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New MIT jobs report: Why AI's work impact will roll in like a rising tide, not a crashing wave
Worried AI is coming for your job? New MIT research suggests a slower shift. AI is improving at work tasks, but its impact may take longer to fully reach the workforce. Rather than "crashing waves" that will shock workers, researchers describe a "rising tide" that gives them more time to adapt. Also: How AI has suddenly become much more useful to open-source developers "AI capabilities are already substantial and poised to expand broadly," the study said. "Most of the tasks that we study could reach AI success rates of 80%-95% by 2029 (at a minimally sufficient quality level), suggesting potentially substantial labor-market impacts as this tide continues to rise." AI-induced job anxiety has become an ever-present reality over the last year as AI agents have gotten more capable (though they come with just as many risks as they do benefits). Even a slightly longer horizon for lasting change could make a huge difference in whether -- and how many -- workers get the chance to upskill for a very different labor market of the future. For the study, MIT referred to 3,000 text-based work tasks from the US Department of Labor's Occupational Information Network (O*NET) database, which is used by many companies, including Anthropic, to map AI's impact on labor. To ensure real-world relevance, researchers focused on tasks where AI could help humans save at least 10% of their time. The study found that LLMs completed 60% of tasks without humans at a "minimally sufficient" level, as determined by a human manager, and only 26% at "superior quality." Still, researchers were impressed by what AI could take on. It's not that AI progress will be slower than anticipated, but that progress will manifest over a longer period of time, "such that individual workers are less likely to be blindsided by AI," they noted. "A rising tide could, however, still be quite disruptive if it happens quickly." Also: I used Gmail's AI tool to do hours of work for me in 10 minutes - with 3 prompts The paper noted that text-based work is especially vulnerable to rapidly evolving AI capabilities and could be automated by LLMs at that "minimally sufficient" level by 2029. But the researchers added that consistent, "near-perfect" performance -- meaning success rates closer to 100% -- could still be years off. "While progress is significant, widespread automation, particularly in domains with low tolerance for errors, may still be some distance away," the researchers wrote. 2029 may not feel very far off for a meaningful uptick in what AI can automate, but given how quickly AI is already evolving, it does mean some extra time for the workforce to adapt. That said, the paper authors also don't think the speediest timeline is a guarantee. AI's evolution could be stymied by limits in compute, which is notoriously expensive to scale, as well as algorithmic and hardware constraints. Maintaining that competitive speed will depend on every component of the AI efficiency machine operating at full tilt. Another MIT study from December 2025 found that current AI systems could automate nearly 12% of the country's workforce as it stands today -- not just tech-specific jobs like coding, which many see as particularly exposed (entry-level developer jobs are already dwindling). That also isn't limited to coastal sectors, and covers roles in finance, HR, office administration, and more. Also: This AI expert says the job apocalypse isn't coming, even if you're a coder - here's why But whether that comes to fruition or not depends on how and where companies actually adopt AI, which is a whole different factor that puts projections all over the map. For example, in contrast to MIT's 12%, a January Forrester report estimated 6% of US jobs could be automated -- not now, but by 2030. At the end of February, Block CEO Jack Dorsey announced the company's decision to lay off nearly half its workforce based on what he said AI tools could handle internally. While there's no way to verify that's the case (and not just some savvy stock juicing), it set a tone: Will companies chasing efficiency gains and wanting to appear cutting-edge follow suit with mass layoffs? There are two camps in this debate. One, occupied by figures like Elon Musk, is driven by the belief that AI can put all humans out of work. In the other, experts think AI will change or augment work (a view supported by findings from Gartner) rather than replace human workers themselves. Career development expert Keith Spencer said he's seeing more of the latter: less job replacement and more augmentation and "uneven, role-specific change" that isn't uniform across the job market. He added that AI is also creating new opportunities in freelance and gig work for some (which AI itself hasn't been great at thus far). Also: I built an app for work in 5 minutes with Tasklet - and watched my no-code dreams come true "As certain tasks become faster and easier to complete, more work is being broken into smaller, project-based assignments that can be done independently," Spencer said. "That's opening the door for workers to take on additional income streams, even as they navigate uncertainty in their primary roles." Still, that augmentation has its costs. "When parts of your job are automated or reduced, it can feel like you're slowly being made obsolete, even if your role still exists," he said. "While the long-term trajectory may include both job creation and job displacement, the immediate experience for many workers is that the ground is shifting beneath them, and that's what's shaping behavior." Where AI isn't fully replacing human workers, it's extending the bounds of work itself. A February report from Harvard Business Review found that AI tools in the workplace don't necessarily save time or reduce work, as so many hoped, but actually intensify it. Workers reported using AI tools on lunch breaks and experimenting with prompts after hours to get ahead on projects. That doesn't sound negative, but that creep can have cumulative impacts on workers. Also: 7 AI coding techniques I use to ship real, reliable products - fast "Research from cognitive and organizational psychology has shown that restorative breaks are necessary; without them, cognitive performance and attention decline rapidly," said Tara Behrend, a professor of labor relations at Michigan State University. "This could be extremely dangerous depending on the kind of work being done." Mal Vivek, CEO at digital strategy company Zeb, thinks recent layoffs from Meta and Oracle are less about AI itself and more a response to a composite picture of the economy. "Many of these layoffs were more driven by AI applying market pressure rather than true enterprise AI adoption and automation driving the jobs away," she told ZDNET. "The jobs eliminated were jobs the company always believed it could live without -- with or without AI." Still, Vivek agreed that the layoffs are a growing trend and can be based on AI's capabilities. "We are seeing that AI is on average as good or better at many intellectual tasks, and the efficiency gains from it are just too promising for companies to ignore -- especially when their competitors are capitalizing," she said, speaking from experience at her own company. Also: I built two apps with just my voice and a mouse - are IDEs already obsolete? Spencer isn't seeing a decline in available jobs based on AI's impact yet, though. "We're seeing clearer changes in expectations than in job volume, at least for now," he said. "One of the biggest shifts is the growing importance of AI fluency. Employers are increasingly expecting workers to understand how to use AI tools, not necessarily at an expert level, but as part of their everyday workflow." Either way, data shows AI-induced job anxiety is high. According to a Resume Now survey of 1,000 adults in the US in December 2025, 60% of workers think AI will axe more jobs than it creates in 2026, and over half are concerned they'll lose their jobs because of AI this year. Another Resume Now survey conducted during the same time found that 41% of respondents believe AI "is replacing, devaluing, or overlapping with parts of their job," while 29% think of AI as a competitor that "could effectively complete at least half of their daily work tasks," rather than act as a copilot. Despite many real accounts of workers learning more with AI in the passenger seat, that's not everyone's experience: more than half of workers polled said AI hasn't impacted the growth of their skills or how they apply them. Also: Reinventing your career for the AI age? Your technical skill isn't your most valuable asset At the same time, however, at least one survey suggests 92% of young workers are using AI for professional development and that it's giving them confidence at work. The split could be generational. Only the latter Resume Now survey mentioned respondent demographics, which were nearly evenly split between men and women, but were just 15% Gen Z, with the rest split evenly between millennials, Gen X, and baby boomers. Spencer's advice echoes similar sentiments across the industry: identify what only you can offer, and what parts of your work are most and least susceptible to automation. Also: AI will accelerate tech job growth - former Tesla president explains where and why "Shift the focus from what AI might replace to where you add value that is harder to replicate," he said, citing skills like judgment, communication, and real-world context. "This is less about reacting to fear and more about understanding where your strengths fit into a changing landscape."
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MIT study challenges AI job apocalypse narrative
Why it matters: This directly pushes back on fear-based narratives coming from some AI leaders and reframes the debate from "when do jobs disappear?" to "how quickly do tasks shift?" State of play: AI is advancing across the workforce more like a "rising tide" than a "crashing wave" -- meaning work will change broadly and gradually, not through sudden job wipeouts in specific sectors, per the study. How it works: Instead of using benchmarks, the study measures whether AI can produce usable work in real-world settings. * The MIT researchers identified 11,500 tasks in the U.S. Labor Department's database and created multiple instances of each. They were then run through more than 40 AI models using workplace-style prompts. * They had workers in those fields evaluate more than 17,000 AI-generated outputs as to whether they were good enough to use without edits. By the numbers: In 2024, AI models could complete roughly 50% of text-based tasks at a minimally acceptable level, rising to 65% by 2025, per the report. * At the current pace, AI could handle 80% to 95% of text-based tasks by 2029 -- though only at a "good enough" level. Yes, but: "Good enough" isn't the same as reliable. * High-quality, error-free work remains much harder and is a gap that continues to trip up real-world deployments. * Recent examples include Deloitte's error-filled AI-generated report for a Canadian province and Klarna's pullback from AI-led customer service. Between the lines: The research finds that we are several years away from AI achieving near-perfect success rates, which means workers may have more time to adapt, making the disruption less abrupt. Zoom in: AI's impact varies by industry but reinforces the need for humans in the loop. * AI has the lowest success rate (47%) in legal work due to the need for precision, judgment and strategic guidance. * It has the highest success rate (73%) across installation, maintenance and repair tasks because of technology's ability to automate the administrative pieces of manual work, like troubleshooting and documentation. * In media, arts and design, AI has a 55% success rate, proving useful for drafting and ideation but lacking in higher-end creative execution, per the report. * Meanwhile, AI has a 53% success rate for managerial tasks like planning, writing and analysis, but is weak when it comes to coordination, judgment, and decision-making. What to watch: Integrating AI into workflows has proven to be hard and costly, which continues to slow AI adoption in the workplace. * March jobs numbers land tomorrow amid rising headlines about AI-linked layoffs. * In February, AI was cited in 10% of job cuts, but so far, a broad job apocalypse hasn't materialized. * Some are using the term "AI-washing" to describe the act of blaming cuts on AI to justify broader restructuring. (See Jack Dorsey's explanation for Block layoffs). The bottom line: The study challenges the idea of a sudden AI-driven employment cliff and instead points to a slower, more uneven reshaping of work. * For now, AI isn't replacing jobs -- it's gradually redefining them. 💠Eleanor thought bubble: This is helpful context for business leaders and communications teams managing the AI transformation inside companies.
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New MIT research reframes the AI employment debate. Instead of sudden job losses, AI impact on jobs will unfold gradually through 2029, giving workers time to adapt. The study found AI completed 65% of text-based tasks at minimally acceptable levels in 2025, rising to 80-95% by 2029—but reliability gaps remain significant.
The feared AI job apocalypse may not arrive as a sudden shock. New MIT study findings suggest AI impact on jobs will manifest as a "rising tide not a crashing wave," giving workers more time to adapt to the future of work
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. Rather than witnessing abrupt job displacement across entire sectors, the gradual reshaping of work will allow individuals to upskill for an evolving labor market.The MIT study analyzed 11,500 tasks from the US Department of Labor's Occupational Information Network (O*NET) database, running them through more than 40 AI models using workplace-style prompts
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. Researchers focused on tasks where AI could save humans at least 10% of their time, ensuring real-world relevance1
. Workers in those fields evaluated over 17,000 AI-generated outputs to determine usability without edits.By 2025, AI models could complete roughly 65% of text-based tasks at a minimally acceptable level, up from 50% in 2024
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. The study projects that Large Language Models (LLMs) could handle 80% to 95% of text-based tasks by 2029 at a "minimally sufficient" quality level1
. However, only 26% of tasks reached "superior quality" in current testing, revealing a significant gap between adequate and reliable performance.This distinction between "good enough" and error-free work matters enormously for AI adoption in industry. Recent examples highlight the reliability problem: Deloitte's error-filled AI-generated report for a Canadian province and Klarna's pullback from AI-led customer service demonstrate that automation of work tasks remains challenging in high-stakes environments
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Source: Axios
AI's success rate differs substantially by sector, reinforcing the need for human in the loop approaches. Legal work shows the lowest success rate at 47% due to requirements for precision, judgment and strategic guidance
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. Installation, maintenance and repair tasks achieved the highest success rate at 73%, as AI automates administrative pieces like troubleshooting and documentation.In media, arts and design, AI reached a 55% success rate, proving useful for drafting and ideation but lacking in higher-end creative execution
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. Managerial tasks like planning, writing and analysis showed a 53% success rate, with AI struggling in coordination, judgment, and decision-making.Related Stories
Another MIT study from December 2025 estimated that current AI systems could automate nearly 12% of the US workforce, covering roles in finance, HR, office administration, and beyond—not just coding positions
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. However, a January Forrester report projected only 6% of US jobs could be automated by 2030, illustrating how projections vary based on actual adoption rates.The question of job replacement or augmentation remains hotly debated. Career development expert Keith Spencer observes more augmentation and "uneven, role-specific change" rather than wholesale job replacement
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. In February, AI was cited in 10% of job cuts, with some experts using the term "AI-washing" to describe companies blaming cuts on AI to justify broader restructuring—as seen with Block CEO Jack Dorsey's announcement of layoffs affecting nearly half the workforce2
.The MIT study authors note that AI's evolution could be constrained by limits in compute, which remains expensive to scale, along with algorithmic and hardware constraints
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. Integrating AI into workflows has proven hard and costly, continuing to slow widespread adoption2
. Text-based work remains especially vulnerable to rapidly evolving AI capabilities, but consistent, "near-perfect" performance could still be years away. While 2029 may seem close for a meaningful uptick in what AI can automate, it provides crucial time for workforce adaptation compared to sudden disruption scenarios.Summarized by
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