2026-04-08 20:10:00
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.
As the conflict in Iran has escalated, a crucial resource is under fire: the desalinization technology that supplies water in the region.
President Donald Trump has threatened to destroy “possibly all desalinization plants” in Iran if the Strait of Hormuz is not reopened. The impact on farming, industry, and—crucially—drinking in the Middle East could be severe. Find out why.
—Casey Crownhart
This story is part of MIT Technology Review Explains, our series untangling the complex, messy world of technology to help you understand what’s coming next. You can read more from the series here.
For small entrepreneurs, deciding what to sell and where to make it has traditionally been a slow, labor-intensive process. Now that work is increasingly being done by AI.
Tools like Alibaba’s Accio compress weeks of product research and supplier hunting into a single chat. Business owners and e-commerce experts say they’re making sourcing more accessible—and slashing the time from product idea to launch.
Read the full story on how AI is leveling the path to global manufacturing.
—Caiwei Chen
When Zeus, a medical student in Nigeria, returns to his apartment from a long day at the hospital, he straps his iPhone to his forehead and records himself doing chores.
Zeus is a data recorder for Micro1, which sells the data he collects to robotics firms. As these companies race to build humanoids, videos from workers like Zeus have become the hottest new way to train them.
Micro1 has hired thousands of them in more than 50 countries, including India, Nigeria, and Argentina. The jobs pay well locally, but raise thorny questions around privacy and informed consent. The work can be challenging—and weird. Read the full story.
—Michelle Kim
This is our latest story to be turned into an MIT Technology Review Narrated podcast, which we’re publishing each week on Spotify and Apple Podcasts. Just navigate to MIT Technology Review Narrated on either platform, and follow us to get all our new content as it’s released.
The must-reads
I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology.
1 Anthropic’s new model found security problems in every OS and browser
Claude Mythos has been heralded as a cybersecurity “reckoning.” (The Verge)
+ Anthrophic is limiting the rollout over hacking fears. (CNBC)
+ It’s also launching a project that lets Mythos flag vulnerabilities. (Gizmodo)
+ Apple, Google, and Microsoft have joined the initiative. (ZDNET)
2 Iranian hackers are targeting American critical infrastructure
Their focus is on energy and water infrastructure. (Wired)
+ They’re targeting industrial control devices. (TechCrunch)
3 Google’s AI Overviews deliver millions of incorrect answers per hour
Despite a 90% accuracy rate. (NYT $)
+ AI means the end of internet search as we’ve known it. (MIT Technology Review)
4 Elon Musk is trying to oust OpenAI CEO Sam Altman in a lawsuit
As remedies for Altman allegedly defrauding him. (CNBC)
+ Musk wants any damages given to OpenAI’s nonprofit arm. (WSJ $)
5 ICE has admitted it’s using powerful spyware
The tools that can intercept encrypted messages. (NPR)
+ Immigration agencies are also weaponizing AI videos. (MIT Technology Review)
6 Greece has joined the countries banning kids from social media
Under-15s will be blocked from 2027. (Reuters)
+ Australia introduced the world’s first social media ban for children. (Guardian)
+ Indonesia recently rolled out the first one in Southeast Asia. (DW)
+ Experts say they’re a lazy fix. (CNBC)
7 Intel will help Elon Musk build his Terafab in Texas
They aim to manufacture chips for AI projects. (Engadget)
+ Musk says it will be the largest-ever semiconductor factory. (Engadget)
+ Future AI chips could be built on glass. (MIT Technology Review)
8 TikTok is building a second billion-euro data center in Finland
It’s moving data storage for European users. (Reuters)
+ Finland has become a magnet for data centers. (Bloomberg $)
+ But nobody wants one in their backyard. (MIT Technology Review)
9 Plans for Canada’s first “virtual gated community” have sparked a row
The AI-powered surveillance system has divided neighbors. (Guardian)
+ Is the Pentagon allowed to surveil Americans with AI? (MIT Technology Review)
10 The high-tech engineering of the “space toilet” has been revealed
Artemis II is the first mission to carry one around the world. (Vox)
Quote of the day
—OpenAI criticizes Musk’s legal action in an X post.
One More Thing
You may not notice it, but your experience on every US government website is carefully crafted.
Each site aligns an official web design and a custom typeface. They aim to make government websites not only good-looking but accessible and functional for all.
MIT Technology Review dug into the system’s history and features. Find out what we discovered.
—Jon Keegan
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.)
+ Rejoice in the splendor of the “Earthset” image captured by Artemis II.
+ Meet the fearless cat chasing off bears.
+ This document vividly explains what makes the octopus so unique.
+ Revealed: the rhythmic secret that makes emo music so angsty.
2026-04-07 22:54:06
MIT Technology Review Explains: Let our writers untangle the complex, messy world of technology to help you understand what’s coming next. You can read more from the series here.
As the conflict in Iran has escalated, a crucial resource is under fire: the desalination technology that supplies water across much of the region.
In early March, Iran’s foreign minister accused the US of attacking a desalination plant on Qeshm Island in the Strait of Hormuz and disrupting the water supply to nearly 30 villages. (The US denied responsibility.) In the weeks since, both Bahrain and Kuwait have reported damage to desalination plants and blamed Iran, though Iran also denied responsibility.
In late March, President Donald Trump threatened the destruction of “possibly all desalinization plants” in Iran if the Strait of Hormuz was not reopened. Since then, he’s escalated his threats against Iran, warning of plans to attack other crucial civilian infrastructure like power plants and bridges.
Countries in the Middle East, particularly the Gulf states, rely on the technology to turn salt water into fresh water for farming, industry, and—crucially—drinking. The mounting attacks and threats to date highlight just how vital the industry is to the region—a situation made even more precarious by rising temperatures and extreme weather driven by climate change.
Right now, 83% of the Middle East is under extremely high water stress, says Liz Saccoccia, a water security associate at the World Resources Institute. Future projections suggest that’s going to increase to about 100% by 2050, she adds: “This is a continuing trend, and it’s getting worse, not better.”
Here’s a look at desalination technology in the Middle East and what wartime threats to the critical infrastructure could mean for people in the region.
Desalination technology has helped provide water supplies in the Middle East since the early 20th century and became widespread in the 1960s and 1970s.
There are two major categories of desalination plants. Thermal plants use heat to evaporate water, leaving salt and other impurities behind. The vapor can then be condensed into usable fresh water. The alternative is membrane-based technology like reverse osmosis, which pushes water through membranes that have tiny pores—so small that salt can’t get through.
Early desalination plants in the Middle East were the first type, burning fossil fuels to evaporate water, leaving the salt behind. This technique is incredibly energy-intensive, and over time, processes that rely on filters became the dominant choice.
Membrane technologies have made up essentially all new desalination capacity in recent years; the last major thermal plant built in the Gulf came online in 2018. Many reverse osmosis plants still rely on fossil fuels, but they’re more efficient. Since then, membrane technologies have added more than 15 million cubic meters of daily capacity—enough to supply water to millions of people.
Capacity has expanded quickly in recent years; between 2006 and 2024, countries across the Middle East collectively spent over $50 billion building and upgrading desalination facilities, and nearly that much operating them.
Today, there are nearly 5,000 desalination plants operational across the Middle East.
And looking ahead, growth is continuing. Between 2024 and 2028, daily capacity is expected to grow from about 29 million cubic meters to 41 million cubic meters.
Some countries rely on the technology more than others. Iran, for example, uses desalination for about 3% of its municipal fresh water. The country has access to groundwater and some surface water, including rivers, though these resources are being stretched thin by agriculture and extreme drought.
Other nations in the region, particularly the Gulf countries (Bahrain, Qatar, Kuwait, the United Arab Emirates, Saudi Arabia, and Oman), have much more limited water resources and rely heavily on desalination. Across these six nations, all but the UAE get more than half their drinking water from desalination, and for Bahrain, Qatar, and Kuwait the figure is more than 90%.
“The Gulf countries are much, much more vulnerable to attacks on their desalination plants than Iran is,” says David Michel, a senior associate in the global food and water security program at the Center for Strategic and International Studies.
There are thousands of desalination facilities across the region, so the system wouldn’t collapse if a small number were taken offline, Michel says. However, in recent years there’s been a trend toward larger, more centralized plants.
The average desalination plant is about 10 times larger than it was 15 years ago, according to data from the International Energy Agency. The largest desalination plants today can produce 1 million cubic meters of water daily, enough for hundreds of thousands of people. Taking one or more of these massive facilities offline could have a significant effect on the system, Michel says.
Desalination facilities are quite linear, meaning there are multiple steps and pieces of equipment that work in sequence—and the failure of a component in that chain can take an entire facility down. Attacks on water inlets, transportation networks, and power supplies can also disrupt the system, Michel says.
During the Gulf War in 1991, Iraqi forces pumped oil into the gulf, contaminating the water and shutting down desalination plants in Kuwait.
The facilities are also generally located close to other targets in this conflict. Desalination is incredibly energy intensive, so about three-quarters of facilities in the region are next to power plants. Trump has repeatedly threatened power plants in Iran. In response, Iran’s military has said that if civilian targets are hit, the country will respond with strikes that are “much more devastating and widespread.” Other governments and organizations, including the United Nations, the European Union, and the Red Cross, have broadly condemned threats to infrastructure as illegal.
But war isn’t the only danger facing these plants, even if it is the most immediate. Some studies have suggested that global warming could strengthen cyclones in the region, and these extreme weather events could force shutdowns or damage equipment.
Water pollution could also cause shutdowns. Oil spills, whether accidental or intentional, as in the case of the Gulf War, can wreak havoc. And in 2009, a red algae bloom closed desalination plants in Oman and the United Arab Emirates for weeks. The algae fouled membranes and blocked the plants from being able to take water in from the Persian Gulf and the Gulf of Oman.
Desalination facilities could become more resilient to threats in the future, and they may need to as their importance continues to grow.
There’s increasing interest in running desalination facilities at least partially on solar power, which could help reduce dependence on the oil that powers most facilities today. The Hassyan seawater desalination project in the UAE, currently under construction, would be the largest reverse osmosis plant in the world to operate solely with renewable energy.
Another way to increase resilience is for countries to build up more strategic water storage to meet demand. Qatar recently issued new policies that aim to improve management and storage of desalinated water, for example. Countries could also work together to invest in shared infrastructure and policies that help strengthen the water supply through the region.
Preparedness, resilience, and cooperation will be key for the Middle East broadly as critical infrastructure, including the water supply, is increasingly under threat.
“The longer the conflict goes on, the more likely we’ll see significant water infrastructure damage,” says Ginger Matchett, an assistant director at the Atlantic Council. “What worries me is that after this war ends, some of the lessons will show how water can be weaponized more strategically than previously imagined.”
2026-04-07 22:00:00
Unlike static, rules-based systems, AI agents can learn, adapt, and optimize processes dynamically. As they interact with data, systems, people, and other agents in real time, AI agents can execute entire workflows autonomously.
But unlocking their potential requires redesigning processes around agents rather than bolting them onto fragmented legacy workflows using traditional optimization methods. Companies must become agent first.
In an agent-first enterprise, AI systems operate processes while humans set goals, define policy constraints, and handle exceptions.
“You need to shift the operating model to humans as governors and agents as operators,” says Scott Rodgers, global chief architect and U.S. CTO of the Deloitte Microsoft Technology Practice.
With technology budgets for AI expected to increase more than 70% over the next two years, AI agents, powered by generative AI, are poised to fundamentally transform organizations and achieve results beyond traditional automation. These initiatives have the potential to produce significant performance gains, while shifting humans toward higher value work.
AI is advancing so quickly that static approaches to task automation will likely only produce incremental gains. Because legacy processes aren’t built for autonomous systems, AI agents require machine-readable process definitions, explicit policy constraints, and structured data flows, according to Rodgers.
Further complicating matters, many organizations don’t understand the full economic drivers of their business, such as cost to serve and per-transaction costs. As a result, they have trouble prioritizing agents that can create the most value and instead focus on flashy pilots. To achieve structural change, executives should think differently.
Companies must instead orchestrate outcomes faster than competitors. “The real risk isn’t that AI won’t work—it’s that competitors will redesign their operating models while you’re still piloting agents and copilots,” says Rodgers. “Nonlinear gains come when companies create agent-centric workflows with human governance and adaptive orchestration.”
Routine and repetitive tasks are increasingly handled automatically, freeing employees to focus on higher value, creative, and strategic work. This shift improves operational efficiency, fosters stronger collaboration, and generates faster decision-making—helping organizations modernize the workplace without sacrificing enterprise security.
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.
2026-04-07 20:10:00
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.
Within Silicon Valley’s orbit, an AI-fueled jobs apocalypse is spoken about as a given. Now even economists who have downplayed the threat are coming around to the idea.
Alex Imas, based at the University of Chicago, is one of them. He believes that any plan to address AI’s impact will depend on collecting one vital piece of data: price elasticity.
Imas argues that “we need a Manhattan Project” for this. Read the full story to find out why.
—James O’Donnell
This article is from The Algorithm, our weekly newsletter giving you the inside track on all things AI. Sign up to receive it in your inbox every Monday.
In January, Elon Musk’s SpaceX applied to launch up to 1 million data centers into Earth’s orbit. The goal? To fully unleash the potential of AI—without triggering an environmental crisis on Earth.
SpaceX is among a growing list of tech firms pursuing orbital computing infrastructure. But can their plans really work? Here are four must-haves for making space-based data centers a reality.
—Tereza Pultarova
This story is part of MIT Technology Review Explains, our series untangling the complex, messy world of technology to help you understand what’s coming next. You can read more from the series here.
The must-reads
I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology.
1 Trump has again proposed major cuts to US science and tech spending
He wants to slash nearly every science-focused agency. (Ars Technica)
+ If Trump gets his way, the US could face a costly brain drain. (NYT $)
+ Top research talent is already fleeing the country. (Guardian)
+ Basic science deserves our boldest investment. (MIT Technology Review)
2 Sam Altman lobbied against AI regulations he publicly welcomed
A bombshell report reveals many OpenAI insiders don’t trust him. (The New Yorker $)
+ Some have called him a sociopath. (Futurism)
+ OpenAI’s CFO fears it won’t be IPO-ready this year. (The Information $)
+ A war over AI regulation is brewing in the US. (MIT Technology Review)
3 NASA’s Artemis II has broken humanity’s all-time distance record
The astronauts have flown farther than any humans before them. (BBC)
+ Their mission includes MIT-developed technology. (Axios)
4 Chinese tech firms are selling intel “exposing” US forces
It comes from combining AI with open-source data.. (WP $)
+ AI is turning the Iran conflict into theater. (MIT Technology Review)
5 War is pushing countries to ditch hyperscalers
Driven by Iran naming tech giants as military targets. (Rest of World)
+ No one wants a data center in their backyard. (MIT Technology Review)
6 OpenAI, Anthropic, and Google have united against China’s AI copying
They’re sharing information on “adversarial distillation” (Bloomberg $)
7 Anduril and Impulse Space are working on Trump’s “Golden Dome”
They’re developing space-based missile tracking for the project. (Gizmodo)
8 OpenAI has urged California to probe Elon Musk’s “anti-competitive behavior.”
It accuses Musk of trying to “take control of the future of AGI.” (Reuters $)
+ And claims he coordinated attacks with Mark Zuckerberg. (CNBC)
+ A former Tesla president has revealed how he survived working for Musk. (WP $)
9 DeepSeek’s new AI model will run on Huawei chips
It’s expected to launch in the next few weeks. (The Information $)
10 Memes have nuked our culture
Internet “brain rot” has escaped our phones to take over everything. (NYT $)
Quote of the day
—Astronaut Victor Glover tells President Donald Trump what it was like when Artemis II was out of communication with the rest of humanity, The New York Times reports.
One More Thing
Inside the controversial tree farms powering Apple’s carbon-neutral goal
In 2020, Apple set a goal to become net zero by the end of the decade. To hit that target, the company is offsetting its emissions by planting millions of eucalyptus trees in Brazil.
Apple is betting that the strategy will lead to a greener future. But critics warn that the industrial tree farms will do more harm than good.
Find out why the plans have sparked a backlash.
—Gregory Barber
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.)
+ Japan’s automated bike garage is a cyclist’s dream come true.
+ This deep dive into bird behavior reveals the secrets of their dining habits. (Big thanks to reader Terry Gordon for the find!)
+ The first photo from the Artemis astronauts vividly captures the glow of our atmosphere.
+ There’s a new contender for the world’s most gorgeous website: RobertDeNiro.com.
2026-04-07 00:33:35
This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here.
Within Silicon Valley’s orbit, an AI-fueled jobs apocalypse is spoken about as a given. The mood is so grim that a societal impacts researcher at Anthropic, responding Wednesday to a call for more optimistic visions of AI’s future, said there might be a recession in the near term and a “breakdown of the early-career ladder.” Her less-measured colleague Dario Amodei, the company’s CEO, has called AI “a general labor substitute for humans” that could do all jobs in less than five years. And those ideas are not just coming from Anthropic, of course.
These conversations have unsurprisingly left many workers in a panic (and are probably contributing to support for efforts to entirely pause the construction of data centers, some of which gained steam last week). The panic isn’t being helped by lawmakers, none of whom have articulated a coherent plan for what comes next.
Even economists who have cautioned that AI has not yet cut jobs and may not result in a cliff ahead are coming around to the idea that it could have a unique and unprecedented impact on how we work.
Alex Imas, based at the University of Chicago, is one of those economists. He shared two things with me when we spoke on Friday morning: a blunt assessment that our tools for predicting what this will look like are pretty abysmal, and a “call to arms” for economists to start collecting the one type of data that could make a plan to address AI in the workforce possible at all.
On our abysmal tools: consider the fact that any job is made up of individual tasks. One part of a real estate agent’s job, for example, is to ask clients what sort of property they want to buy. The US government chronicled thousands of these tasks in a massive catalogue first launched in 1998 and updated regularly since then. This was the data that researchers at OpenAI used in December to judge how “exposed” a job is to AI (they found a real estate agent to be 28% exposed, for example). Then in February, Anthropic used this data in its analysis of millions of Claude conversations to see which tasks people are actually using its AI to complete and where the two lists overlapped.
But knowing the AI exposure of tasks leads to an illusory understanding of how much a given job is at risk, Imas says. “Exposure alone is a completely meaningless tool for predicting displacement,” he told me.
Sure, it is illustrative in the gloomiest case—for a job in which literally every task could be done by AI with no human direction. If it costs less for an AI model to do all those tasks than what you’re paid—which is not a given, since reasoning models and agentic AI can rack up quite a bill—and it can do them well, the job likely disappears, Imas says. This is the oft-mentioned case of the elevator operator from decades ago; maybe today’s parallel is a customer service agent solely doing phone call triage.
But for the vast majority of jobs, the case is not so simple. And the specifics matter, too: Some jobs are likely to have dark days ahead, but knowing how and when this will play out is hard to answer when only looking at exposure.
Take writing code, for example. Someone who builds premium dating apps, let’s say, might use AI coding tools to create in one day what used to take three days. That means the worker is more productive. The worker’s employer, spending the same amount of money, can now get more output. So then will the employer want more employees or fewer?
This is the question that Imas says should keep any policymaker up at night, because the answer will change depending on the industry. And we are operating in the dark.
In this coder’s case, these efficiencies make it possible for dating apps to lower prices. (A skeptic might expect companies to simply pocket the gains, but in a competitive market, they risk being undercut if they do.) These lower prices will always drive some increase in demand for the apps. But how much? If millions more people want it, the company might grow and ultimately hire more engineers to meet this demand. But if demand barely ticks up—maybe the people who don’t use premium dating apps still won’t want them even at a lower price—fewer coders are needed, and layoffs will happen.
Repeat this hypothetical across every job with tasks that AI can do, and you have the most pressing economic question of our time: the specifics of price elasticity, or how much demand for something changes when its price changes. And this is the second part of what Imas emphasized last week: We don’t currently have this data across the economy. But we could.
We do have the numbers for grocery items like cereal and milk, Imas says, because the University of Chicago partners with supermarkets to get data from their price scanners. But we don’t have such figures for tutors or web developers or dietitians (all jobs found to have “exposure” to AI, by the way). Or at least not in a way that’s been widely compiled or made accessible to researchers; sometimes it’s scattered across private companies or consultancies.
“We need, like, a Manhattan Project to collect this,” Imas says. And we don’t need it just for jobs that could obviously be affected by AI now: “Fields that are not exposed now will become exposed in the future, so you just want to track these statistics across the entire economy.”
Getting all this information would take time and money, but Imas makes the case that it’s worth it; it would give economists the first realistic look at how our AI-enabled future could unfold and give policymakers a shot at making a plan for it.
2026-04-06 19:00:00
For years Mike McClary sold the Guardian LTE Flashlight, a heavy-duty black model, online through his small outdoor brand. The product, designed for brightness and durability, became one of his most popular items ever. Even after he stopped offering it around 2017, customers kept sending him emails asking where they could buy it.
When McClary decided to revisit the Guardian flashlight in 2025, he didn’t begin the way he might have in the past, by combing through supplier listings and sending inquiries to factories. Instead, he opened Accio, an AI sourcing and researching tool on Alibaba.com.
For small entrepreneurs in the US, deciding what to sell and where to make it has traditionally been a slow, labor-intensive process that can take months. Now that work is increasingly being done by AI tools like Accio, which help connect businesses with manufacturers in countries including China and India. Business owners and e-commerce experts told MIT Technology Review that these AI tools are making sourcing more accessible and significantly shortening the time it takes to go from product idea to launch.
McClary, 51, who runs his business from his Illinois living room, has sold products ranging from leather conditioner to camping lights, including one rechargeable lantern that brought in half a million dollars. Like many small online merchants, he built his business by being extremely scrappy—spotting demand for a product, tweaking existing designs, finding a factory, doing modest marketing, and getting the goods in front of customers fast.
This time, though, he began by telling Accio about the flashlight’s original design, production cost, and profit margin. Then Accio suggested several changes, making it smaller and slightly less bright and switching its charging method to battery power. It also identified a manufacturer in Ningbo, China, that McClary said could cut the manufacturing cost from $17 to about $2.50 per unit.
McClary took the process from there, contacting the supplier himself to discuss the revised design. Within a month, the new version of the Guardian flashlight was back up for sale on Amazon and on his brand’s website.
Although Alibaba is better known for owning Taobao, the biggest shopping site in China, its first business was Alibaba.com, the primary website that lists Chinese factories open for bulk orders. Placing an order with a manufacturer usually requires far more than clicking “Buy.” Sellers often spend days or weeks browsing listings, comparing suppliers’ reviews and manufacturing capacities, asking about minimum order quantities, requesting samples, and negotiating timelines and customization options.
But Accio has gained significant momentum by changing how that sourcing gets done. Launched in 2024, Accio exceeded 10 million monthly active users in March 2026, according to the company. That means about one in five Alibaba users consults with AI about product sourcing.
Accio’s interface looks a lot like ChatGPT or Claude: Users type a question into an empty box and choose between “fast” and “thinking” modes. But when asked about products, the tool returns more than text, offering charts, links, and visuals and asking follow-up questions to clarify the buyer’s needs. It then narrows the field to one or a handful of suppliers that appear capable of delivering. After that, the human work begins: Users still have to reach out to suppliers themselves and negotiate the details.
Zhang Kuo, the president of Alibaba.com, told MIT Technology Review that the tool is built on multiple frontier models, including the company’s own Qwen series, a popular family of open-source large language models. The system is able to pull from the site’s millions of supplier profiles and is trained on 26 years of proprietary transaction data.
For tasks like product research and sourcing analysis, the tool “blows it away” compared with general AI tools like ChatGPT, says Richard Kostick, CEO of the beauty brand 100% Pure.
Many websites have tried using AI to assist shopping, but Alibaba has been one of the most aggressive. In March, Eddie Wu, CEO of the site’s parent company Alibaba Group, told managers that integrating the company’s core services with Qwen’s AI capabilities is a top priority. During a Chinese New Year promotion of Qwen’s personal shopping AI agent, where the company gave away cash, customers placed 200 million orders, the firm says.
Vincenzo Toscano, an e-commerce seller and consultant, recommended Accio to his clients before deciding to try it himself for a new sunglasses brand. He came in with a rough vision: a brand shaped by his Italian heritage, his personal style, and a boutique aesthetic. He says the AI helped turn that concept into something more concrete, suggesting materials, refining the look, and pointing to design ideas that felt current.
But the tool has clear limits. McClary, who uses AI tools regularly, says Accio is strongest when it comes to product ideation, but less helpful on marketing questions such as advertising and social media outreach. To use it well, he says, buyers still need to challenge its recommendations, since some can be generic.
As platforms become more AI-driven, manufacturers are adjusting too. Sally Li, a representative at a makeup packaging company in Wuhan, China, says her firm has started writing more detailed product descriptions and adding information about its equipment and manufacturing experience on Alibaba.com because it suspects those details make its listings more likely to be surfaced by AI.
Yan says manufacturers cannot tell whether an inquiry from a customer was generated or guided by AI, and that her firm is not using AI to negotiate pricing or product details.
“AI agents are increasingly used by people to assist purchase decisions and even directly making transactions, and with clear guardrails, they can become extremely useful,” says Jiaxin Pei, a research scientist at the Stanford Institute for Human-Centered AI, “but agents need to act transparently, securely, and in the customer’s best interest.” Pei says developers of these tools should disclose the data they collect and the incentives built into them to ensure that the marketplace remains fair.
Zhang, of Alibaba.com, says Accio currently does not include advertising. Suppliers can pay for higher placement in Alibaba.com’s regular search results, but Zhang says Accio is “not integrated” with that system. “We haven’t had a clear answer in terms of how to monetize this tool,” he says. For now, users can pay for additional tokens to continue chatting with the agent after their free queries run out.
Sellers say that while AI tools have made it easier to come up with ideas and get a business off the ground, they do not replace the core skills that make someone good at e-commerce. McClary believes that even when sellers have access to the same market information, some are still better at making decisions, acting quickly, and actually delivering on orders. Those differences, he says, still go a long way.
Toscano, the brand founder and e-commerce consultant, feels good about officially launching his new brand of sunglasses in just a few months: “We [small business owners] always have to bootstrap a lot of decisions. Deciding what to sell often comes down to an educated guess,” he says, “And we’re now in an era when making those decisions is easier than ever.”
