It’s probably the number one question people ask me when they hear I cover AI: “Will AI take my job?” That question is often followed by, “How about your job?”
Sigh. Well, so far, I’m still here. And new research from Anthropic suggests the fate of our jobs is more complicated than a simple story of humans being replaced by AI agents and robots.
In the latest installment of its Economic Index, Anthropic rolled out a new way of measuring how people actually use its chatbot Claude—what kinds of tasks they give it, how much autonomy they grant it, and how often it succeeds. The goal is to get a clearer, data-driven picture of whether AI is really making people faster at work, what sorts of tasks AI supports best and how it might actually change the nature of people’s occupations and professions.
I spoke yesterday to Anthropic economist Peter McCrory about the ongoing research, which he said the company kicked off in earnest a year ago in recognition of the fact that AI is a general purpose technology that will affect every job in some way–certainly every sector of the economy.
AI reshapes jobs differently depending on the role
But the results are not always straightforward–at least for now. For example, the research found that AI is reshaping jobs differently depending on the role. A radiologist or therapist may find that AI can elevate their skills by taking on some of the most time-intensive tasks, allowing them to spend more time talking with patients and clients. But people in other jobs may find themselves being deskilled, or that their jobs become simpler without allowing them to devote more time to some obvious higher-level task. This could happen for jobs such as data entry workers, IT specialists and travel agents.
In addition, human collaboration and oversight remain essential, particularly for complex work. So AI appears to increase productivity for highly-skilled professionals, rather than replacing those roles.
McCrory said that he is hopeful that other researchers can take Anthropic’s insights to better understand the uneven implications of AI on the labor market. However, one thing is easily understood: Adoption is happening quickly – in fact, AI is spreading across the US faster than any major technology in the past century, he said.
“In our last report that we put out in September, we documented that disproportionate use is concentrated in a small number of states,” he explained. “In this report, we see evidence that low-usage states are catching up pretty quickly.”
Anthropic’s Claude is growing in the number of tasks it can cover
And there is no doubt that AI is getting more powerful: The research found that Anthropic’s Claude is growing in the number of tasks it can cover, with 44% of jobs now able to use AI in at least a quarter of its tasks, up from 36% in the last report.
I couldn’t help but note that the latest research was completed before Anthropic’s latest model, Opus 4.5, debuted – and also prior to the release of Claude’s Cowork application, a general-purpose AI agent that can manipulate, read, and analyze files on a user’s computer, which just came out this week.
“it just illustrates the broad-based applicability of this technology, and the fact that Claude is increasingly able to not just give you information, but take actions on your behalf, under your discretion and delegation,” McCrory said. “I think you might see a rise in the importance of delegation skills–there’s evidence from the academic literature that suggests that people get more value out of large language models when they have better managerial skills.” That’s also been his own experience, he added: “I find myself delegating increasingly sophisticated tasks to Claude that I might have otherwise given to a research assistant if I had one.”
When I told McCrory that I had written in last week’s Eye on AI about software developers excited about using Claude Code but depressed over reducing their role to that of a manager, he nodded sympathetically and suggested I check out other Anthropic research, developed by its societal impacts team.
“I think the big takeaway here is that we don’t know what’s on the horizon,” he said. When I pointed out how much most of us dislike uncertainty, he emphasized that he hoped the report and the data would help researchers see the future a bit more clearly. “We’re committed to open sourcing this data,” he said, so economists and policymakers can better understand the potential is of what’s coming and how we all prepare for it.
With that, here’s more AI news.
Sharon Goldman
sharon.goldman@fortune.com
@sharongoldman
FORTUNE ON AI
AI ‘godfather’ Yoshua Bengio says he’s found a fix for AI’s biggest risks and become more optimistic by ‘a big margin’ on humanity’s future – by Sharon Goldman
Trump triggers retail investors to dump the Magnificent Seven – by Jim Edwards
Teachers decry AI as brain-rotting junk food for kids: ‘Students can’t reason. They can’t think. They can’t solve problems’ – by Eva Roytburg
What Apple’s AI deal with Google means for the two tech giants, and for $500 billion ‘upstart’ OpenAI – by Jeremy Kahn and Beatrice Nolan
AI IN THE NEWS
Leadership drama at Mira Murati’s Thinking Machines. In a surprising leadership shake-up, two co-founders of Mira Murati’s AI startup Thinking Machines Lab — Barret Zoph and Luke Metz — announced they’re leaving the fledgling company to rejoin OpenAI, just months after departing the organization to help start the venture. According to Wired, another former OpenAI researcher, Sam Schoenholz, is also returning to OpenAI as part of the move. The departures were confirmed in an internal memo from OpenAI’s applications chief, Fidji Simo, who said the return “has been in the works for several weeks.” The turn of events represents a significant blow to Thinking Machines Lab, which had only recently raised a large seed round and recruited top talent, and underscores the intense competition for elite AI researchers in the industry.
Another blockbuster quarter for TSMC. According to CNBC and others, Taiwan Semiconductor Manufacturing Company, the world’s largest semiconductor fabricator, reported a 35% jump in profit and record revenue as demand for AI chips continues to surge. The company beat expectations on both revenue and net income, with its high-performance computing business—driven by AI and data center chips—now accounting for 55% of sales. Advanced chips of 7 nanometers or smaller made up more than three-quarters of wafer revenue, underscoring how central cutting-edge AI processors have become to TSMC’s business.
Google Gemini introduces Personal Intelligence. In a new blog post written by Google VP Josh Woodward, the company announced the US beta launch of “Personal Intelligence” in its Gemini app–which lets users opt in to securely connect their Gmail, Photos, Search, YouTube and other Google apps to Gemini. The idea is to make the assistant more proactive and useful—combining information across emails, photos, and searches to answer questions or offer recommendations specific to your life—while keeping privacy control in the user’s hands (the feature is off by default and users choose what to connect). Personal Intelligence is initially available in the U.S. to paid subscribers, with plans to expand over time, and signals Google’s push to differentiate its consumer AI by leveraging its wider ecosystem to power more personalized AI interactions.
EYE ON AI NUMBERS
48%
That’s how many single adults reported using AI to help draft break-up messages or boundary-setting texts, according to new research from chat assistant use.ai.
As a result, there’s less need to “ghost” dating partners now that users can rely on AI to navigate emotionally charged conversations. Among those who used AI tools to let their dates down gently, 62% described the resulting conversations as more structured, and 39% noted fewer follow-up conflicts.
According to the survey of 4,812 single adults across five English-language markets, the trend extends beyond dating: 27% rehearse sensitive in-person conversations with AI, while 20% use it to manage boundaries in non-romantic relationships.
AI CALENDAR
Jan. 19-23: World Economic Forum, Davos, Switzerland.
Jan. 20-27: AAAI Conference on Artificial Intelligence, Singapore.
Feb. 10-11: AI Action Summit, New Delhi, India.
March 2-5: Mobile World Congress, Barcelona, Spain.
March 16-19: Nvidia GTC, San Jose, Calif.
April 6-9: HumanX, San Francisco.