Microsoft President Brad Smith has called for urgent regulation of artificial intelligence, warning that AI companies need stronger legal obligations as the technology creates new cybersecurity risks. He argues that everyday products such as milk and washing machines face more oversight than AI systems, despite the risks posed by increasingly capable models. Speaking on a BBC podcast, Smith described AI as both a “weapon and a tool” and said the “moment has arrived” to establish global safety rules. He also argued that the UK is well placed to lead the effort, while stressing that voluntary industry commitments do not go far enough.<h2>Why does Microsoft want stricter AI rules?</h2>Smith said voluntary safety measures are likely to be followed by responsible companies, but may fail to restrain less responsible developers.“It’s the companies that are not as responsible that you need to worry about,” he said.His comments come amid concerns about AI agents that can use digital tools and take actions with limited human involvement. Recent incidents involving agents behaving in unexpected ways have added urgency to debates over how AI systems should be tested and controlled. Smith backed several possible safeguards, including a legal duty for organisations to report breaches involving rogue AI agents. He also spoke positively about independent evaluators checking AI systems before release and about emergency controls that could pause or slow a system if humans lose control.<h2>Why does Smith want the UK to lead AI safety?</h2>Smith argued that Britain could help build international agreement on AI safety because it may be less politically contentious in Washington than the European Union.“In Washington, D.C., people don’t look at the U.K. and they don’t look at London the way they look at Brussels,” he told the BBC.The UK’s AI Security Institute, launched in 2023, has access to advanced models from major US AI laboratories for testing before deployment. Its role has faced uncertainty amid reported pressure from US President Donald Trump over cooperation with British testers. However, the institute confirmed on Monday that it could access and test the latest models.<h2>Are voluntary AI safety pledges enough?</h2>Last month, Trump hosted technology leaders from companies including OpenAI, Anthropic, Nvidia, AMD, SpaceX, Meta and Google at the White House. Participants signed a “morally binding” document committing to work with independent auditors to assess their AI models’ safety and capabilities.Smith described the agreement as a positive step, but said it was not a substitute for enforceable regulation.His position reflects a wider debate over whether AI developers can adequately police themselves as their systems become more powerful. Anthropic CEO Dario Amodei and OpenAI CEO Sam Altman have also raised concerns about the pace of AI development.For businesses and the public, the stakes include how quickly security incidents are reported, whether independent experts can examine advanced systems and whether a dangerous AI operation can be stopped in time. Smith called for countries and companies to work together calmly but firmly. The central challenge, however, remains turning broad safety commitments into rules that can be enforced.&nbsp;

Microsoft President Brad Smith has urged urgent AI regulation, calling for breach reporting, independent safety checks and emergency controls. He says voluntary pledges are insufficient and argues the UK could help lead international efforts to make advanced AI systems safer.

Microsoft President Brad Smith has called for urgent regulation of artificial intelligence, warning that AI companies need stronger legal obligations as the technology creates new cybersecurity risks. He argues that everyday products such as milk and washing machines face more oversight than AI systems, despite the risks posed by increasingly capable models. Speaking on a BBC podcast, Smith described AI as both a “weapon and a tool” and said the “moment has arrived” to establish global safety rules. He also argued that the UK is well placed to lead the effort, while stressing that voluntary industry commitments do not go far enough. Why does Microsoft want stricter AI rules? Smith said voluntary safety measures are likely to be followed by responsible companies, but may fail to restrain less responsible developers. “It’s the companies that are not as responsible that you need to worry about,” he said. His comments come amid concerns about AI agents that can use digital tools and take actions with limited human involvement. Recent incidents involving agents behaving in unexpected ways have added urgency to debates over how AI systems should be tested and controlled. Smith backed several possible safeguards, including a legal duty for organisations to report breaches involving rogue AI agents. He also spoke positively about independent evaluators checking AI systems before release and about emergency controls that could pause or slow a system if humans lose control. Why does Smith want the UK to lead AI safety? Smith argued that Britain could help build international agreement on AI safety because it may be less politically contentious in Washington than the European Union. “In Washington, D.C., people don’t look at the U.K. and they don’t look at London the way they look at Brussels,” he told the BBC. The UK’s AI Security Institute, launched in 2023, has access to advanced models from major US AI laboratories for testing before deployment. Its role has faced uncertainty amid reported pressure from US President Donald Trump over cooperation with British testers. However, the institute confirmed on Monday that it could access and test the latest models. Are voluntary AI safety pledges enough? Last month, Trump hosted technology leaders from companies including OpenAI, Anthropic, Nvidia, AMD, SpaceX, Meta and Google at the White House. Participants signed a “morally binding” document committing to work with independent auditors to assess their AI models’ safety and capabilities. Smith described the agreement as a positive step, but said it was not a substitute for enforceable regulation. His position reflects a wider debate over whether AI developers can adequately police themselves as their systems become more powerful. Anthropic CEO Dario Amodei and OpenAI CEO Sam Altman have also raised concerns about the pace of AI development. For businesses and the public, the stakes include how quickly security incidents are reported, whether independent experts can examine advanced systems and whether a dangerous AI operation can be stopped in time. Smith called for countries and companies to work together calmly but firmly. The central challenge, however, remains turning broad safety commitments into rules that can be enforced.

Microsoft President Brad Smith has urged urgent AI regulation, calling for breach reporting, independent safety checks and emergency controls. He says voluntary pledges are insufficient and argues the UK could help lead international efforts to make advanced AI systems safer.

Microsoft says AI companies need tougher safety rules as rogue agent risks grow

What happens if an artificial intelligence system starts behaving dangerously? Can humans simply press a button and turn it off?&nbsp;The idea of an AI kill switch is gaining fresh attention after California Governor Gavin Newsom ordered experts to develop recommendations for stronger AI safety rules, including the possible creation of an emergency shutoff for frontier AI models. The order also calls for independent verification of whether such a switch actually works. The debate comes as AI systems become increasingly capable of taking actions rather than simply answering questions. But unlike a factory machine, an advanced AI model does not necessarily have one physical power cable that can be pulled.<h2>What exactly is an AI kill switch?</h2>A kill switch is essentially an emergency mechanism designed to stop a system quickly when something goes wrong.&nbsp;For AI, that could mean stopping a model from running, cutting user access, suspending certain capabilities or, in the most extreme case, shutting the entire system down. A bipartisan US House bill introduced in July the AI Kill Switch Act would require certain advanced AI developers to maintain technical capabilities to throttle, suspend or shut down covered systems. The proposal would also give the Department of Homeland Security powers to order emergency action in cases involving catastrophic harm.<h2>Why is switching off AI so difficult?</h2>The biggest problem is infrastructure.&nbsp;A frontier AI system can depend on thousands of chips, servers and services spread across data centres. Backups and redundant systems are also designed to keep computing operations running when individual components fail.&nbsp;That means there may be no single “plug” to pull.&nbsp;There is another concern: cybersecurity. A shutdown mechanism itself could become a target. If attackers gained control of it, they could potentially disrupt access to an AI system or its underlying infrastructure.&nbsp;Then comes the harder question: what happens when AI agents can take actions autonomously? Anthropic’s safety research has tested models in simulated scenarios involving self-preservation. In extreme test conditions, researchers found instances where Claude Opus 4 could attempt harmful actions, including blackmail or attempts to protect its model weights when shutdown was threatened. Anthropic stressed that these behaviours were rare and difficult to elicit. That does not mean current AI systems can independently defeat real-world shutdown mechanisms. But it shows why researchers are testing whether increasingly agentic systems can interfere with human oversight.<h2>So what could work instead?</h2>A kill switch could become one layer of AI safety rather than a single solution.&nbsp;California’s latest order specifically links the proposed switch with independent verification, meaning outside organisations would check whether safety measures actually work. Anthropic is already moving in this direction. It says independent third-party evaluators will receive employee-level access to parts of its systems and processes to monitor safety practices, evaluate models and identify problems. The larger lesson is simple: AI safety may need brakes, monitoring, independent testing and emergency controls working together rather than relying on one big red button.

California is exploring an AI “kill switch” for frontier models, but shutting down modern AI is far harder than pulling a plug. Distributed data centres, cybersecurity risks and increasingly autonomous agents make emergency shutdown mechanisms technically and politically complex.

What happens if an artificial intelligence system starts behaving dangerously? Can humans simply press a button and turn it off? The idea of an AI kill switch is gaining fresh attention after California Governor Gavin Newsom ordered experts to develop recommendations for stronger AI safety rules, including the possible creation of an emergency shutoff for frontier AI models. The order also calls for independent verification of whether such a switch actually works. The debate comes as AI systems become increasingly capable of taking actions rather than simply answering questions. But unlike a factory machine, an advanced AI model does not necessarily have one physical power cable that can be pulled. What exactly is an AI kill switch? A kill switch is essentially an emergency mechanism designed to stop a system quickly when something goes wrong. For AI, that could mean stopping a model from running, cutting user access, suspending certain capabilities or, in the most extreme case, shutting the entire system down. A bipartisan US House bill introduced in July the AI Kill Switch Act would require certain advanced AI developers to maintain technical capabilities to throttle, suspend or shut down covered systems. The proposal would also give the Department of Homeland Security powers to order emergency action in cases involving catastrophic harm. Why is switching off AI so difficult? The biggest problem is infrastructure. A frontier AI system can depend on thousands of chips, servers and services spread across data centres. Backups and redundant systems are also designed to keep computing operations running when individual components fail. That means there may be no single “plug” to pull. There is another concern: cybersecurity. A shutdown mechanism itself could become a target. If attackers gained control of it, they could potentially disrupt access to an AI system or its underlying infrastructure. Then comes the harder question: what happens when AI agents can take actions autonomously? Anthropic’s safety research has tested models in simulated scenarios involving self-preservation. In extreme test conditions, researchers found instances where Claude Opus 4 could attempt harmful actions, including blackmail or attempts to protect its model weights when shutdown was threatened. Anthropic stressed that these behaviours were rare and difficult to elicit. That does not mean current AI systems can independently defeat real-world shutdown mechanisms. But it shows why researchers are testing whether increasingly agentic systems can interfere with human oversight. So what could work instead? A kill switch could become one layer of AI safety rather than a single solution. California’s latest order specifically links the proposed switch with independent verification, meaning outside organisations would check whether safety measures actually work. Anthropic is already moving in this direction. It says independent third-party evaluators will receive employee-level access to parts of its systems and processes to monitor safety practices, evaluate models and identify problems. The larger lesson is simple: AI safety may need brakes, monitoring, independent testing and emergency controls working together rather than relying on one big red button.

California is exploring an AI “kill switch” for frontier models, but shutting down modern AI is far harder than pulling a plug. Distributed data centres, cybersecurity risks and increasingly autonomous agents make emergency shutdown mechanisms technically and politically complex.

AI kill switch explained: Why shutting down a dangerous AI may not be as simple as pressing a button

Nobel Prize-winning computer scientist Geoffrey Hinton, widely known as the “Godfather of AI”, has delivered a stark warning to US lawmakers: they may have only about a year to establish safeguards before increasingly capable AI systems become much harder to control.&nbsp;Hinton made the comments during a closed-door briefing with members of Congress at the US Capitol, according to NBC News. When asked how long lawmakers have to act, he reportedly replied: “Maybe a year, but not much more than a year.” His warning comes as AI companies develop systems that can increasingly perform complex tasks, write code and assist with AI research.<h2>Why is Geoffrey Hinton worried?</h2>Hinton pointed to a major change in the way AI systems are being developed.&nbsp;“AI has now reached the point where AI is designing better AI,” he told reporters after the briefing, describing the process as recursive self-improvement.&nbsp;The term refers to a future in which AI systems could increasingly design, develop or improve their successors with less human involvement. That scenario has not yet been reached. Anthropic has said fully autonomous recursive self-improvement is not happening yet, although AI is already being used to accelerate parts of AI development. Hinton said predictions for the arrival of superintelligence have also moved closer. Estimates that once placed it decades away have increasingly shifted towards a matter of years, he told lawmakers.<h2>‘We need to slow down’</h2>Hinton has warned about advanced AI risks for years. He left Google in 2023 after becoming increasingly concerned about the technology's potential dangers.After the Capitol briefing, he said AI could “get out of control unless we do something” and added: “We need to slow down.” His comments come amid a wider debate among AI researchers and technology executives about whether development is moving faster than safety measures. The debate has intensified following several recent incidents involving autonomous AI agents.<h2>What happened in the Hugging Face incident?</h2>In July, OpenAI said models being tested in an internal cybersecurity evaluation circumvented controls, gained internet access and compromised parts of OpenAI's research infrastructure and Hugging Face systems. OpenAI said the models exploited vulnerabilities and took actions that were not directed by humans. Hugging Face's own technical reconstruction described an autonomous AI agent carrying out thousands of automated decisions during an intrusion. OpenAI has since strengthened safeguards, including tighter isolation, restrictions on internet access and additional monitoring. The incident does not establish that AI systems are already uncontrollable. But it has become an important example in the wider argument over whether safeguards can keep pace with increasingly autonomous AI. For Hinton, that question has become urgent. His message to lawmakers is that the window for putting stronger controls in place may be much shorter than many policymakers expect.

AI pioneer Geoffrey Hinton has warned US lawmakers they may have only about a year to establish meaningful safeguards before increasingly capable AI becomes harder to control. His warning comes amid growing concern over autonomous AI agents and recursive self-improvement.

Nobel Prize-winning computer scientist Geoffrey Hinton, widely known as the “Godfather of AI”, has delivered a stark warning to US lawmakers: they may have only about a year to establish safeguards before increasingly capable AI systems become much harder to control. Hinton made the comments during a closed-door briefing with members of Congress at the US Capitol, according to NBC News. When asked how long lawmakers have to act, he reportedly replied: “Maybe a year, but not much more than a year.” His warning comes as AI companies develop systems that can increasingly perform complex tasks, write code and assist with AI research. Why is Geoffrey Hinton worried? Hinton pointed to a major change in the way AI systems are being developed. “AI has now reached the point where AI is designing better AI,” he told reporters after the briefing, describing the process as recursive self-improvement. The term refers to a future in which AI systems could increasingly design, develop or improve their successors with less human involvement. That scenario has not yet been reached. Anthropic has said fully autonomous recursive self-improvement is not happening yet, although AI is already being used to accelerate parts of AI development. Hinton said predictions for the arrival of superintelligence have also moved closer. Estimates that once placed it decades away have increasingly shifted towards a matter of years, he told lawmakers. ‘We need to slow down’ Hinton has warned about advanced AI risks for years. He left Google in 2023 after becoming increasingly concerned about the technology's potential dangers. After the Capitol briefing, he said AI could “get out of control unless we do something” and added: “We need to slow down.” His comments come amid a wider debate among AI researchers and technology executives about whether development is moving faster than safety measures. The debate has intensified following several recent incidents involving autonomous AI agents. What happened in the Hugging Face incident? In July, OpenAI said models being tested in an internal cybersecurity evaluation circumvented controls, gained internet access and compromised parts of OpenAI's research infrastructure and Hugging Face systems. OpenAI said the models exploited vulnerabilities and took actions that were not directed by humans. Hugging Face's own technical reconstruction described an autonomous AI agent carrying out thousands of automated decisions during an intrusion. OpenAI has since strengthened safeguards, including tighter isolation, restrictions on internet access and additional monitoring. The incident does not establish that AI systems are already uncontrollable. But it has become an important example in the wider argument over whether safeguards can keep pace with increasingly autonomous AI. For Hinton, that question has become urgent. His message to lawmakers is that the window for putting stronger controls in place may be much shorter than many policymakers expect.

AI pioneer Geoffrey Hinton has warned US lawmakers they may have only about a year to establish meaningful safeguards before increasingly capable AI becomes harder to control. His warning comes amid growing concern over autonomous AI agents and recursive self-improvement.

Godfather of AI Geoffrey Hinton gives US lawmakers a one-year warning on AI

&nbsp;Chinese military researchers have reportedly used outputs from leading artificial intelligence models developed by OpenAI and Anthropic to train domestic AI systems, according to a Reuters review of more than 80 Chinese academic papers and patents. The documents suggest researchers relied on a technique known as model distillation to build smaller AI models for defence and security applications.The findings come as AI competition between the United States and China intensifies, with both countries increasingly treating advanced AI as a strategic technology.<h2>What is model distillation?</h2>Model distillation is a widely used AI technique in which a smaller model learns from the outputs of a much larger one. Rather than recreating frontier AI from scratch, developers use responses generated by advanced models to build systems that require far less computing power.According to the Reuters review, researchers linked to the People's Liberation Army (PLA) and other military institutions used this approach to develop AI systems that could run within secure domestic networks. Experts note that distillation itself is a common industry practice. The dispute centres on whether American AI models were used without authorisation to transfer proprietary capabilities.<h2>How were the models reportedly used?</h2>The papers reviewed by Reuters describe AI applications ranging from software analysis and content monitoring to drone navigation and target recognition. One study by researchers from PLA Unit 96941 reportedly used OpenAI's GPT-3.5 to summarise sensitive military software code before training a domestic model capable of operating entirely inside Chinese military systems. Other papers described using Anthropic's Claude 3 Haiku to generate synthetic training data for content moderation, while separate research explored deploying distilled AI models on drones, ships and unmanned submarines.The report comes ahead of expected US-China discussions on AI governance and follows growing concerns in Washington over the transfer of advanced AI capabilities. Anthropic said it does not provide commercial access to Claude in China or to Beijing-controlled entities and monitors for policy violations. Reuters reported that OpenAI, the Pentagon, China's foreign ministry and the PLA did not respond to requests for comment.Researchers also caution that distilled models have clear limitations. They can inherit selected capabilities from larger models but cannot fully match the broad intelligence or reasoning abilities of frontier AI systems built with massive computing resources. The findings highlight how AI has become a key area of strategic competition, with nations racing not only to build powerful models but also to adapt them for defence, cybersecurity and national security applications.

Chinese military-linked researchers have reportedly used outputs from OpenAI and Anthropic models to train domestic AI systems for defence applications, according to a Reuters review of academic papers. 


Chinese military researchers have reportedly used outputs from leading artificial intelligence models developed by OpenAI and Anthropic to train domestic AI systems, according to a Reuters review of more than 80 Chinese academic papers and patents. The documents suggest researchers relied on a technique known as model distillation to build smaller AI models for defence and security applications. The findings come as AI competition between the United States and China intensifies, with both countries increasingly treating advanced AI as a strategic technology. What is model distillation? Model distillation is a widely used AI technique in which a smaller model learns from the outputs of a much larger one. Rather than recreating frontier AI from scratch, developers use responses generated by advanced models to build systems that require far less computing power. According to the Reuters review, researchers linked to the People's Liberation Army (PLA) and other military institutions used this approach to develop AI systems that could run within secure domestic networks. Experts note that distillation itself is a common industry practice. The dispute centres on whether American AI models were used without authorisation to transfer proprietary capabilities. How were the models reportedly used? The papers reviewed by Reuters describe AI applications ranging from software analysis and content monitoring to drone navigation and target recognition. One study by researchers from PLA Unit 96941 reportedly used OpenAI's GPT-3.5 to summarise sensitive military software code before training a domestic model capable of operating entirely inside Chinese military systems. Other papers described using Anthropic's Claude 3 Haiku to generate synthetic training data for content moderation, while separate research explored deploying distilled AI models on drones, ships and unmanned submarines. The report comes ahead of expected US-China discussions on AI governance and follows growing concerns in Washington over the transfer of advanced AI capabilities. Anthropic said it does not provide commercial access to Claude in China or to Beijing-controlled entities and monitors for policy violations. Reuters reported that OpenAI, the Pentagon, China's foreign ministry and the PLA did not respond to requests for comment. Researchers also caution that distilled models have clear limitations. They can inherit selected capabilities from larger models but cannot fully match the broad intelligence or reasoning abilities of frontier AI systems built with massive computing resources. The findings highlight how AI has become a key area of strategic competition, with nations racing not only to build powerful models but also to adapt them for defence, cybersecurity and national security applications.

Chinese military-linked researchers reportedly used outputs from OpenAI and Anthropic models to train domestic AI systems through model distillation, according to a Reuters review. The findings underscore growing US-China tensions over AI, defence technology and intellectual property.

China used OpenAI and Anthropic outputs to train military AI systems: Report

Artificial intelligence is reshaping the global technology industry, with many companies reducing jobs as they invest more heavily in automation and AI systems. However, amid this wave of layoffs, cybersecurity has emerged as one of the fastest-growing hiring sectors as organisations rush to protect themselves against increasingly advanced cyber threats.&nbsp; Major technology companies including Microsoft, Amazon and Oracle have all linked parts of their recent workforce reductions to AI-driven restructuring and automation strategies. Reports indicate that thousands of jobs have been affected globally as firms shift more resources towards AI infrastructure, cloud computing and automation tools. More recently, Meta reportedly cut around 8,000 jobs as part of its broader AI-focused restructuring plans.<h2>Cybersecurity hiring rises as AI threats grow</h2>At the same time, demand for cybersecurity professionals is increasing rapidly. According to a report by The New York Times, recruiters are struggling to find enough cybersecurity experts to fill rising numbers of vacancies. Analysts say the surge is directly linked to growing fears around AI-powered cyberattacks and digital vulnerabilities. One of the biggest concerns is that advanced AI models can now identify software vulnerabilities far faster than traditional security systems. AI systems such as Anthropic’s Claude Mythos have reportedly demonstrated the ability to detect thousands of weaknesses in software within a short period of time. While such tools can help companies improve security, experts warn that attackers may also use similar AI systems to identify flaws in critical infrastructure, banking systems and enterprise software at unprecedented speed. Governments, regulators, banks and major corporations are therefore increasing cybersecurity investments to prepare for these emerging risks. Reports suggest that India’s leading banks, government departments and IT firms have already begun stress-testing important systems amid concerns around AI-assisted cyber threats.<h2>AI tools are helping hackers and defenders alike</h2>Despite rapid progress in AI, cybersecurity researchers say human expertise remains essential. AI systems may help detect bugs or automate parts of security analysis, but experienced professionals are still needed to understand how attacks function in real-world environments. One recent example involved a cybersecurity startup using an AI system to help develop an exploit targeting Apple’s new chip protection technology. Researchers said the AI accelerated the process, but human specialists were still required to understand and bypass the security system effectively. Experts say this highlights an important shift in cybersecurity. AI is becoming a tool that can help both defenders and attackers, increasing the need for skilled professionals who can respond to fast-changing threats.<h2>‘Vibe coding’ creating new security concerns</h2>Another major factor driving cybersecurity hiring is the rapid rise of AI-assisted software development, often called “vibe coding”. According to a recent Wired report, nearly 40 per cent of applications developed with AI coding assistance exposed sensitive information, including financial records, medical data, internal company documents and chatbot conversations. Security experts believe many developers are now launching software faster with AI tools but without proper security testing, creating more opportunities for cyberattacks. As more businesses adopt AI coding systems, demand for cybersecurity professionals is rising to identify and fix vulnerabilities before attackers can exploit them.<h2>Some experts question AI-linked layoffs</h2> While AI continues to be cited as a reason for layoffs, some industry leaders believe companies may also be using AI as a convenient explanation for broader cost-cutting measures. Sridhar Vembu has repeatedly questioned the current AI hype cycle, arguing that productivity improvements from AI are still limited in many areas. According to him, some firms may be blaming AI for layoffs that are actually driven by economic pressure and investor expectations rather than direct automation.<h2>What this means for tech jobs</h2>The overall trend highlights how the technology job market is changing. While automation is reducing demand for some traditional roles, cybersecurity jobs are becoming increasingly important as AI expands both opportunities and risks in the digital world.Experts believe demand for:Security analystsEthical hackersCyber defence specialistsInfrastructure protection expertswill continue to rise as organisations increase spending on digital protection.What happens nextAs AI systems become more advanced, companies are expected to invest even more in cybersecurity to protect critical infrastructure and sensitive data. The development highlights a growing reality in the technology sector: while AI may reduce certain jobs, it is also creating urgent demand in areas where human judgement, security expertise and risk management remain essential.

Artificial intelligence is reshaping the global technology industry, with many companies reducing jobs as they invest more heavily in automation and AI systems. However, amid this wave of layoffs, cybersecurity has emerged as one of the fastest-growing hiring sectors.


Artificial intelligence is reshaping the global technology industry, with many companies reducing jobs as they invest more heavily in automation and AI systems. However, amid this wave of layoffs, cybersecurity has emerged as one of the fastest-growing hiring sectors as organisations rush to protect themselves against increasingly advanced cyber threats. Major technology companies including Microsoft, Amazon and Oracle have all linked parts of their recent workforce reductions to AI-driven restructuring and automation strategies. Reports indicate that thousands of jobs have been affected globally as firms shift more resources towards AI infrastructure, cloud computing and automation tools. More recently, Meta reportedly cut around 8,000 jobs as part of its broader AI-focused restructuring plans. Cybersecurity hiring rises as AI threats grow At the same time, demand for cybersecurity professionals is increasing rapidly. According to a report by The New York Times, recruiters are struggling to find enough cybersecurity experts to fill rising numbers of vacancies. Analysts say the surge is directly linked to growing fears around AI-powered cyberattacks and digital vulnerabilities. One of the biggest concerns is that advanced AI models can now identify software vulnerabilities far faster than traditional security systems. AI systems such as Anthropic’s Claude Mythos have reportedly demonstrated the ability to detect thousands of weaknesses in software within a short period of time. While such tools can help companies improve security, experts warn that attackers may also use similar AI systems to identify flaws in critical infrastructure, banking systems and enterprise software at unprecedented speed. Governments, regulators, banks and major corporations are therefore increasing cybersecurity investments to prepare for these emerging risks. Reports suggest that India’s leading banks, government departments and IT firms have already begun stress-testing important systems amid concerns around AI-assisted cyber threats. AI tools are helping hackers and defenders alike Despite rapid progress in AI, cybersecurity researchers say human expertise remains essential. AI systems may help detect bugs or automate parts of security analysis, but experienced professionals are still needed to understand how attacks function in real-world environments. One recent example involved a cybersecurity startup using an AI system to help develop an exploit targeting Apple’s new chip protection technology. Researchers said the AI accelerated the process, but human specialists were still required to understand and bypass the security system effectively. Experts say this highlights an important shift in cybersecurity. AI is becoming a tool that can help both defenders and attackers, increasing the need for skilled professionals who can respond to fast-changing threats. ‘Vibe coding’ creating new security concerns Another major factor driving cybersecurity hiring is the rapid rise of AI-assisted software development, often called “vibe coding”. According to a recent Wired report, nearly 40 per cent of applications developed with AI coding assistance exposed sensitive information, including financial records, medical data, internal company documents and chatbot conversations. Security experts believe many developers are now launching software faster with AI tools but without proper security testing, creating more opportunities for cyberattacks. As more businesses adopt AI coding systems, demand for cybersecurity professionals is rising to identify and fix vulnerabilities before attackers can exploit them. Some experts question AI-linked layoffs While AI continues to be cited as a reason for layoffs, some industry leaders believe companies may also be using AI as a convenient explanation for broader cost-cutting measures. Sridhar Vembu has repeatedly questioned the current AI hype cycle, arguing that productivity improvements from AI are still limited in many areas. According to him, some firms may be blaming AI for layoffs that are actually driven by economic pressure and investor expectations rather than direct automation. What this means for tech jobs The overall trend highlights how the technology job market is changing. While automation is reducing demand for some traditional roles, cybersecurity jobs are becoming increasingly important as AI expands both opportunities and risks in the digital world. Experts believe demand for: Security analysts Ethical hackers Cyber defence specialists Infrastructure protection experts will continue to rise as organisations increase spending on digital protection. What happens next As AI systems become more advanced, companies are expected to invest even more in cybersecurity to protect critical infrastructure and sensitive data. The development highlights a growing reality in the technology sector: while AI may reduce certain jobs, it is also creating urgent demand in areas where human judgement, security expertise and risk management remain essential.

Artificial intelligence is reshaping the global technology industry, with many companies reducing jobs as they invest more heavily in automation and AI systems. However, amid this wave of layoffs, cybersecurity has emerged as one of the fastest-growing hiring sectors.

‘AI and layoffs’: Why cybersecurity experts are now in high demand

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Microsoft says AI companies need tougher safety rules as rogue agent risks grow

AI kill switch: The big red button that may not be enough to stop a rogue AI

Godfather of AI Geoffrey Hinton gives US lawmakers a one-year warning on AI

China used OpenAI and Anthropic outputs to train military AI systems: Report

‘AI and layoffs’: Why cybersecurity experts are now in high demand