiative, supporting Thailand’s drive to expand digital education.

Led by UNESCO Bangkok in partnership with Thailand’s Ministry of Education and Huawei Technologies Co., Ltd, the Smart Classrooms initiative aims to strengthen digital learning environments, equip teachers with digital and AI competencies, and support policy development for AI in education. The programme also supports Thailand’s ‘Transforming Education in the Digital Era’ policy and the National AI Strategy and Action Plan (2022–2027).

Each province has one designated ‘mother school’ that serves as a regional digital hub, supporting four surrounding ‘child schools’ by sharing resources, training, and expertise. The ten pilot schools in total have received high-speed internet, interactive digital displays, and collaborative learning platforms that support real-time content sharing and blended learning. Forty-five teachers from the pilot schools also participated in hands-on demonstrations of Smart Classrooms systems on 4–5 March.

‘This new technology will help translate theory into practice, allowing students to experiment, test strategies, and see results immediately,’ said Pathanapong Momprakhon, Principal of Paisan Pittayakom School. UNESCO Bangkok’s Deputy Director and Chief of Education, Marina Patrier, highlighted the importance of combining infrastructure with teacher capacity-building.

‘At UNESCO, we are committed to promoting the ethical and inclusive use of AI in ways that empower teachers and expand opportunities for every learner,’ Ms Patrier said at the launch. ‘While Smart Classrooms provide important tools, it is teachers’ creativity, professional judgement and leadership that ultimately bring these innovations to life.’

Chitralada Chanyaem of the Thai National Commission for UNESCO highlighted the importance of collaboration in advancing digital education.

‘The UNESCO–Huawei Funds-in-Trust Project on Technology-Enabled Open Schools for All stands as a powerful example of collaboration dedicated to transforming education into a system that is open, inclusive, flexible, and resilient in the face of a rapidly changing world, she said. ‘As the future of education cannot be confined within classroom walls, it must bridge sectors and communities, working collaboratively to create equitable and sustainable opportunities for all.’

Teachers observed Huawei technical staff and master teachers demonstrate how digital tools and AI-supported applications can be used in everyday lessons. Ms Piyaporn Kidsirianan, Public Relations Manager at Huawei Technologies (Thailand) Co., Ltd, said the initiative aims to reduce digital inequality.

‘The Open Schools for All initiative represents a commitment to using technology as a bridge to deliver quality education to remote and underserved communities.’ The TEOSA Smart Classrooms initiative combines policy support, digital infrastructure upgrades, and teacher training to help translate Thailand’s digital education ambitions into practical impact at the school level.

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Malaysia expands AI learning across universities with Google tools

AI tools from Google are now available across all public universities in Malaysia after the nationwide deployment of Gemini for Education.

An initiative that integrates AI capabilities into university systems, providing digital research and learning support to nearly 600,000 students and 75,000 faculty members.

The rollout is coordinated with the Ministry of Higher Education Malaysia as part of the country’s broader strategy to become an AI-driven economy by 2030. Universities already using Google Workspace for

Education can now access advanced tools, including NotebookLM and the reasoning model Gemini 3.1 Pro, which are designed to support research, writing and personalised learning.

Several universities are already experimenting with AI-assisted teaching. At Universiti Malaysia Perlis, lecturers have created customised AI assistants to guide students through specialised engineering courses.

Meanwhile, researchers and students at Universiti Putra Malaysia are using AI tools to improve literature reviews and academic research workflows.

Other institutions are focusing on digital literacy and AI skills.

At Universiti Malaysia Sarawak, hundreds of lecturers and students are receiving AI certifications, while training programmes are expanding across campuses.

Officials believe the combination of AI tools, training and research support will strengthen the education system of Malaysia and prepare graduates for an increasingly AI-driven economy.

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Network Slicing unlocks powerful opportunities for Africa’s 5G future

Accelerating the deployment of standalone 5G networks is the most critical step for enabling network slicing in Africa. Standalone 5G uses cloud-native cores that allow operators to create and manage virtual network slices with guaranteed performance. Many African networks still rely on non-standalone architecture, which limits full slicing capabilities.

Releasing and harmonising mid-band spectrum is another key policy priority. Spectrum in the 3.5 GHz band is particularly important for delivering high throughput and low latency. Without timely spectrum allocation, operators may struggle to support advanced industrial and enterprise applications.

Clear enterprise service frameworks are also essential. Industries such as mining, logistics, and energy require reliable connectivity with strict service-level agreements. Regulators and operators must define transparent pricing models and performance guarantees to support enterprise adoption.

Investment in automation and technical skills will also play a central role. Network slicing relies on AI-driven orchestration, cloud infrastructure, and cybersecurity capabilities. Strengthening technical expertise will help operators manage complex network environments.

Once these policy foundations are in place, network slicing can unlock new business models for telecom providers. Operators can offer slice-as-a-service, allowing enterprises to subscribe to dedicated network segments tailored to specific operational needs.

African telecom companies are already exploring these opportunities. Operators such as MTN, Vodacom, Safaricom, and Telkom are developing enterprise connectivity solutions for sectors including mining, manufacturing, logistics, and energy.

Private 5G deployments in mining operations illustrate the potential value of these services. Dedicated networks support automation, real-time monitoring, and remote equipment management. These projects often involve multi-year contracts worth several million dollars.

Network slicing also enables telecom providers to move beyond traditional consumer data services. Instead of charging primarily for data volume, operators can generate revenue from long-term enterprise connectivity and managed digital services.

As 5G infrastructure expands across the continent, network slicing is expected to play an increasing role in enterprise connectivity. By aligning network performance with industry needs, it could become a key driver of digital transformation in Africa.

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AI security risks grow as companies integrate AI into daily workflows

AI is rapidly transforming workplaces as companies automate tasks and boost productivity. From writing code to analysing documents, AI tools help employees work faster, but also introduce new AI security and compliance risks.

One of the main concerns is the handling of sensitive information. Employees may upload confidential documents, proprietary code, or customer data into AI chatbots without realising the consequences. Doing so could violate privacy regulations such as the EU’s GDPR or breach internal non-disclosure agreements, making AI security an important priority for organisations.

Another challenge is the reliability of AI-generated content. While large language models can produce convincing responses, they sometimes generate false information, which is a phenomenon known as hallucination. High-profile cases have already shown professionals submitting work with fabricated references generated by AI. Such incidents highlight the need for rigorous AI security and oversight.

Cybersecurity risks are also growing. AI systems rely on complex infrastructure that can become targets for attackers through techniques such as prompt injection, which tricks the model into producing unintended responses, or data poisoning, which involves injecting malicious data into training sets to alter behaviour or outputs. Addressing these threats requires stronger AI security practices and careful monitoring.

When adopting AI, organisations must develop clear policies, strengthen cybersecurity measures, and maintain human oversight. Taking those steps is essential to ensuring that the technology is used safely and responsibly.

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