The UK has become the first country in the world to require Google to let publishers opt out of AI-generated search results without sacrificing their visibility in traditional search rankings.

A New Rule For AI Search

The change follows intervention by the Competition and Markets Authority (CMA), which has imposed a new conduct requirement on Google under the UK’s Digital Markets regime.

The regulator says the move is designed to give publishers greater control over how their content is used within Google’s increasingly AI-driven search experience, while also improving transparency for users.

In practical terms, publishers will be able to prevent their content from appearing in AI-generated search features such as AI Overviews and AI Mode while remaining fully indexed and ranked within conventional Google Search results.

The CMA describes this as a “world-first” requirement and says it will help secure “a fairer deal for publishers and consumers” as AI becomes more deeply embedded within search services.

Why Publishers Have Been Concerned

The dispute centres on a growing tension between AI search systems and the websites that provide much of the information they rely on.

For decades, publishers have accepted that Google could index their content because search results generally sent visitors back to their websites. However, AI-generated summaries increasingly answer users’ questions directly on the search page, reducing the need for people to click through to the original source.

Many publishers argue that this allows AI systems to benefit from their content while reducing the traffic that helps fund journalism, research, reviews, and other forms of online publishing.

Recognising those concerns, the CMA says publishers will now have “effective tools to prevent their content being used to power AI features in search, such as AI Overviews”. The regulator believes this will place publishers “in a stronger position to negotiate content deals with Google”.

The move also extends beyond search summaries. Following consultation feedback, Google will be required to allow publishers to opt out of having their content used for the “fine-tuning” of AI models, giving them greater control over how their material is used across a wider range of AI applications.

How Google’s New Controls Will Work

Google has already begun testing the new controls with a subset of UK website owners and plans to roll them out globally.

According to the Google blog, website owners will gain access to “a new control that lets website owners manage how their links and content appear in generative AI Search features”.

The company says website owners will be able to decide “if they want their site to appear in and help ground responses in our generative AI Search features”.

Importantly, Google has confirmed that publishers who choose to opt out will not be penalised in traditional search rankings. As the company explains, “This control will not be used as a ranking signal for search results outside of these generative AI Search features.”

That distinction is crucial because many publishers have previously argued they faced an impossible choice between allowing AI systems to use their content or disappearing from Google’s search ecosystem altogether.

The controls will also be accompanied by new reporting tools within Google Search Console, giving website owners greater visibility into how their content appears within AI-generated search experiences.

A Bigger Change In Search

The announcement comes at a time when Google is rapidly transforming how search works.

Google says AI Overviews now reaches more than 2.5 billion monthly users, while AI Mode has surpassed one billion monthly users. The company argues that people are increasingly turning to generative AI tools to help them “find, sort through and understand information”.

Google also maintains that AI search creates new opportunities for publishers rather than simply diverting traffic away from them. The company says AI features are designed “to help people find and visit great websites” while helping publishers “strengthen their audiences”.

To support that goal, Google says it has increased the number of links appearing inside AI-generated responses and is continuing to experiment with new ways of encouraging users to visit source websites.

However, the CMA clearly believes safeguards are needed as these systems evolve. For example, CMA Chief Executive Sarah Cardell said: “With features like AI Overviews rapidly reshaping online search, it is crucial that content publishers, including news organisations, have appropriate bargaining power over how their content is used.”

The regulator has also required Google to improve attribution, ensuring publisher content is accompanied by clear links when it appears inside AI-generated search responses.

What Does This Mean For Your Business?

For businesses, the decision highlights how quickly AI is changing the economics of online visibility.

Whether organisations publish news, research, product information, professional advice, or marketing content, the way that material is discovered online is evolving rapidly as AI-generated answers become more common.

The CMA’s intervention suggests regulators are increasingly concerned about ensuring a fair exchange of value between AI platforms and the organisations that create the content those platforms rely upon.

The wider significance extends beyond publishers alone. As AI systems become more deeply integrated into search, businesses will need to think carefully about how their content is being used, where their traffic comes from, and how they maintain visibility in a world where users increasingly receive answers without leaving the search page.

Google’s new controls may not resolve every debate around AI and content ownership, but they do represent one of the first major attempts anywhere in the world to give content creators more control over how their material is used within AI-powered search systems.

Microsoft has unveiled Majorana 2, a next-generation quantum chip that it says is 1,000 times more reliable than its predecessor, helping bring forward its target for a scalable quantum computer from 2033 to 2029.

What Is It?

Majorana 2 is Microsoft’s latest topological quantum chip, a processor designed to overcome one of the biggest obstacles in quantum computing, which is keeping quantum bits, or qubits, stable long enough to perform useful calculations.

According to Microsoft, the new chip is 1,000 times more reliable than its previous generation. The company says its qubits have a mean lifetime of 20 seconds, with some lasting as long as one minute. By comparison, many competing quantum systems measure qubit lifetimes in microseconds.

Microsoft attributes much of the improvement to a new materials design that replaces aluminium with lead in its topological superconductor architecture. The company says this provides greater protection against the environmental disturbances that can cause qubits to lose their quantum state and fail.

As Microsoft Technical Fellow Chetan Nayak explains, “Majorana 2 contains qubits that are 1,000x more reliable than those in our previous quantum processing unit”, and that “The new material stack, which swaps aluminium for lead, creates highly reliable topological qubits with operations on the microsecond scale and lifetimes with a mean of 20 seconds, occasionally exceeding one minute.”

Why This Matters

Reliability is one of the most important challenges facing quantum computing because even extremely powerful quantum systems are of limited value if their qubits cannot remain stable long enough to complete calculations.

Microsoft believes the improvement delivered by Majorana 2 is significant enough to accelerate its roadmap towards a scalable quantum computer. The company has now brought forward its target date from 2033 to 2029.

Microsoft’s announcement about the new quantum chip is also notable because the company says AI played an important role in achieving the breakthrough. For example, using its Microsoft Discovery platform, the company says it deployed AI agents to analyse research data, automate measurements, optimise manufacturing processes, identify hidden problems, and help researchers evaluate new materials more quickly.

Although practical large-scale quantum computing remains a major engineering challenge, Microsoft’s announcement suggests that advances in AI may now be helping accelerate progress towards systems capable of solving problems that remain beyond the reach of today’s conventional computers.

Why AI Is Part Of The Story

Although the quantum hardware itself is attracting most of the attention, Microsoft is also keen to place equal emphasis on the role of its Microsoft Discovery platform.

Microsoft Discovery uses teams of AI agents to help researchers analyse data, generate hypotheses, automate experiments, optimise manufacturing processes, and identify problems that may otherwise be missed.

According to Microsoft, AI agents were used to analyse almost two decades of quantum research data, automate complex measurement processes, optimise fabrication techniques, and even identify an uncalibrated temperature sensor that was introducing unwanted noise into the manufacturing process.

Describing the impact, Nayak said: “Agentic AI has permeated almost everything we do – it’s just become kind of a very natural part of our workflow.”

The company’s quantum team also used AI to help identify promising material combinations before conducting physical experiments, reducing the amount of costly trial-and-error testing required.

Zulfi Alam, Corporate Vice President for Quantum at Microsoft, described this as a move from the “old world order” of repeated experimentation towards simulations that identify “where the highly probable target is.”

A Different Approach To Quantum Computing

Microsoft’s strategy here seems to differ from many of its competitors. For example, companies such as IBM and Google largely focus on superconducting qubits, while Microsoft’s topological approach attempts to create a more stable form of quantum computing by exploiting exotic quantum states known as Majorana Zero Modes.

That said, the approach has not been without controversy. Microsoft’s earlier claims regarding Majorana particles attracted significant scientific scrutiny, and some previous findings were challenged by other researchers.

However, the company believes Majorana 2 demonstrates that the underlying approach is now delivering measurable engineering progress.

Support

It seems Microsoft has also attracted support from DARPA, the US Defence Advanced Research Projects Agency. DARPA has advanced Microsoft into the final phase of its Quantum Benchmarking Initiative, one of only two companies to reach that stage.

According to Microsoft, DARPA concluded that the company could “plausibly build a utility-scale quantum computer in a reasonable timeframe.”

What Could Quantum Computers Actually Do?

If Microsoft can achieve its 2029 target, the implications could be substantial. Quantum computers are not expected to replace conventional computers. Instead, they are designed to tackle highly specialised problems that are currently impractical or impossible for classical systems.

Potential applications include drug discovery, advanced materials research, energy optimisation, logistics, manufacturing, climate modelling, and cryptography.

Microsoft says a scalable quantum computer could help solve problems affecting “global health, food supply, sustainability, energy production and more.”

However, significant technical challenges remain before these systems become commercially useful at scale.

The wider quantum computing industry has a long history of optimistic forecasts, many of which have taken far longer to materialise than originally predicted.

What Does This Mean For Your Business?

For businesses, the announcement is less about purchasing quantum computers any time soon and more about understanding where things seem to be going in the world of advanced computing.

The most significant aspect of Microsoft’s announcement may actually be the growing convergence between AI and scientific research. Rather than simply helping users write documents or answer questions, AI is increasingly being used to accelerate materials science, engineering, pharmaceutical research, manufacturing, and frontier technology development.

Microsoft’s claim that AI helped reduce its quantum computing timeline by four years highlights how AI is becoming a tool for discovery as well as productivity.

Whether Microsoft’s 2029 target ultimately proves achievable remains to be seen. However, the combination of increasingly capable AI systems and advancing quantum hardware suggests that some of the world’s most difficult scientific and engineering challenges may begin moving faster than many experts previously expected.

For organisations watching emerging technologies, the bigger story may not be quantum computing alone, but how AI is increasingly being used to accelerate the creation of the next generation of technology itself.

Poland will introduce a new “sovereignty test” for major government technology purchases as Prime Minister Donald Tusk warns that growing dependence on foreign digital infrastructure and AI providers has become a strategic national concern.

What Has Been Announced?

Speaking at the European Financial Congress in Sopot, Tusk said Poland would begin assessing significant public-sector technology procurements through a sovereignty lens, while also publishing annual reports tracking the country’s progress towards greater IT independence.

Although the full details of the test have not yet been released, the policy is expected to examine issues such as vendor dependence, control over critical systems, access to data, and the strategic risks associated with relying heavily on a small number of technology suppliers.

Explaining the reasoning behind the move, Tusk said: “At this point, the scale of this dependency, and I’m referring here to the relationship between the state and the digital sphere, has reached such proportions that it must prompt serious economic, institutional, and organisational decisions.”

The announcement represents one of the clearest examples yet of a European government moving beyond discussions about digital sovereignty and beginning to embed those concerns directly into procurement policy.

Why Poland Is Concerned

The policy reflects growing concern across Europe that critical public services increasingly depend on technology platforms, cloud infrastructure, AI systems, and digital services controlled by a relatively small number of foreign companies.

Tusk argued that technological sovereignty should become a strategic objective for Poland, not because the country wants to isolate itself from global technology markets, but because governments need meaningful choice rather than dependence.

According to figures cited by the Polish government, the country’s digital trade deficit has grown from approximately PLN 9 billion in 2016 to around PLN 45 billion in 2025, highlighting the increasing flow of technology spending towards foreign providers.

At the same time, artificial intelligence is creating new forms of dependency. Governments increasingly rely on cloud platforms, AI models, cybersecurity tools, data infrastructure, and software ecosystems that are often developed and controlled outside their own borders.

As AI becomes embedded in healthcare, public administration, education, defence, transport, and critical infrastructure, questions about who owns, controls, and maintains those systems are becoming more politically significant.

Part Of A Wider European Debate

Poland’s announcement reflects a wider debate taking place across Europe about digital sovereignty. For example, for several years, European policymakers have expressed concerns about dependence on both American technology giants and Chinese hardware suppliers. However, the rapid emergence of generative AI has added fresh urgency to those discussions.

Many European leaders now worry that regulation alone may not be enough if the most advanced AI systems, cloud platforms, and digital infrastructure remain concentrated in the hands of a small number of overseas providers.

The challenge is particularly evident in AI, where the most advanced models currently come largely from companies based in the United States. European governments and businesses increasingly face difficult decisions about balancing access to the best available technology against concerns around strategic dependence.

Poland has already taken steps in this direction. For example, earlier this year, the government restricted certain Chinese technologies from sensitive military environments and has increased support for domestic AI initiatives, including the development of Polish-language AI models.

What Could The Sovereignty Test Mean In Practice?

Although the final framework remains unclear, the test is unlikely to operate as a simple ban on foreign technology suppliers.

Instead, it appears more likely that government departments will be required to assess whether major procurements create excessive dependence on a single vendor or introduce risks around control, resilience, security, or long-term flexibility.

For example, authorities may need to consider whether critical systems can be migrated elsewhere if required, whether data remains under appropriate control, and whether alternative suppliers exist.

Such considerations are already becoming common in discussions around cloud computing, cybersecurity platforms, AI systems, telecommunications infrastructure, and public-sector software procurement.

The broader objective appears to be ensuring that Poland retains meaningful strategic choice rather than finding itself locked into technologies that become difficult or impossible to replace.

What Does This Mean For Your Business?

For businesses, Poland’s announcement highlights how technology procurement is increasingly becoming a strategic and geopolitical issue rather than simply a commercial one.

Cost, functionality, and performance remain important, but governments and organisations are paying growing attention to questions of control, resilience, supplier concentration, and long-term dependency.

The policy also reflects a wider change in how AI is being viewed. Rather than treating AI purely as a productivity tool, governments are increasingly seeing access to AI infrastructure and capabilities as a matter of economic competitiveness and national security.

Whether other countries follow Poland’s lead remains to be seen. However, the introduction of a sovereignty test suggests that future technology purchasing decisions may increasingly involve questions about who controls the technology, where it is hosted, and how dependent organisations become on the companies that provide it.

Artificial intelligence emerged as a bigger concern than nuclear weapons during a major strategic stability discussion at the Shangri-La Dialogue in Singapore, as senior military leaders warned that AI is accelerating the speed of conflict beyond the pace of human decision-making.

Why AI Dominated The Discussion

The Shangri-La Dialogue is one of the world’s most important defence and security forums, bringing together defence ministers, military commanders, policymakers, and security experts from across the Indo-Pacific and beyond.

Traditionally, discussions about strategic stability have focused heavily on nuclear deterrence, missile defence, arms control, and the balance of power between major states. This year, however, much of the conversation centred on artificial intelligence and the risks it could introduce into military decision-making.

The concern was not that AI is becoming conscious or uncontrollable. Rather, military leaders repeatedly highlighted the possibility that AI-enabled systems could compress decision-making timelines so dramatically that humans struggle to assess situations properly before responding.

Lieutenant General Nauman Zakria, Commander of 1 Corps and the Army Rocket Force Command of the Pakistan Army, explained the problem through the military concept known as the OODA loop, which stands for Observe, Orient, Decide, and Act.

According to Zakria, AI is compressing that cycle to the point where “a human can’t evaluate the situation fast enough.”

He warned that under such conditions, “People will act irrationally, and the actions will be extreme.”

Why Military Leaders Are So Worried

The concern centres on escalation. For example, for decades, strategic stability has relied on the assumption that leaders have sufficient time to evaluate information, consult advisers, communicate with allies, and consider the consequences of military action.

AI-enabled systems have the potential to analyse data, identify threats, recommend responses, and support operational decisions far faster than human decision-makers can process information themselves.

That speed may offer significant military advantages. However, crucially, it also raises the possibility that misunderstandings, false alarms, technical errors, or incorrect threat assessments could trigger responses before humans have time to intervene.

The faster the decision cycle becomes, the less opportunity there is to question assumptions or prevent mistakes.

Already On The Battlefield

Several speakers stressed that these concerns are no longer theoretical. For example, General Onno Eichelsheim, Chief of Defence of the Netherlands, pointed to the growing use of AI in active conflicts, including Ukrainian efforts to anticipate Russian attacks and coordinate drone operations. The United States has also confirmed using AI tools to support military planning and targeting decisions.

As Eichelsheim put it: “AI is a huge risk in escalation. I think that’s clear.”

At the same time, he acknowledged that military adoption is unlikely to slow, adding: “But I’m not naive. It’ll be used in the domain. It is already being used.”

Those comments reflect a growing reality that military organisations increasingly see AI as a capability they cannot afford to ignore, even while recognising the risks associated with it.

The Pace Is Accelerating

What makes these concerns more pressing is the speed at which military AI capabilities are evolving. Increasingly, AI is being integrated with drones, autonomous systems, and robotics rather than operating solely as a decision-support tool.

For example, US startup Foundation Future Industries, which has Eric Trump as an adviser, recently tested humanoid robots in Ukraine with support from Ukrainian authorities. The company says it hopes to deploy more advanced versions with military forces within the next 12 to 18 months. Although the trials focused on logistics rather than combat, they illustrate how AI, robotics, and military operations are becoming increasingly interconnected.

Taken together, these developments suggest that AI is moving beyond the planning room and becoming a more active part of military operations, raising further questions about human oversight, accountability, and control during conflict.

A Humanitarian Concern

The strongest warning came from Mirjana Spoljaric, President of the International Committee of the Red Cross. While military leaders focused largely on strategic and operational risks, Spoljaric highlighted the humanitarian implications of increasingly automated warfare.

She warned that the growing distance between decision-makers and the battlefield creates new challenges for accountability and civilian protection.

“We don’t know where the trigger is pulled,” she said. “It could be thousands of kilometres away.”

Spoljaric also argued that while AI may eventually offer benefits for civilian protection, current deployments are highlighting more of the risks than the advantages.

Her comments reflect wider concerns among humanitarian organisations that meaningful human control over lethal decisions could become increasingly difficult to maintain as AI capabilities advance.

Nuclear Weapons Have Not Gone Away

It should be noted here, however, that nuclear deterrence remained part of the discussion. Major General Meng Xiangqing of China’s People’s Liberation Army reaffirmed China’s long-standing no-first-use nuclear policy and proposed broader commitments among nuclear powers.

“If we can do so, we can reduce the risk and we can further enhance strategic stability,” he said. However, the fact that AI repeatedly returned to the centre of the discussion was itself notable.

A panel that would traditionally be dominated by nuclear strategy spent much of its time examining how artificial intelligence could reshape military escalation, crisis management, and conflict decision-making.

What Does This Mean For Your Business?

For businesses, the discussion highlights how quickly AI is moving from a productivity and automation tool into an issue of national security, geopolitics, and strategic risk.

Many organisations currently view AI primarily through the lens of efficiency, customer service, software development, or data analysis. Governments and defence planners are increasingly focused on a different question, namely what happens when AI systems begin influencing decisions where mistakes carry serious consequences.

The wider significance is that AI’s impact may ultimately extend far beyond individual applications or business processes. The technology is beginning to affect how countries think about defence, deterrence, crisis management, and international stability.

The message emerging from the Shangri-La Dialogue was not that AI should be stopped. Rather, it was that societies may need to think much more carefully about how much decision-making authority is delegated to systems that can operate faster than humans can fully understand the situations they are responding to.

Microsoft has drawn criticism from parts of the cyber security community after publicly condemning a researcher who disclosed several unpatched Windows vulnerabilities and warning that its Digital Crimes Unit would continue pursuing those who enable criminal activity.

What Happened?

The dispute centres on a researcher known online as “Nightmare Eclipse”, who recently published proof-of-concept exploit code for a series of vulnerabilities affecting Microsoft Defender and BitLocker.

The flaws, which became known as BlueHammer, RedSun, UnDefend, YellowKey, GreenPlasma, and MiniPlasma, were disclosed publicly before Microsoft had released patches for all of them. Some have since been assigned CVE identifiers, while Microsoft and the US Cybersecurity and Infrastructure Security Agency (CISA) have confirmed that certain vulnerabilities have been exploited in real-world attacks.

Microsoft argues that the disclosures put customers at unnecessary risk because the company was not given sufficient opportunity to investigate and fix the flaws before exploit code became publicly available.

In a post published by the Microsoft Security Response Center, the company said: “The details of these vulnerabilities were not shared with Microsoft prior to release, and the disclosures put our customers at unnecessary risk.”

The company also stated: “Uncoordinated disclosures that put proof-of-concept code for unpatched vulnerabilities into the hands of bad actors are never justifiable and have real-world consequences.”

Why The Response Has Proved Controversial

The strongest reaction did not come from Microsoft’s criticism of the disclosures themselves, but from language used elsewhere in the company’s statement.

Microsoft wrote that its Digital Crimes Unit “will continue bringing cases against these actors and those that enable their criminal activity – coordinating as needed with law enforcement around the world.”

Many researchers interpreted that wording as a threat directed at vulnerability researchers, particularly given the public nature of the dispute.

The controversy intensified because Nightmare Eclipse claims to have previously attempted to engage with Microsoft through its Microsoft Security Response Center process before later having their account revoked. Microsoft has not publicly addressed those specific claims.

The researcher subsequently published the vulnerabilities through GitHub and GitLab, and their accounts on both platforms have since been removed.

A Debate That Has Been Running For Decades

The dispute touches on one of cyber security’s longest-running arguments about how vulnerabilities should be disclosed.

For example, most of the industry now follows what is known as Coordinated Vulnerability Disclosure, or CVD. Under this model, researchers privately notify software vendors about security flaws, give them time to investigate and develop fixes, and then publish technical details once patches become available.

Microsoft strongly supports that approach. In its statement, the company described CVD as “the industry standard” and said it works with “hundreds of security researchers” each year through the process.

However, critics argue that disclosure relationships only work when vendors respond quickly, communicate effectively, and treat researchers fairly. When researchers believe their concerns are being ignored, disputes can arise over whether public disclosure becomes justified.

The disagreement is significant because independent researchers play a major role in identifying vulnerabilities that software vendors might otherwise miss.

Why This Matters Beyond Microsoft

The row has happened at a time when vulnerability discovery is accelerating across the industry. For example, recent advances in AI-assisted security research are enabling researchers and organisations to identify flaws at unprecedented speed. At the same time, software suppliers are facing growing backlogs of vulnerabilities to investigate, validate, and patch.

That creates tension on both sides. Vendors want time to protect customers before details become public. Researchers want assurance that their findings will be taken seriously and addressed promptly.

The result is growing pressure on disclosure processes that were designed for a slower era of software development and vulnerability discovery.

The wider concern expressed by many researchers is that aggressive responses to disclosure disputes could discourage future reporting.

Microsoft itself acknowledged the importance of the research community, stating: “Our team will continue to support responsible research as we do everything we can to quickly investigate, address, and release updates for vulnerabilities that impact our customers.”

The company also said: “We always have and will continue to welcome vulnerability submissions from anyone through our public researcher portal, regardless of past interactions or reputation.”

What Does This Mean For Your Business?

For businesses, the most important issue here is not really the disagreement itself but the vulnerabilities at the centre of it.

The Defender and BitLocker flaws highlight how even widely trusted security tools can contain weaknesses that attackers may seek to exploit. Organisations should therefore continue prioritising patch management, endpoint monitoring, vulnerability scanning, and defence-in-depth controls rather than assuming any single security product provides complete protection.

The wider lesson is that the relationship between software vendors and independent researchers remains an essential part of cyber security. Vulnerabilities are often discovered by external researchers long before vendors become aware of them, making cooperation between the two groups critical to keeping systems secure.

Whether Microsoft handled this particular dispute correctly will continue to be debated. However, most security professionals would at least agree that a disclosure process that encourages researchers to report vulnerabilities and vendors to fix them quickly remains one of the most important defences the industry has.

Literary agents are increasingly being impersonated by scammers as AI makes it easier to create convincing fake identities, websites, emails, and publishing credentials.

Mark Gottlieb of Trident Media Group says artificial intelligence has not simply accelerated publishing fraud but has “industrialised it”. Scammers can now quickly create realistic agency websites, correspondence, and professional profiles.

The scams exploit the fact that many aspiring authors have limited experience working with literary agents and often communicate remotely. Fraudsters can therefore pose as legitimate agents and offer representation or publishing opportunities.

The threat is also evolving beyond upfront fees. Stolen manuscripts can be turned into counterfeit ebooks, fake audiobooks, unauthorised translations, or AI-generated derivative works.

Businesses and individuals should verify identities through official channels, check websites and email domains carefully, and be cautious of unexpected approaches. As AI makes impersonation more convincing, confirming who you are dealing with is becoming an increasingly important security measure.