These 40 Jobs May Be Replaced by AI. These 40 Probably Won’t

A new study measuring the use of generative artificial intelligence in different professions has just gone public, and its main message to people working in some fields is harsh. It suggests translators, historians, text writers, sales representatives, and customer service agents might want to consider new careers as pile driver or dredge operators, railroad track layers, hardwood floor sanders, or maids — if, that is, they want to lower the threat of AI apps pushing them out of their current jobs. Why should anyone heed yet another of the myriad, sometimes conflicting reports in AI’s potential impacts on jobs? Because the researchers behind the new findings really know what they’re talking about. They all work for tech giant Microsoft, which is developing Copilot and related AI apps examined in the study. And those tools, the authors say, risk putting ticket agents and telemarketers out of work far sooner than orderlies and paving equipment operators. The Microsoft study comes as debate continues about the employment threats AI may pose to millions of people in clerical, administrative, communications, marketing, and other jobs. Executives of several tech companies, including AI developer Anthropic CEO Dario Amodei, have alternatively cheered or warned about bots automating a wide range of work tasks, potentially eliminating up to half of all white-collar and entry-level jobs in the process. Other business leaders, notably serial entrepreneur Mark Cuban, believe the tech will generate even more new positions than it erases by assuming a lot of repetitive drudge work. Microsoft’s new research doesn’t offer an opinion on the quantitative consequences on employment that AI will ultimately have. But it does provide clear indication of which 40 jobs are already using apps most frequently — and the contrasting 40 professions reflecting the tech’s lowest levels of penetration. The full text of their findings and the two rankings are available here. These 40 jobs are most threatened by AI Interpreters and Translators Historians Passenger Attendants Sales Representatives of Services Writers and Authors Customer Service Representatives CNC Tool Programmers Telephone Operators Ticket Agents and Travel Clerks Broadcast Announcers and Radio DJs Brokerage Clerks Farm and Home Management Educators Telemarketers Concierges Political Scientists News Analysts, Reporters, Journalists Mathematicians Technical Writers Proofreaders and Copy Markers Hosts and Hostesses Editors Business Teachers, Postsecondary Public Relations Specialists Demonstrators and Product Promoters Advertising Sales Agents New Accounts Clerks Statistical Assistants Counter and Rental Clerks Data Scientists Personal Financial Advisers Archivists Economics Teachers, Postsecondary Web Developers Management Analysts Geographers Models Market Research Analysts Public Safety Telecommunicators Switchboard Operators Library Science Teachers These 40 jobs are least threatened by AI Phlebotomists Nursing Assistants Hazardous Materials Removal Workers Helpers–Painters, Plasterers Embalmers Plant and System Operators, All Other Oral and Maxillofacial Surgeons Automotive Glass Installers and Repairers Ship Engineers Tire Repairers and Changers Prosthodontists Helpers–Production Workers Highway Maintenance Workers Medical Equipment Preparers Packaging and Filling Machine Operators Machine Feeders and Offbearers Dishwashers Cement Masons and Concrete Finishers Supervisors of Firefighters Industrial Truck and Tractor Operators Ophthalmic Medical Technicians Massage Therapists Surgical Assistants Tire Builders Helpers–Roofers Gas Compressor and Gas Pumping Station Operators Roofers Roustabouts, Oil and Gas Maids and Housekeeping Cleaners Paving, Surfacing, and Tamping Equipment Operators Logging Equipment Operators Motorboat Operators Orderlies Floor Sanders and Finishers Pile Driver Operators Rail-Track Laying and Maintenance Equipment Operators Foundry Mold and Coremakers Water Treatment Plant and System Operators Bridge and Lock Tenders Dredge Operators The results were obtained by analyzing 200,000 “conversations between users and Microsoft Bing Copilot.” Researchers then matched those with “measurements of task success and scope of impact, [to] compute an AI applicability score for each occupation.” The jobs with the highest use rates tended to be office positions or other work communicating data or thoughts for specific business purposes. “We find the highest AI applicability scores for knowledge work occupation groups such as computer and mathematical, and office and administrative support, as well as occupations such as sales whose work activities involve providing and communicating information,” the study says. “Additionally, we characterize the types of work activities performed most successfully, how wage and education correlate with AI applicability, and how real-world usage compares to predictions of occupational AI impact.” The upshot of that is data showing the work of ticketing agents, proofreaders, and PR specialists is already being automated at far higher levels than labor provided by housepainters and plasterers, embalmers, ship engineers, and phlebotomists — the technicians who draw blood for medical tests. But despite the study establishing a de facto ranking of the jobs threatened the most — and least — by AI, its authors ultimately waffle a bit on just how big the tech’s impact on overall employment and workplace stability might be. That’s probably not surprising, given they all work for the same Microsoft employer whose business future will largely depend on successfully developing and selling those work-automating apps to other companies. And some of the study’s disclaimers suggest underlining AI’s potential for possibly eviscerating current employee counts wasn’t considered the best messaging for broadening the appeal of apps to prospective customers. “It is tempting to conclude that occupations with high overlap will experience job loss,” they write in one of those hedges on AI’s likely impact on employment. “This would be a mistake, as our data do not include the downstream business impacts of new technology, which are very hard to predict.” On the one hand, authors do specify that AI tools are being used most often for communications tasks like language interpretation, emailing, and composing marketing materials. But on the other, they hasten to add it isn’t clear apps are also being asked to assume the complete array of tasks those workers perform on the job — or whether they’d even be capable of doing that. The researchers similarly note the different objectives employees studied had in using bots. Some of those workers asked apps to entirely handle and complete certain job tasks. But in many other cases, people queried AI assistants about the most effective ways to fulfill work duties themselves, retaining their own value to employers. Meantime, the study’s authors also seem to balance between the higher productivity objectives — and potentially decreased labor costs — that some employers hope AI will provide and employees’ contrasting fears about their job security. Those diverging focuses, the authors say, won’t generate the zero-sum results many warn of — at least not necessarily. “For example, if AI makes software developers 50 percent more productive, companies could raise their ambitions and hire more developers as they are now getting more output per developer, or hire fewer developers because they can get the same amount done with fewer of them,” they say. “Our data is only about AI usage and we have no data on the downstream impacts of that usage, so we only weigh in on the automation versus augmentation question by separately measuring the tasks that AI performs and assists.” But the study also makes it clear that the jobs least likely to be disrupted initially by increased or dominant use of AI are those involving some mixture of manual activity, use of machines, and interaction with people. That combination leaves nursing assistants, hazardous waste removers, car windshield installers, and medical equipment preparers among the professions with the lowest level of app penetration. But even there, the authors create some wiggle room for eventual employment outcomes. They note their research is based on use of AI that Microsoft developed from large language models (LLMs). More focused apps tailored to individual professions — possibly paired with robotic machines — might still leave many manual jobs vulnerable to the tech’s influence in the future. “Note that our measurement is purely about LLMs,” the authors note. “Other applications of AI could certainly affect occupations involving operating and monitoring machinery, such as truck driving.” Meaning, any historians or brokerage clerks feeling fearful about their work after reading the study might want to rethink any plans about rushing into careers as a roustabout or packaging machine operator. Because those professions, too, may come under the growing influence of specialized AI apps in the not too distant future. BY BRUCE CRUMLEY @BRUCEC_INC

Only 14 Percent of Small Businesses Have Successfully Integrated AI. Anthropic Says This Is the Missing Link

Small businesses want to use AI. The problem, Anthropic says, is that many don’t know how. On Thursday, Anthropic published findings from its Claude SMB Tour, a series of free workshops it held for six weeks with more than 1,000 small business owners across 10 U.S. cities. The majority of attendees came from industries like construction, manufacturing, and logistics. Before launching the tour, Anthropic surveyed 503 small-business decision-makers. It found that 81 percent were open to trying new AI tools. Their top pain point, however, was that employees didn’t know how or when to use them. That uncertainty showed up during the workshops. Anthropic says many attendees had already used its Claude chatbot daily, but hadn’t tried more advanced features like Cowork, skills, or connectors, which use agents, instructions, and integrations to automate multi-step workflows. Others told Anthropic that AI was changing so quickly that training programs struggled to keep up. Anthropic says hands-on training helped. During the workshops, business owners learned how to set up Claude Cowork and build workflows for tasks like automating payroll or creating a “virtual chief-of-staff.” Across 635 exit surveys, the guided build session was the most-cited highlight, and nearly two-thirds of attendees asked for more hands-on help implementing AI afterward. Owners also wanted to learn from other small businesses. Hearing how their peers used AI was the second-most-cited highlight of the workshops, and attendees requested a shared collection of real-world use cases more often than any new product feature, according to Anthropic. The findings come as small businesses race to figure out where AI fits into their operations. A Goldman Sachs survey of 1,256 small business owners published in March found that 76 percent of them were using AI, but just 14 percent had fully integrated it into their core operations. Nearly half cited a lack of technical expertise as a barrier, while 73 percent said more training and resources would help them implement AI. For small businesses with limited staff and resources, that training can help owners move beyond playing around with chatbots and identify tasks they can actually hand off to AI, potentially freeing up time for work. Anthropic is betting that more training can close that gap. The company is launching a Claude SMB Trainer Program to teach community organizations and AI partners how to bring AI workshops to small businesses themselves. The first two training sessions will take place in San Francisco and New York City, with the dates still to be announced. Its Claude SMB Tour is also expanding to more cities this fall, starting with Boston on September 16. BY AARON MOK

It’s getting harder to tell whether we should be worried about AI, or just exhausted by the marketing hype disguised as warnings

For most of the past year, AI companies have told us that their models are getting increasingly dangerous. It seems as though this trend started when Anthropic made a model called Mythos. The company claimed the model is better than any before at identifying bugs and vulnerabilities in software, making it extremely useful, but potentially catastrophic if it were in the hands of bad actors who could use it to basically hack all software everywhere. At the time, the U.S. government imposed a restriction forbidding the company from releasing the model to the public. Only later did the company release a version of Mythos with safety guardrails called Fable. Obviously, everyone wanted to use Fable. After all, if the government said Mythos is too dangerous for anyone to use, of course we’d want to use whatever version of it Anthropic will give us. It’s a strange marketing strategy when you think about it, but it’s also remarkably effective. OpenAI, Anthropic, and others have warned us that AI models would, or at least could, eventually become smarter than humans. When that happens, the story goes, they’ll take our jobs, be capable of launching cyberattacks, create biological weapons, or—in the most extreme scenario—wipe out humanity altogether. That’s not exactly the kind of thing most companies brag about, but there’s an obvious benefit. Nothing makes your product sound impressive quite like suggesting it might be too powerful for humanity to control. Of course, if you tell people your product is super dangerous but then you ship it anyway, it’s hard to know whether you’re serious. At some point it just seems like a marketing tactic to make more people want to use what you’re selling. That’s created a real problem, because now some of the people building the most powerful AI models are saying that we should slow down. And this time, it seems like they actually mean it. On Saturday, Anthropic CEO Dario Amodei published a blog post titled “We Must Pace the Frontier,” arguing that AI companies should deliberately slow the rate at which they develop more capable frontier models. Amodei isn’t calling for AI development to stop. On the contrary, he says that advancement is crucial since if they don’t do it, someone else will. And if that someone else is China, that would be a national security risk. Instead, he says companies should give safety research enough time to keep up with rapidly advancing capabilities. It does invite the question of “why now?” The answer is either terrifying or another scare-marketing tactic. It’s hard to know which because we’ve basically heard this before. But maybe this time he really means it. “My first concern is that, since roughly this summer, AI has been advancing drastically faster, driven primarily by AI’s growing ability to build the next generation of AI,” Amodei writes. That’s what researchers call recursive self-improvement, and it’s one of the most significant tipping points with artificial intelligence. Until now, it’s mostly been theoretical, but apparently the big AI companies are starting to see evidence that it’s becoming more than just theory. The idea is pretty simple: Humans build an AI system. That AI system is able to help humans build a better AI system. That better system is capable of building an even better one than before, and—eventually—it’s able to build models without the help of humans. At some point, humans aren’t making a better AI model; the AI is making AI. That accelerates the process and also makes it much harder for humans to understand what the models are truly capable of. That, for obvious reasons, would be very bad. According to Amodei, that’s no longer theoretical. “It is starting to happen across the industry, including at Anthropic,” he writes. His second concern is considerably weirder. The OpenAI hack of Hugging Face seems to have been a wake-up call. In that case, the model created thousands of agents that exploited vulnerabilities in their testing environment, communicated and coordinated with other agents, gained unauthorized access to outside systems, and collaborated to interfere with the testers evaluating their performance. Amodei said they behaved like a “fanatically devoted collective,” willing to sacrifice individual agents to accomplish the group’s objective. “It’s my worry that in 6–12 months such a swarm could be capable of taking over the entire internet,” he wrote. That is an extraordinary prediction. On the other hand, it’s just a prediction. Yes, Amodei has access to far more information about frontier AI models than pretty much anyone else in the world, but it’s also hard to simply take his word for it. That is, after all, part of the problem. When AI companies are raising money, they talk about their models as the technology that will transform the global economy. When they’re selling those models as products, they talk about how companies that don’t adopt AI are going to be left behind. And then there’s artificial general intelligence, which is either right around the corner or just up the foothills. When they talk about safety, on the other hand, the technology is so powerful it might destroy us all. It’s entirely possible that all of those things are true. But it’s not hard to understand how it becomes difficult to separate out what’s a warning and what’s a sales pitch when they’re using the same words. It’s worth mentioning that there’s another problem with Amodei’s proposal. Most of what he suggested would both make AI safer and also be very good for Anthropic. For example, Amodei is calling for frontier AI companies to coordinate their pace of development. You can make a real safety argument, but there’s also an obvious competitive benefit. If Anthropic decides to slow down the pace of development to ensure alignment, it risks being left behind if OpenAI and Google charge ahead. On the other hand, if everyone agrees to slow down together, Anthropic gets the extra time without giving up its competitive ground. None of that means Amodei is being insincere. It just makes it harder to know his real motivation. It’s like the AI boy cried wolf, but also the wolf is real, and you should buy one, but maybe it will eventually try to eat you. It’s complicated. There’s a lesson here for every leader, which is that trust is your most valuable asset. I’ve written about that very thing so many times before, but it bears repeating because it really is the single most important part of this story. If we thought they really had our best interests in mind, it’d be so much easier to believe what they have to say and not just assume it’s a weird form of hype marketing. Maybe this time the AI companies really mean it when they say we should be worried about what they’ve built. It turns out that a little trust and credibility go a long way when your message comes down to “this time we really mean it.” EXPERT OPINION BY JASON ATEN, TECH COLUMNIST @JASONATEN

Call for global AI rules after Claude bioweapon research

The European Commissioner with responsibility for tech regulation has said that global rules on artificial intelligence (AI) are "really needed". Commission Executive Vice-President for Tech Sovereignty, Security and Democracy Henna Virkkunen was responding to questions about AI company Anthropic which said it has disrupted attempts to use its models to develop biological weapons. Anthropic also said it has shut down multiple cases of state-sponsored surveillance operations using its technology in China, Iran and west Africa. Speaking to reporters in Dublin, Ms Virkkunen said in Europe there is the AI Act. "According to our AI Act, if those kinds of very capable models are coming to the market the service provider has to, all the time, assess and mitigate the risks and also, when the models are on the market they have to monitor the situation all the time," Ms Virkkunen said. She said we know that this is not the case globally. "It's very important that we continue international co-operation because I see that global rules are really needed here. "With AI there is, of course, huge potential and so many positive things, but there is also risk, and we have to be aware of that, cyber risks and bio risks, we are aware that these are very serious topics " she added. In a report titled 'Detecting and countering misuse of AI', the San Francisco-based AI company Anthropic listed five case studies of potential biological misuse of its models which it says "is one of the most serious risks of frontier AI models". The scientific research in those case studies involved work around the mosquito-born chikungunya virus, a "highly-pathogenic" strain of the bird flu, a family of viruses that include smallpox and mpox, venoms and other toxins. In the examples identified, Anthropic said the actors circumvented controls imposed to prevent users from unsupported regions accessing their models, while the actors also "engaged in other efforts to obfuscate the purpose of their research to evade our safeguards". "When we detected and investigated these cases, we banned the users' accounts and incorporated our investigative findings into our frontier model safeguards, enforcement, and threat intelligence processes to better prevent, detect, and disrupt these activities in the future," the report said. Anthropic said the intent of the actors was not clear-cut and the AI lab did not identify them. "The individuals implicated in these case studies are working scientists. We do not assert that they intended harm, and identifying them or their labs could expose them to harm," the report said. Anthropic said its aim in sharing the examples is to "spark conversation within the AI industry, and with governments, about emerging biological risks and how best to counter them". Anthropic says China, Iran used its AI to aid spying Also in the report, Anthropic said it shut down multiple cases of state-sponsored surveillance operations that used its AI models, and warned that governments and state-aligned actors are increasingly using AI to spy on ethnic minorities and dissidents. The incidents were found and disrupted between January and July, and they originated in China, Iran and west Africa, Anthropic said in a report about misuse of its models. These surveillance campaigns "targeted the same diaspora and dissident communities these regimes have historically targeted". "These include pro-democracy figures in Hong Kong, Tibetan and Falun Gong communities across Asia, and Iranian minority communities and opponents of the Iranian regime abroad," the report said. In one case, Iranian actors developed a way to identify people through their social media accounts; in another, a contractor working for Malian national security authorities used Claude "to design the underlying software that enabled the intelligence gathering". "AI is now being used in place of an engineering workforce," the report said. Anthropic also disrupted efforts by users to design weapons and create dating scams. The San Francisco-based AI lab also accused Chinese developers of deceptively using Claude to produce responses to user queries while simultaneously "distilling" that data to improve their own models. Distilling is an industry term that refers to a process where one AI model is used to train another one. Chinese developers have previously been accused of using that technique without permission, essentially stealing resources from American labs such as Anthropic and OpenAI. Now Anthropic alleges that China's Moonshot and Deepseek have also secretly used Claude to generate answers given to its users. "In one instance, over a 10-day period, Moonshot relayed almost 300,000 customer requests to Anthropic" through a "network of 5,380 fraudulent accounts, most of which appeared to be located in Singapore and Japan," the report said. Some of that data contained sensitive user information, potentially in violation of privacy agreements. "We do not know if Moonshot notified their customers that their requests were being rerouted to Anthropic and exposed to a third party," the report said. Deepseek used similar techniques. Earlier this week, an artificial intelligence researcher who left OpenAI to join Anthropic has decided to leave the industry, accusing both US companies of "gambling with our lives" in the race to develop AI models capable of self-improvement. By Brian O'Donovan Additional reporting AFP