Most large European enterprises have no shortage of AI ambition, but they lack the data foundation to support it. Fragmented legacy systems, strict GDPR obligations, and anxiety about handing sensitive data to foreign cloud infrastructure have left many IT leaders running the same modernization projects on a loop, stuck in AI pilot purgatory before they reach production. Onix, a leading services-as-software data and AI specialist, thinks it has the answer. The outfit is rolling out Wingspan across the UK and Europe this summer, built around a proprietary technology it calls the Semantic Twin: a continuously updated intelligence layer that maps an organization's entire data landscape, system relationships, and business context, then uses that foundation to give AI agents the grounding they need to work. To find out what that means in practice, Onix's EMEA managing director, Vittorio Sanvito, answers IT and compliance leaders' most pressing questions. Q: With Google Cloud seeing significant, high-growth demand, why is now the critical moment for Onix to make this unified push across the continent? A: The European tech sector is at a pivotal moment. Market demand is undeniable: Google Cloud has a substantial backlog going into the coming year and continues to grow at pace, which reflects strong AI demand across every industry. Yet large enterprises in Europe are struggling to execute because they lack the proper data foundation, stuck in perpetual data modernization cycles that prevent them from scaling. We're at the major Google Cloud Summits across Europe this summer with a single message: you don't have to stay trapped in pilot purgatory. The Wingspan rollout across Europe and our expanded strategic collaboration with Google Cloud, which is expected to drive over $500 million in cloud consumption, together reflect the scale of what we're trying to do here. We want to make clear that Onix is the execution engine for enterprises that want to turn their AI ambitions into measurable impact. Q: When enterprise leaders speak about what keeps them up at night, data privacy and security are almost always at the top of the list. There are concerns that using advanced AI means sacrificing control over localized, sensitive data. How are Onix and Wingspan directly addressing this while keeping organizations compliant? A: It's a valid concern, and the exact reason we built a localized, customer-first approach into the core of Wingspan. European businesses shouldn't be forced to choose between maintaining their digital sovereignty and remaining economically competitive on a global scale. Wingspan is designed as what we call an Enterprise Intelligence Fabric. It activates data locally and securely, supports complex multi-country deployments, and complies with GDPR and regional data residency requirements by design rather than bolted on afterward. It operates across hybrid and multi-cloud environments without creating vendor lock-in. The Semantic Twin is central to all of this: because it maps your data landscape internally and continuously, you never push unverified or unstructured data outside your governance boundary to make AI work. Q: How does Semantic Twin technology work under the hood to alleviate fears about the AI "black-box"? A: A modern AI agent might be born today and put to work tomorrow, but it doesn't know how to execute tasks because it lacks instruction on standard operational steps. Traditional AI initiatives usually fail because they lack this deep business context. The Semantic Twin solves this by acting as a living intelligence layer that continuously maps an organization's entire data landscape, system relationships, and operational dependencies directly to KPI levels. By providing this connective tissue up front, the Semantic Twin grounds AI agents in real enterprise data with built-in guardrails, so they operate with 99.9 percent data validation accuracy. From a compliance perspective, this eliminates the AI black-box. The Semantic Twin enables full lineage tracking and governance-aware orchestration, so AI outcomes are grounded in corporate data, fully auditable, and explainable. This strict data grounding minimizes the hallucination risks that keep compliance teams awake at night. Q: That level of governance-aware orchestration is mission-critical for highly regulated and data-intensive industries like financial services, healthcare, and the public sector. But beyond compliance, what does the operational impact look like for a customer who's deployed this? A: Because the Semantic Twin provides the true enterprise context and meaning behind the data, our AI agents can move beyond simple, static automation and advance toward autonomous, high-accuracy decision-making. We're helping customers create a new AI operating model that will replace standard SDLC models. This translates to faster time-to-value. By combining agentic AI with this enterprise context, we help organizations orchestrate data modernization and AI operations within a single framework. This accelerates modernization by 3x, moves data into an "AI-ready" state in a matter of weeks rather than years, and delivers a 50 percent to 80 percent reduction in manual effort. Beyond the platform itself, we've also changed how we structure engagements. We're shifting away from traditional, bloated consulting models that rely on endless time-and-materials billing. About 75 percent of our engagements are now set up as outcome-based, with fixed-milestone projects. We guarantee exponential ROI by using AI-assisted delivery pods to execute these transformations rapidly. Q: What does success look like for Onix in Europe over the next 12 months? A: Success looks like the enterprises that came to us running consecutive AI pilots finally having something in production: governed, measurable, and connected to business outcomes rather than sitting in a sandbox. Europe has been cautious about AI for good reasons, and GDPR exists for good reasons. What we want to prove is that caution and ambition aren't mutually exclusive. The Semantic Twin is how we make that case technically; the rest is execution. Contributed by Onix.

Salesforce has agreed to buy AI customer support outfit Fin for $3.6 billion, bolstering its Agentforce business as software vendors race to convince customers that bots really can handle customer service. The CRM giant announced on Monday that it had signed a definitive agreement to acquire Fin, formerly known as Intercom, in a deal expected to close during the fourth quarter of Salesforce's fiscal 2027. Fin's flagship product is an AI customer service agent designed to handle support requests across platforms including live chat, email, WhatsApp, SMS, Slack, and phone. Fin says that the system is powered by its proprietary Apex model, built specifically for customer support workloads. "We're thrilled to welcome Fin to Salesforce as we enable every company to become an agentic enterprise," Salesforce CEO Marc Benioff said in a statement. "Fin brings proven agent technology, a deep commitment to customer success, and an incredible AI team that will complement Agentforce with powerful service agent capabilities." The acquisition adds both technology and customers. Salesforce said Fin serves more than 30,000 companies worldwide and cited examples of customers using its AI agents to resolve an average of 76 percent of support requests end-to-end without human intervention. Fin chief exec and co-founder Eoghan McCabe said joining Salesforce would allow the company to deploy its technology at a much larger scale than it could independently. The deal also strengthens Salesforce's Agentforce business, the company's flagship push into AI agents. Salesforce said Agentforce reached $1.2 billion in annual recurring revenue during the first quarter of fiscal 2027, up 205 percent year over year. It also arrives during a busy period for the company. Last week Salesforce confirmed another round of layoffs affecting teams including Agentforce, MuleSoft, and Marketing Cloud, while also pressing ahead with the acquisition of usage-based billing specialist m3ter and expanding its stock buyback program. Salesforce has spent the past two years positioning AI agents as the next major battleground for enterprise software vendors, alongside rivals including Microsoft, Oracle, and SAP. While much of that competition has focused on building increasingly-capable AI systems, the acquisition suggests Salesforce is also willing to write sizeable checks for companies that have already persuaded customers to put those systems into production. ®

As Anthropic execs prepare to visit the White House after effectively being ordered to cease offering the company's Mythos 5 and Fable 5 models, the European Commission says the incident is another example of why the EU must achieve technological autonomy. Anthropic announced on Friday that the US government issued an export control directive that required the AI upstart to prevent any non-US citizens from accessing its cybersecurity models Mythos 5 and Fable 5. The order meant even some Anthropic staff could not use its models. And as there’s no way to tell if someone on the internet is a US citizen, the order effectively meant that the AI company had to stop making the models available to everyone to ensure compliance. Anthropic isn't sure why the White House issued the order. "Our understanding is that the government believes it has become aware of a method of bypassing, or 'jailbreaking,' Fable 5," the company said. "To date, the government has only given us verbal evidence of a potential narrow, non-universal jailbreak, which essentially consists of asking the model to read a specific codebase and fix any software flaws. "Our understanding is that one potential jailbreak was shared with the government." The Wall Street Journal reports that the directive was the result of conversations held between Amazon CEO Andy Jassy and US officials, including Treasury secretary Scott Bessent, and Jassy's report of a possible jailbreak. Anthropic executives are set to meet with US officials at the White House this week to gain a fuller understanding of the developments that informed the directive, according to Axios. Whatever the Trump administration's reason for the order, Mythos and Fable remain unavailable at the time of writing. A case study for sovereignty The incident has not gone unnoticed. Thomas Regnier, spokesperson for the European Commission, said the body is still examining the directive's implications for the EU amid concerns that the US can switch off access to technology that allied partners could soon come to rely on heavily. "The Commission has taken note of Anthropic's statement regarding the US export control directive on its most advanced models and is assessing its implications, including for users in the European Union," he said. "We are seeing a new generation of highly capable AI models reach the market. These models offer significant benefits, including for cyber-defence, but they also raise serious cybersecurity concerns that need to be addressed. "This is a shared challenge, not one confined to a single jurisdiction or company. We believe that contingency measures taken in this light should not be discriminatory against partners. "This development is a further illustration of why Europe needs to strengthen its technological sovereignty, and it underlines the relevance of the cybersecurity and AI legislation already in place at EU level, including the AI Act, the Cyber Resilience Act, and the NIS2 Directive – as tools to manage exactly this kind of risk on our own terms. "We are looking closely at the practical consequences of this for European users of these services." The comments come days after the EU launched its European Technological Sovereignty Package, a slew of measures aimed at sharply reducing its reliance on technology developed by the US and China. Cybersecurity-specific AI models such as Mythos 5, Fable 5, and OpenAI's GPT-5.5 are still very early in their development, and are not yet available to many organizations, let alone casual users. The cost of dependency stays invisible until it's too late The US directive to prevent foreign nationals from accessing Anthropic's models will nevertheless prompt concerns among global partners and organizations about how a foreign government can simply revoke access to technology on which they may become highly reliant in the future. For Aled Lloyd Owen, chief of staff at Responsible AI UK, the news of Anthropic restricting access to its models only strengthens the case for the EU's plans to loosen its ties to US tech. "This is another incident that just proves the rule and proves that [the EU] must move faster and deeper, and really establish that independence as soon as possible," he told The Register. As for alternatives, Mistral AI is one of the EU's flagship AI development projects. It is widely regarded as a fast, capable, open-source model, but one that lacks the performance of "frontier" models such as those made by Anthropic and OpenAI. Owen said there is a limit to how quickly the EU can achieve autonomy, but the latest Anthropic story is "quite helpful in a lot of ways." "It's saying: 'You can't, from a commercial point of view, trust these bodies,' so to some extent, are you willing to sacrifice performance, both perceived and real, for European homegrown models that are not quite there but are certainly driving in that direction, in order to have a more reliable sovereign service? "So, the ability to shift is both technological, in terms of building effective models and building effective infrastructure, but will also involve weaning European companies from the high-capability overseas models that they're already using." Kate Hanaghan, chief research officer at TechMarketView, said: "Last week, I was talking to a couple of European integrators about exactly this issue. One framed it as 'The cost of dependency stays invisible until it's too late.' "For UK enterprises, the risk is now very clear. Depending on a single US frontier provider leaves operations exposed if that access is withdrawn. And this weekend showed it can happen without warning. Ultimately, that leaves Europe to work out what it should, and realistically can, develop for itself." Voices in the UK echo those in the EU. Kanishka Narayan, minister for AI and online safety, posted on X: "The main lesson: as we debate the future of national security and technological sovereignty, access to AI capabilities is crucial." I care about sovereign AI because it now decides our security Separately, he said: "We treat every other threat to our sovereignty with deadly seriousness, but we haven't learned to treat this one in the same way." "I care about sovereign AI because it now decides our security… it will reshape our economy faster than anything else we've seen in our lifetimes," he added. The MP went on to say: "I'm not going to pretend there's a simple switch that we can pull. There isn't. Britain needs more AI capability. This is the central political question of our time, and our first duty is to see it clearly before someone else decides the answer for us." Policy on the run The order has also angered others, for different reasons. A group of 54 security and AI experts co-signed an open letter to the US government after the directive was issued, calling on the government to lift the restrictions. They also asked the government to commit to a more transparent approach to handling AI risk assessments in the future, saying that it should be a more democratic process. Not all the signatories believe the US should have regulatory control over AI models (Anthropic believes the US rightfully holds the authority to block releases), but they said that materially impactful decisions should be grounded in science and security teams should be given time to prepare. The letter pointed out that vulnerability researchers and red teams are already relying on these models every day, and decisions to revoke access to them should be made through a democratic process, and should restrict capabilities only to the minimal extent necessary. "As a result, this action has taken the best models away from defenders, created market uncertainty, and risked America's AI leadership without any real risk to justify it," the signatories wrote. Who's next? In its response to the White House order, Anthropic asserted the allegedly problematic features of Fable and Mythos are also present in other models, including GPT-5.5. Anthropic has stated from the launch of Fable 5 that it believes developing AI models with perfect jailbreak resistance "does not appear to be possible today," and that no one has developed a universal jailbreak for its models to the best of its knowledge. It has long advocated for and continues to stand by its defense-in-depth approach to managing risks. ®

Britain's AI jobs boom is creating a two-track labor market, according to PwC, which just so happens to make a healthy living helping companies navigate AI-driven transformation. The consulting giant's latest AI Jobs Barometer found hiring for AI specialists in the UK jumped 61 percent over the past year, rising from 112,000 roles in 2024 to 180,000 in 2025, even as overall job vacancies across the economy fell by 6.6 percent. That headline figure is the sort of thing consultancies put in press releases, but the more interesting bit comes later. PwC's analysis suggests employers aren't rushing to hire hordes of machine learning engineers and model builders. Instead, they're increasingly looking for people who can use AI inside existing professions and business functions. The firm found that so-called AI user roles grew by almost 66,000 positions during the year, while AI developer roles increased by just 2,600. After years of declaring that AI will revolutionize everything from accounting to sandwich-making, companies appear to have reached the awkward stage where somebody actually must make the technology useful. PwC argues the result is a "two-track" labor market. Jobs where AI helps skilled workers automate repetitive tasks and focus on higher-value work are growing faster than roles where the technology mainly makes tasks easier and lowers barriers to entry. According to the report, roles most enhanced by AI have grown by 39 percent since 2018, compared with 17 percent growth in jobs where AI is primarily simplifying work. The firm’s wage data tells a similar story. Jobs requiring AI skills now command an average wage premium of 34.2 percent, up from 11 percent a year ago. Consumer market companies are offering premiums as high as 64 percent, while government and public sector employers top out at 12 percent. That's certainly good news for workers with AI skills. It's also not the sort of conclusion likely to upset a firm that advises clients on AI strategy for a living. The findings land against a backdrop of growing anxiety about AI's impact on employment. Recent polling found one in five Britons believes AI-driven layoffs could eventually trigger civil unrest, while another survey found that office workers are already spending nearly six hours every week checking, correcting, or redoing work generated by AI tools. For all the excitement around AI, the hiring surge appears to be concentrated in a surprisingly old-fashioned category: people who know what they're doing. ®

OPINION Tech companies hate liability, or at least the sort that makes them liable if something goes wrong. It doesn’t much matter if what they ship is buggy, shabby or simply blows chunks, it’s on you for using it. You fool. Corporates can get service level agreements to focus their suppliers’ minds, and life-critical applications such as health or transport wire in liability through regulation, but shlubs like us get nothing. This goes double for LLMs, which lie to our face all day every day and twice on Sundays. It’s on you to check. If you file a court brief with an hallucinated cite, or lose your production database to an insane agent, it’s on, yes, you. Again. Terms and conditions. If the AI companies were liable for the things they ship they know are faulty, the industry would look very different. Thus it is very interesting indeed that a Munich court has just found Google strictly liable for bad things that its own AI is doing — in this case, making false and potentially very damaging statements about a couple of publishers. The AI Overview linked the publishers to various scams, in prime position at the top of the search results. Normally, search results don’t make the search engine liable for what it digs up. These results weren’t dug up, they were made up. Normally, if a page returned by a search engine contains legally actionable material, you can go after the page's author. Here, there were no such pages. The author was Google’s own AI. No escaping it, the court decided, someone had to be liable and that someone was Google. The company argued in its defense that because everyone knew you can’t trust AI results, everyone knew to check what AI Overview told them. This worked as well as Alex Jones arguing that as he was a performance artist rather than a journalist, the massive damage caused by his Infowars platform wasn’t his responsibility. Don’t blame me Pompei, said Vesuvius, I was just putting on a fireworks show. No sale. Google, you are guilty. Stop doing it. This may seem on its face to be nothing new, not different in principle to a lawyer abusing AI and eating judge boot. The difference is that the lawyer can either stop abusing AI or stop using it altogether. Google can do neither. It has bet the shop on an AI it can’t control, one with a court-tested liability that can’t be fixed until hallucinations and false equivalencies are fixed. Businesses that use AI have indeed learned what Google said in court and have evolved their own processes to detoxify AI internally. It means using skilled humans to check and verify. It means that productivity benefits are as hard to find as Alex Jones’ donations to the Southern Poverty Law Center. As any sensible human knows, productivity isn’t the one metric to bind them all. Quality, value and integrity are part of the equation, and the skill is balancing the incalculable against the countable. Google can’t do that. It has mustered under the ‘AI All The Things’ banner, but unlike its fellow LLMinati, Google’s primary product is serving facts to billions of people. There can be no mitigating human filter, no legal prophylactic of ‘we made it up, but you know what we’re like’. Google multiplied is liability the day it made AI Overview not an option, but unavoidable and the first thing you see. It’s rolling out more and more layers of AI-mediated content in lieu of actual search results, despite nobody wanting that, under the corporate hallucination that lie ability trumps liability. Which has been true for most tech companies most of the time, but no longer. It’s improbable that Google can change course and do the obvious thing, incorporate an AI kill switch in its search product. It can no more compete on quality of results than a dodo can enter the All Mauritius Aviad Aerobatics championship. Which is a shame, because the first rats of legal liability have scuttled ashore. Expect this process to continue. Proponents of AGI are adept at minimizing the implicit — and in this court case, explicit — unreliability of LLMs as an unsolved problem. Humans are unreliable too, after all. We have evolved our own error detection and correction protocols, be they the scientific method or the police and legal systems in general, or internal reviews and test cycles in corporate. There is no way that AI’s insinuation into process can or should be exempt from these systems, at least while it mucks things up like a stoned teenager in a muscle car. The tech industry has avoided liability on the grounds of immaturity, that what it does is so wonderful that it shouldn’t be held back because of flaws that will take too long to fix. Immaturity only lasts so long, then you have to take the consequences not only of your actions, but of refusing to change your behavior. The Munich court has fired the warning shot of those consequences, and Google must search its soul and find the truth. If, that is, its AI will let it. ®