In 2026, the question for enterprise AI is no longer whether predictive models can outperform statistical forecasts—that argument is settled. The big question now is how to enable predictive systems to act on their own conclusions without drifting from business intent. The frontier has moved from prediction to autonomous decision making, and the gap between leaders and laggards is widening accordingly.
“Enterprises are done with a backward-looking point of view; they want to be more forward-thinking,” says Vishal Gupta, partner at research firm Everest Group.
Intelligent analytics, powered by technologies like deep learning and generative AI, are making this possible. Real-time training allows AI to evolve continuously instead of waiting for quarterly refreshes. In addition, the data that newer predictive engines rely upon has expanded to encompass not just neat, numerical records but also messy, unstructured sources of insight-rich interactions. As a result, AI-powered analytics are moving enterprises from passive hindsight to pragmatic foresight.
AI takes predictive analytics—a broad discipline that includes predictive modeling, data prep, analysis workflows, interpretation of results, and decision-making applications—to new heights. “In many ways I think the word ‘analytics’ is giving way to AI,” says Gupta. “Everything is becoming AI.”
This content was produced by Insights, MIT Technology Review’s custom content arm, not its editorial staff. It was researched and written by humans, with any AI tools that may have been used limited to production processes under human oversight.
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.
People really hate AI, so why can’t they get enough?
—Will Douglas Heaven
Over the summer I talked to the CEO of Springboards, a startup building an LLM designed to come up with a wide variety of responses. He said something that’s been stuck in my head since: “We often say that we’re a self-loathing AI company. We don’t know if we really like what we’re doing.” My reply? “I guess that makes me a self-loathing AI journalist.”
Around the world, a love/hate attitude toward AI is very much the vibe right now. Public sentiment is souring fast, with more people saying AI will have a negative impact than a positive one. At the same time, AI use is skyrocketing.
So why do people hate AI but keep coming back for more? Here’s my theory.
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EmTech Future 2026: when AI meets everything
Last week, EmTech Future 2026 explored some of the biggest questions shaping technology right now: how AI is changing industries, where quantum is heading, what new energy systems could make possible, and how robotics are evolving. It also looked at what happens when these technologies start to converge.
The full program is now available on demand. And today, we’re releasing two sessions exclusively to subscribers: a chat with Google Research’s Yossi Matias on how AI is reshaping biology, infrastructure, manufacturing and science, and a special panel with MIT Technology Review editors that takes you inside our newsroom.
I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology.
1 Trump has unveiled a “Super Intelligence Force” to oversee AI The group will coordinate US AI policy and industry engagement. (NBC News) + Trump named national intelligence chief Jay Clayton as its leader. (NPR) + Elon Musk says he will rename SpaceXAI to SpaceXSI. (Reuters $) + Trump has doubled down on voluntary AI safeguards. (Information $) + Who’s liable when AI agents go rogue? (MIT Technology Review)
2 Zelensky asked Trump to block Russia and China’s Starlink rival The two countries are developing a satellite network for the battlefield. (FT $) + Trump reportedly deferred the decision to Elon Musk and SpaceX. (TNW)
3 An AI version of a murder victim has upended his killer’s sentence An appeals court has ruled that the original deepfake of the victim “forgiving” his killer should never have been aired in court. (BBC) + The original judge said he “loved” the footage and found it genuine. (NBC News) + But the appeals court said it presented imagined thoughts as fact. (NYT $)
4 Americans are turning to hybrid cars as fuel prices soar SUVs and pickups are losing ground to more efficient vehicles. (NYT $) + What’s next for EV batteries? (MIT Technology Review)
5 China’s digital trade “superweapon” has quietly fallen apart LOGINK’s partnerships have collapsed amid US scrutiny. (Reuters $) + Chinese AI has divided the White House. (MIT Technology Review)
6 AI has learned to exploit the software checking its maths Developers have added defenses against proof-checking. (New Scientist)
7 GPT-6 Astra couldn’t beat humans at StarCraft—so it cheated It downloaded the best human-made bot and ran that instead. (Verge + Here’s why AI agents lie and cheat. (MIT Technology Review)
8 The solar system has been given a dramatically shorter lifespan New simulations cut it from 100 billion years to just a few billion. (404 Media)
9 Forensic technologies exposed fresh evidence of Egyptian sacrifice They revealed blunt force trauma that archaeologists previously thought was natural. (Ars Technica)
10 A new fossil shows dinosaurs found multiple ways to evolve flight They developed similar flight adaptations in different sequences. (Nature)
Quote of the day
“We believe that the world should accept some bad things happening for the benefits of this technology.”
—Sam Altman tells Politico that AI’s potential rewards justify its downsides.
One more thing
Inside the stealthy startup that pitched brainless human clones
After operating in secrecy for years, R3 Bio, a California-based startup, suddenly revealed this spring that it had raised money to create nonsentient monkey “organ sacks” as an alternative to animal testing. But there is more to the story. And R3 doesn’t want that story told.
MIT Technology Review discovered that founder John Schloendorn also pitched a startling, ethically charged vision: “brainless clones” that serve as backup human bodies. Find out all the details on the radical proposal.
—Antonio Regalado
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.)
+ Trace the weird history of space food with this short documentary + Meet the winner of Iowa’s annual hay bale toss, who threw one 13 feet 6 inches into the air. + 40 filmmakers in 25 countries have captured the natural world entirely on Super 8 in a collective ode to our planet. + This newsletter makes a compelling argument for us to spend more time doing nothing together.
Over the summer I talked to the CEO of Springboards, a startup building an LLM that’s designed to come up with a wider variety of responses than its mainstream rivals do. At the start of the call, he said something that’s been stuck in my head since: “We often say that we’re a self-loathing AI company. We don’t know if we really like what we’re doing.”
“I guess that makes me a self-loathing AI journalist,” I replied. It was a joke! I love my job. But I do not love many of the things the technology I write about has become: warped by hype, steered by zealots, inescapable.
The CEO of Springboards and I are far from alone. Around the world, a love/hate attitude toward AI is very much the vibe right now.
On the one hand, public feelings are souring fast. According to the Pew Research Center, more adults in the US think AI will have a negative impact on them personally, and on society in general, than expect a positive one. The pessimism is strongest among the young.
More than half of people worldwide say that AI products and services make them nervous, according to a report from Stanford University. In a Gallup poll in May, 71% of US adults said they would oppose construction of a new AI data center in their area, far more than the 53% who said they would oppose a new nuclear power plant. And in an NBC poll in March, AI was less popular than ICE.
Yet the number of people using AI is still skyrocketing. ChatGPT hit a billion monthly users in May, according to the market analysis firm Sensor Tower. Google DeepMind’s Gemini is close behind, logging 950 million users in July.
According to Pew, half of US adults now say they use a chatbot, more than twice the number who said they did in 2023. One in four people say they do so every day. And it’s a global habit: More than a third of adults across all 38 OECD countries (a group of the world’s wealthiest democracies) report having used generative AI tools in the last three months.
All these surveys paint a picture of two contradictory truths: A lot of people really do not like AI and a lot of people cannot get enough of it. What’s going on?
It’s possible that these are two distinct groups, but I doubt it. The numbers don’t add up unless the Venn diagram is on its way to being a circle.
It’s also possible that the more people use AI, the more negative their opinions about it will be. There’s at least a correlation to back this up: The Global North, where adoption is highest, skews pessimistic. In the Global South, where adoption levels are lower, people are more optimistic.
But here’s what I really think is going on: When people say they hate AI it’s not the technology they dislike but, rather, the relentless drive of the companies behind it to push the tech upon us in as many ways as possible. They’re telling us to brace for the biggest social and economic upheaval in generations. How do they expect people to feel?
In many ways, we’ve been here before. We saw a similar dynamic play out with social media over the last 20 years. Billions flocked to Facebook and Twitter despite mounting techlash against the companies that ran those services. Ditto for Google search.
With social media there wasn’t much anyone could do. Quitting a platform meant losing all your content and connections, giving you the choice to suck it up or start over. But with AI there’s still a chance for people to have some sway. There’s certainly more political appetite for regulation this time around. All 50 US states have either passed or proposed laws governing the development and deployment of AI, creating a patchwork of more than 2,100 bills across the country—a tenfold increase in three years.
And with a number of top-class open-source alternatives to Google and OpenAI and Anthropic already on the market, there’s also (for now, at least) the potential for more consumer choice and the market pressure that goes with it.
I don’t want to be naïve. Trillion-dollar companies are hard to move. But what comes next is not as inevitable as those companies often imply. When I asked the Springboards CEO why his firm was developing a new model if he didn’t really like AI, he told me there was no walking back from LLMs—but you could still make them do something different.
Here’s hoping we see a lot more of something different: Clarity about what AI can and cannot do and, crucially, a technology that’s not sold as if it’s about to take over the world.
Yossi Matias, Vice President & Head of Google Research, explores how AI is beginning to reshape biology, infrastructure, manufacturing, and science, and why its greatest impact may come when it intersects with other fields.
Step inside the newsroom with our MIT Technology Review editors for sharp analysis and unpublished insights from the team that researches and reports on emerging tech daily.
There’s much more to discover
These are just two sessions from EmTech Future 2026.
Across three days, EmTech Future explored some of the most important questions shaping technology right now: how AI is impacting industries, where quantum is heading, what new energy systems could make possible, how robotics are evolving, and what challenges and opportunities arise when these technologies start to converge.
Hear the ideas, insights, and perspectives you missed at EmTech Future 2026.
The full program is now available on demand, giving you access to all the conversations and sessions from the event, including:
Quantum in context Hartmut Neven, founder and lead at Google Quantum AI, explores how quantum is advancing alongside other frontiers and why its significance may lie not only in what it can do on its own, but in how it begins to interact with the systems around it.
Energy Systems for the Future Evelyn Wang, VP for energy & climate at MIT, explores how energy, computing, infrastructure, and climate technologies are increasingly interconnected, and what these converging systems could mean for the future of industry and society.
Rethinking our relationship with AI –Cory Doctorow, bestselling author and award-winning writer, explores how AI is changing the way we work and think.
As an MIT Technology Review subscriber, you’ll get a 20% discount, meaning you can access the full EmTech Future 2026 program for just $596.
Roman Storm and the XRP army aren’t happy former SEC boss Jay Clayton is Trump’s new AI czar, Peter Brandt flips bullish and says Bitcoin may reach as high as $600K by 2029.
