This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here. Imagine coming in to work to learn that a new underling will report to you. The worker is not a person but an AI tool—one that your company nonetheless calls Alex, an “employee” with a title and defined responsibilities. How well do you think you would work with Alex? If you’re anything like the managers recently studied by Emma Wiles, a Boston University business professor, treating Alex as a “coworker” and not a software tool would lead you to do a worse job. Wiles found that people caught 18% fewer errors when the work was said to have come from an agentic “AI employee” rather than a chatbot. It turns out that what’s in a name matters. A lot.  This is an alarming glimpse of the future Silicon Valley is hurling us toward. Last year Nvidia’s CEO, Jensen Huang, talked about workplaces of “digital humans.” Since April, Microsoft, OpenAI, Anthropic, and Google have all released new tools oriented toward managing teams of AI agents, many of which are explicitly advertised as digital colleagues with the flexibility and cognitive power of actual humans. And nearly a third of the 1,261 managers who participated in Wiles’s study said their companies already frame AI agents as employees (23% even list them on org charts).
The technical progress of agentic AI is not all hot air, of course. Agents, which can effectively be thought of as AI tools programmed to work in a loop until they achieve a goal, have become measurably better at more complicated tasks. But it’s a huge leap to refer to these tools as coworkers or employees, and doing so will set unrealistic expectations for what AI can do while leaving the human employees supposedly responsible for them worse off. That’s partially because, Wiles’s research suggests, it inverts our sense of who’s in charge. When an AI tool was framed as an employee, participants in the study saw themselves as less responsible for its output. They were also 44% more likely to escalate its questionable work to a manager for further review rather than trusting their own corrections (thus negating the time-saving purpose of using the AI agent in the first place). 
That matters far beyond office culture: As AI agents are embedded into health care, warfare, education, and government, there’s a growing risk they’ll become a convenient place to dump blame for failures that are instead the product of bad human decisions, incentives, and oversight (recall how the bomb strike on a girls’ school in Iran was popularly blamed on Claude, when all signs point to a cascade of human errors). “AI agents right now are being marketed as things that can replace humans, and I think that’s just a losing proposition,” says Daron Acemoglu, an economist at MIT who won the Nobel Prize in 2024 and studies AI’s impact on the economy. “They should instead be optimized so that they can improve human capabilities, which is not what they have [been] at the moment.” What could that look like? Consider a new effort at Stanford, where researchers presented 1,500 workers in 104 jobs with information about what tasks AI could potentially do in their work and then asked what would actually be most helpful and productive. Workers did want automation in certain areas: Law clerks thought AI could help ensure that adequate progress was being made across cases, for example. But often the tasks that tech experts deemed most suitable for AI—like verifying customer credit ratings for sales reps—were what the actual workers said they definitely did not want or need an agent to do.  Which brings us back to Alex. Calling Alex an employee is easy—and convenient, especially when something goes wrong—but it’s a branding exercise. It doesn’t make the tool more fit for the job, and as Wiles’s research shows, it makes the humans around it worse at theirs. And recall that they are the ones with the agency that AI is trying to replicate. They deserve better than Alex. 

In partnership withMicrosoft Enterprise investment in AI is booming. Gartner is calling 2026 an “inflection year” for organizations to align their AI projects with strategic business objectives. As the pressure to prove ROI mounts, executives and technology leaders are looking to agentic AI to drive the measurable financial outcomes their businesses seek. A prime opportunity for AI agents exists in the tech function, where IT infrastructure costs are projected to grow two to three times by 2030, even as budgets remain unchanged, according to McKinsey. And in the last 18 months, tech teams—the engineers, developers, architects, and other practitioners who are building, deploying, and continually improving their organizations’ infrastructure and applications—are clearly putting agents to work. The ultimate promise of agents is not only to automate tasks but to manage and coordinate entire workflows, pursuing business goals in a way that allows humans and agents to work together. Given the risks involved in automated decision-making, teams cannot delegate the work that agents do without confidence that they are fully capable of performing the task and that it will do so in a safe, reliable, and secure manner. Among technology experts, our research shows that teams are exceedingly confident about using agentic AI across a significant amount of AI, data, and cloud tasks.
Where agent readiness drops is largely due to a lack of business context being supplied to agentic systems. The more complex the task, the more reasoning capability an agent requires and the greater its need for business context. Such context-generation capabilities for agents are still at an early stage of development, especially in situations where enterprise data is difficult to wrangle and connect into the agent lifecycle at the speed and quality in which developers and executives need it. Human oversight is a key factor of success in deploying agentic AI. Knowing that tech teams are in a pivotal position to lead this transformation, the experts we interviewed expect agent confidence to accelerate as experience with agents deepens and business environments mature. “As we design agents to operate within the same operational boundaries, identity systems, and governance models that teams already use, they start to behave more like the systems organizations already trust,” says Jeremy Winter, corporate vice president and chief product officer at Microsoft Azure Platform.
This report, based on a survey of 300 global technology experts, ranks 101 tasks across AI, data, and cloud workflows based on respondents’ confidence in agents acting on their behalf. It also examines how technology teams view the opportunities and challenges related to agentic AI, along with the potential for the technology to enhance their careers. Key findings from the report include: Confidence in agents is surging for measurable tasks and growing in areas of complex judgment. Technology experts overwhelmingly believe agents help with everyday work including streamlining processes, improving performance, and reducing repetitive tasks. Confidence is highest for processes like generating reports and boilerplate code, and there is clear opportunity where tasks involve multistep workflows and advanced reasoning to make decisions. Data workflows are the breakthrough domain. Tech teams trust agents most where structure can provide a reliable foundation for decisions. This includes areas such as data quality monitoring, visualization anomaly detection, real-time data stream monitoring, and data profiling. This is where domain experts closest to the point of data generation can provide context to allow agents to act and deliver trusted outcomes. Download the full report. Read the Microsoft Cloud blog by Amanda Silver, corporate vice president of Microsoft 365 Core and Work IQ, which underscores the importance of keeping humans in the loop and how systems thinking advances careers. And for a deeper dive into data workflows as a breakthrough use case for agents, check out the Fabric blog to hear from Kim Manis, corporate vice president of Product for Microsoft Fabric. This content was produced by Insights, the custom content arm of MIT Technology Review. It was not written by MIT Technology Review’s editorial staff. It was researched, designed, and written by human writers, editors, analysts, and illustrators. This includes the writing of surveys and collection of data for surveys. AI tools that may have been used were limited to secondary production processes that passed thorough human review.

This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. The inevitable weakness of metrics There are plenty of useful things a metric can reveal. There are even more that it can obscure or corrupt. Like a lot of people bitten by the self-quantifying bug, I started gathering personal data to pursue a nebulous collection of goals and desires. I wanted to feel better physically and emotionally, get outside more, and bring order to the messiness and uncertainty of my daily existence. But external metrics and data can never capture what’s truly important. Worse, they inevitably redefine your core sense of what’s important, whether you’re aware of the trap or not.
Dive into the dangers of quantifying our lives with metrics. —Bryan Gardiner
This story is from the next edition of our magazine, which is all about engineering. Subscribe now to get a copy when it lands! Elephant alert! AI warning systems aim to avoid deadly clashes India is home to about 60% of the world’s wild Asian elephants, and around 80% of their habitat lies outside protected areas. That brings them into close contact with people, and clashes can turn lethal: there have been some 3,000 human casualties in the last five years and over 1,000 elephant deaths since 2014. In response, state forest departments, NGOs, and locals are designing, testing, and deploying a range of AI systems that cut response and warning times to minutes—or even seconds. They range from wildlife eyes in Maharashtra to infrared drones in Chhattisgarh. Find out how they work in our interactive map. —Kanika Gupta The must-reads I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology. 1 The US has allowed Anthropic to release Mythos 5 to “trusted” orgsAbout 100 US companies and federal agencies now have access. (Semafor)+ The White House said appropriate safeguards were now in place. (WSJ $)+ The US had restricted both models over national security concerns. (BBC)+ Which raised new questions about AI safety. (MIT Technology Review)  2 A Chinese AI model has matched Mythos in finding security bugsSecurity researchers say Zhipu AI is poised to reset the AI race. (WSJ $)+ It’s sparked alarm that US restrictions are boosting China’s progress. (NYT $)+ Although it still can’t match Anthropic or OpenAI on general tasks. (Verge)+ In the AI race, China is eyeing a come-from-behind victory. (WP $) 3 Apple is seeking approval to buy chips from a blacklisted Chinese firmIt’s lobbying the White House for clearance to buy from ChangXin. (FT $)+ ChangXin is on a Pentagon list of firms with Chinese military ties. (WP $)+ Chipmakers are profiting off AI at the expense of everyone else. (WSJ $)+ The US is banning imports of more Chinese technology. (Reuters $)+ But Chinese tech companies feel optimistic. (MIT Technology Review) 4. South Korea plans to train its entire military as “drone warriors”It wants to train all 500,000 personnel. (Reuters $)+ And produce 110,000 drones by 2029. (Ars Technica) 5 Google has limited Meta’s use of its Gemini AI modelsMeta wanted more compute than Google could provide. (FT $)+ The cap has disrupted and delayed some Meta AI projects. (Bloomberg $)6 Zuckerberg wants Meta to work with Polymarket and KalshiMeta wants its own prediction market, but without real-money bets. (NYT $)+ The partnerships could hedge risks and accelerate development. (Reuters $) 7 Extreme heat is putting already hot data centers under pressureSevere weather is now the leading cause of loss for data centers. (CNBC)+ Heat waves also mess with your brain. (MIT Technology Review)8 Android phones alerted millions moments before Venezuela’s earthquakesThey gave users between seconds and up to two minutes’ notice. (NYT $)9 Scientists think Uranus and Neptune may not be the icy giants we imaginedThey may have a magma ocean brewing on the inside. (Gizmodo)10 Too much sleep may be as harmful as too littleA new study suggests 6.4–7.8 hours is the sweet spot. (Economist $)

Quote of the day “This kind of powerful weapon that can alter the landscape of cyberwarfare can’t remain solely in American hands.”  —360 Security CEO Zhou Hongyi tells a cybersecurity conference in Beijing why Chinese AI firms need to match the capabilities of their rivals in the US, The Wall Street Journal reports. One More Thing Why Generation Z falls for online misinformation Research shows that young people are more likely to believe and pass on misinformation if they feel a sense of common identity with the person who shared it in the first place.  Offline, teenagers are likely to draw on the context that their communities provide. Social media, however, promotes credibility based on identity rather than community. And when trust is built on identity, authority shifts to influencers. As young people participate in more political discussions online, those who have successfully cultivated identity-based credibility could become de facto community leaders, attracting like-minded people and steering the conversation. While that has the potential to empower marginalized groups, it also exacerbates the threat of misinformation. Find out what we can all learn about how young people evaluate truth online. —Jennifer Neda John
We can still have nice things A place for comfort, fun, and distraction to brighten up your day. (Got any ideas? Drop me a line.) + The Euclid space telescope has captured the most detailed image yet of the Milky Way.+ Here’s a lovely, lilting medieval bardcore cover of Daft Punk’s electronic classic Veridis Quo.+ A toilet plunger becomes an unlikely engineering breakthrough in this quest to build a better blowgun.

This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. Heat waves mess with your brain. Scientists are trying to figure out why. —Jessica Hamzelou It’s been hot in London this week. Really hot. A dangerous heat wave has hit Western Europe. On Wednesday, the UK recorded its highest ever June temperature at 36.1 °C (about 97 °F). But as the weather app on my phone confirmed, it felt like 39 °C. Much of Western Europe is suffering, bringing awful consequences for agriculture, infrastructure, and the health system. But heat can also affect the brain.
Studies have confirmed that as temperatures rise, people seem to get more irritable and more violent. And they have shown that firefighters find it harder to focus immediately after heat exposure. Rising temperatures can also have particularly disastrous outcomes for children and people with mental health disorders. Research on lab animals suggests that excessive heat can alter the function of chemical signals in our brains. But we still need a better understanding of the mechanisms behind these effects.
Here’s what scientists are learning about extreme heat’s impact on the brain. This story is from The Checkup, our weekly biotech newsletter. Sign up to receive it in your inbox every Thursday. For more on Europe’s heat wave, read our stories on why soaring temperatures are shutting down power plants and what they mean for the grid. The must-reads I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology. 1 The Trump administration has asked OpenAI to limit its next model releaseIt wants to vet the first GPT 5.6 users before a wider launch. (Bloomberg $)+ OpenAI said each of the initial partners will be government-approved. (FT $)+ It’s the first US firm to be told to restrict an AI model before release. (Axios)+ Anthropic is also still feuding with Washington. (MIT Technology Review)2 Apple and Xbox have hiked prices, blaming AI-driven chip costsSome MacBooks, iPads, and Xboxes are going up in price by over 20%. (BBC)+ Apple’s shares plummeted after the announcement. (NBC)+ AI data center demand has pushed up memory and storage prices. (WSJ $)+ The shortages have been dubbed “RAMaggedon.” (The Verge) 3 Colossal and the US are building an endangered species “biovault”It aims to cryptopreserve over 2,300 plant and animal samples. (Wired $)+ It comes amid growing threats to endangered species protections. (NYT $)+ Colossal is also growing chickens in artificial eggshells. (MIT Technology Review) 4 The US has banned Polestar from selling its EVs due to anti-China rulesThe Sweden-based company is majority-owned by China’s Geely. (CNN)+ The ban is because its connected-vehicle tech is linked to China. (Reuters $)+ What happened to China’s overseas EV factory boom? (Rest of World) 5 China is betting on humanoids to beat its demographic declineIt wants the robots to narrow the labour gap. (FT $)+ Gig workers are training humanoids at home. (MIT Technology Review) 6 The “fingerprints” of a black hole’s event horizon have been detectedThe discovery was made by studying ripples in space-time. (AFP) 7 OpenAI is now expected to delay its IPO until next yearIt’s been spooked by choppy global markets and SpaceX’s slump. (NYT $) 8 Data centers have moved to the forefront of environmental lawsuits The litigation is linked to energy sources, water consumption, and air pollution. (Guardian)9 A master gene that turns on human development has been uncoveredIt results in cells forming a human body. (New Scientist $)10 Grok’s most popular feature? SmutIt accounts for “well over half” of the chatbot’s traffic. (The Information $) Quote of the day “The most advanced AI is built by a handful of American companies, on American soil, under American law, and what the rest of us are permitted to do with it can change on a Friday afternoon.” —Nathan Benaich, AI investor at London-based venture firm Air Street Capital, tells the Financial Times about the geopolitical reality of US AI dominance.

One More Thing MAX-O-MATIC How technology helped archaeologists dig deeper In 1991, construction workers in Manhattan unearthed hundreds of coffins. Further investigation revealed that the remains were between 200 and 300 years old, and they were all African and African American. This discovery came at an inflection point in scientific history. Breakthroughs in chemical and genetic analysis allowed researchers to figure out where many of these people were born, the physical challenges they faced, and even the routes they took from Africa to North America. Today, archaeologists are using techniques they could only dream of then: lasers, 3D photography, lidar, satellite imagery, and more. These tools are revealing where people came from, how ancient cities were built, and the lives of those who built them.

EXECUTIVE SUMMARY It’s been hot in London this week. Really hot. A dangerous heat wave has hit Western Europe. Yesterday, the UK recorded its highest ever June temperature at 36.1 °C (about 97 °F). But as the weather app on my phone confirmed, it felt like 39 °C. It’s frightening that we are seeing such temperatures in the UK in June. According to the Met Office, the country’s national weather and climate service, June temperatures peaked at an average 19 °C (66 °F) in England between 1991 and 2020. Across Europe, the heat wave is likely to cause thousands of deaths. There will be other awful consequences for agriculture, infrastructure, and the health system. But this week I want to look at what the heat does to our minds and brains. Personally, I’ve found it almost impossible to think straight. The heat is distracting and my mind is foggy. I dread to think about the conditions of people who work outdoors, in even hotter regions. It’s not just exhaustion and confusion. The effects of heat on the brain can be deadly. And researchers are still trying to figure out why.
Studies have confirmed that as temperatures rise, people seem to get more irritable and more violent. Most of these studies are based on associations, though. It’s difficult to directly study how a heat wave might affect our thinking, says Catherine Thompson, a cognitive psychologist at Liverpool Hope University.  She has been studying the effects of extreme heat on firefighters instead. It’s easier to measure people’s cognitive skills before and after they undergo scheduled training that involves entering a burning building.  
It’s early days, but the team found that firefighters found it harder to focus and control their attention immediately after heat exposure—something people in heat waves can empathize with, I’m sure.  The firefighters’ skills returned to normal after 20 minutes or so of cooling down. But they’d experienced just 15 minutes of intense heat exposure. Thompson doesn’t know what the effects of living through a days-long heat wave might be—or how long they’ll last. Figuring that out might involve shipping cognitive test kits to thousands of people during the few days’ notice of an impending heat wave. “My guess [is] that no one’s done it because it’s just so difficult to do,” says Thompson.  Still, researchers can learn about some of the impacts of heat waves through studies after the fact. And those studies suggest that the heat seems to have more disastrous outcomes for people with mental-health disorders.  Those outcomes become apparent when temperatures rise above what is considered typical for a given region. “There seems to be a correlation where the hotter it gets, especially during the hottest times of the year, the worse the mental-health outcomes,” says Joshua Wortzel, who directs the Heat-Mind Lab at Hartford HealthCare in Connecticut. In a study published in 2023, Emma Lawrence at the University of Oxford, who studies the effect of climate change on mental health, and her colleagues reviewed the evidence linking mental-health outcomes to ambient outdoor temperatures. They found that during heat waves, there was a 9.7% increase in the rate of hospital admissions for people with such conditions.  “People who live with mental-health conditions are among the most susceptible to the physical impacts of heat,” says Lawrence. People with schizophrenia were found to have been three times more likely to die during the record-breaking heat wave that affected Canada in 2021, for example. In order to protect people, we need a better understanding of the mechanisms underlying these effects. After all, a lot of things change when it’s very, very hot. Some people may end up stuck indoors, avoiding outdoor play and exercise, and it can be difficult to get a good night of sleep, for example. Sleep, socializing, and exercise are all really important for our mental health.  But whether unusual heat does something specific to our brains is, as Wortzel puts it, “the million-dollar question.”

Research in lab animals suggests that excessive heat can alter the way chemical signals work in our brain. The levels of neurotransmitters like serotonin, for example, seem to increase when rats and mice are exposed to high temperatures, according to multiple studies. The heat may also interfere with the way networks in our brains communicate with each other. It might affect the way oxygen reaches our brain cells. “There are so many biological reasons why brains may be negatively affected by heat,” says Wortzel. Emerging research suggests that for whatever reason, children and young people are among the most vulnerable. In research published earlier this week, Wortzel and his colleagues saw a 2.97% increase in the suicide rate among people in the US aged 15 to 24 for every 1 °C increase in average monthly temperature. That’s more than double the increase seen in people over the age of 24 (which is concerning in its own right). Other work hints that heat exposure might have long-term consequences for children’s brain development. Babies who were exposed to either extreme heat or cold appeared to have altered white matter by the time they were nine to 12 years old—although it’s not clear how these impacts might affect an individual child. “It seems that extreme temperature exposure for very young children may affect their brain development,” says Lawrence, who spoke to me from Oxford. She was meant to be in London for Climate Action Week, but her event, which focused on extreme heat, ended up being canceled … owing to the extreme heat. We are living through the effects of climate change. And that brings a new urgency to the question of how heat affects our brains. Children born in 2020 are predicted to experience around seven times the number of heat waves their grandparents did, says Lawrance. “[We] need to be serious about adapting to a warming world.” This article first appeared in The Checkup, MIT Technology Review’s weekly biotech newsletter. To receive it in your inbox every Thursday, and read articles like this first, sign up here.

In partnership withInfosysArtificial intelligence is rapidly reshaping retail, but not in the ways consumers might immediately notice. The biggest transformation may not be flashy virtual try-ons or chatbot shopping assistants, but in how decisions are made behind the scenes: how products surface in search results, how inventory moves through supply chains, how engineers ship code faster, and how retailers respond to customer behavior in real time. As legacy retailers navigate a fragmented and hyper-competitive landscape, AI is becoming an operating philosophy. [embedded content] At Macy’s, that philosophy is more often defined by what senior director of engineering Murali Murugan describes as an “AI-first” approach. “AI first isn’t about adding intelligence on top,” Murugan says. “It’s about redesigning how decisions happen so the business moves faster and every experience feels more relevant by default.” Rather than layering AI onto existing workflows, Macy’s is embedding intelligence directly into systems that include personalization, search, operational planning, and software development itself.The company’s strategy is reflective of a larger shift taking place across retail: moving from isolated AI pilots toward integrated systems designed to compress, as Murugan puts it, “the gap between the signal and the action.” Early efforts focused on narrow, high-impact use cases like search recommendations and customer engagement, where measurable gains in conversion and reduced friction quickly built internal momentum. “Once we established the quick wins, scaling was a business decision, not a technology debate anymore,” he says.That momentum is now extending into conversational commerce through tools like Ask Macy’s, an AI-powered shopping assistant designed to act more like a personal stylist than a traditional search bar. Whether for a prom, a vacation, or a last-minute event, customers can describe what they need conversationally and receive curated recommendations informed by past purchases, preferences, and context.Still, the company sees AI as more of an invisible layer augmenting human judgment than a replacement for it. The long-term vision is retail that feels increasingly seamless, adaptive, and personalized, powered by systems customers may never even notice are there.”The real transformation in this all comes from continuous improvement,” Murugan says. “It’s about learning from the mistakes, quickly adapting to the newer technology standards that are coming into play, timing, and execution which compound into a meaningfully better customer experience.” This webcast is produced in partnership with Infosys. This content was produced by Insights, the custom content arm of MIT Technology Review. It was not written by MIT Technology Review’s editorial staff. It was researched, designed, and written by human writers, editors, analysts, and illustrators. This includes the writing of surveys and collection of data for surveys. AI tools that may have been used were limited to secondary production processes that passed thorough human review.