The AI revolution at work may not be arriving quite as quickly as the headlines suggest. A new University of Konstanz study finds that just 38% of employees in Germany currently use AI as part of their work, up only slightly from 35% a year earlier. More interestingly, a lot of that adoption isn’t being handed down by the IT department. Employees are increasingly bringing AI into the workplace themselves.
The third wave of the Konstanz AI study surveyed 1,105 employees in May 2026 and found that only 55% of AI users said their employer had officially introduced their most-used AI tool. In other words, almost half are experimenting with tools that their companies haven’t formally rolled out. As study leader Florian Kunze puts it, employees are experimenting while employers are still catching up with policies, training, and secure AI infrastructure.
There is also a surprisingly big divide in who gets to play with the AI toys. 49% of people in office and knowledge-based jobs use AI, compared with 25% in production and manual roles. Education makes an even bigger difference: 56% of employees with higher educational qualifications use AI, compared with just 21% among those with lower qualifications. Smaller organisations are also less likely to provide AI training, formal rules or company-owned tools.
Despite all the AI doomscrolling, workers aren’t necessarily convinced that the robot is coming for their desk tomorrow. 40% of those surveyed expect AI and automation to have a negative impact on the labour market over the next decade, but only 17% are worried about losing their own job. Just 12% believe AI has already reduced entry-level positions, while only 23% say AI is currently making a significant contribution to their organisation’s value creation.
That paints a much messier picture than the usual “AI will change everything overnight” narrative. People are clearly experimenting with AI, but adoption remains uneven and often informal, while company policies and training are struggling to keep pace. For now, the workplace AI revolution looks less like a coordinated corporate takeover and more like employees quietly downloading the future and hoping nobody from IT notices.
AI companies spend enormous amounts of time convincing us their technology is safe and secure. But what happens when those same companies become targets of increasingly sophisticated AI-powered attacks? Anthropic, the company behind Claude, is now facing that question. According to a Washington Post report, cybersecurity startup Cathedral discovered vulnerabilities that let its researchers access sensitive information in Anthropic's internal systems.
The researchers used AI agents to identify potential entry points in less than 12 hours. Interestingly, they didn't need to crack Claude itself. Instead, they exploited weaknesses in third-party business applications that Anthropic uses for everyday operations. Anthropic's security testing program disclosed the findings, which allows outside researchers to identify and report vulnerabilities.
Military working dogs charge into places the rest of us would flee. So, I understand why anyone would want to breed tougher, healthier dogs for the job.
Warhound, a new startup from Colossal Biosciences co-founder Ben Lamm and Anduril co-founder Palmer Luckey, has stepped out of stealth with $200 million to clone and gene-edit working dogs for American troops, police departments, and emergency services (via TechCrunch).
AI can describe a picture, identify objects, and answer questions about what a camera sees. But when a blind user needs a quick answer, getting an entire spoken essay about the scene isn't exactly helpful. Researchers at the University of Maryland (UMD) have found that AI-powered visual assistance can leave blind users doing too much work to get the information they actually need.
The study, titled Say It My Way: Exploring Control in Conversational Visual Question Answering with Blind Users, examined how people interact with Be My AI, an AI-powered feature of the Be My Eyes app. The researchers found that users often received lengthy descriptions that didn't adequately address their immediate goals, forcing them to ask follow-up questions or find ways to steer the AI towards a more useful answer.