Source: Fast Company, Megan Carnegie
Photo: Freepik

Recent graduates are clearly not okay—but neither are the companies that decided they could do without them.

Isaac, 33, has been a mid-level software development engineer at a Big Tech firm for four years, and noticed entry-level job postings dropping at his workplace at the start of 2025. The work, however, didn’t vanish with them. Tasks once handled by junior engineers—like writing and testing code, fixing bugs, and contributing to development projects—were absorbed by senior staff, often with the assumption that AI would make up the difference.

And while AI has sped up the velocity of shipping code and features, there are fewer people to do tasks like designing, testing, and working with stakeholders, which AI has zero grasp on. The cracks have been hard to ignore. “Seniors are burning out, and when they leave, there’s no rush to replace them, because ‘the AI will do it’!” Isaac says. Worried that he’ll become the next strung-out senior, he’s looking for his exit, ideally at a smaller tech firm. (Isaac spoke to Fast Company under a pseudonym to avoid possible retaliation.)

The shift is striking, given how recently corporate America was courting Gen Z with fanatic fervor. Organizations raced to prove they understood younger employees. They flooded LinkedIn with thought leadership on the multigenerational workplace of the future, and retooled benefits programs to include wellness stipends and mental health days. Reverse mentorship programs, through which younger employees share knowledge and perspectives with more senior colleagues—touted by companies like Target, Accenture, and PwC—promised to give junior employees a voice in shaping culture and strategy. Some firms even brought Gen Z voices into the boardroom.

Yet now, in the case of firms like Isaac’s, entry-level workers, once heralded as essential to innovation and growth, are struggling to get a toe—let alone a foot—in the door. Internships, starter jobs, and junior roles, the indispensable on-ramps to white-collar careers, have been evaporating for several years due to cost pressures and post-pandemic belt-tightening. Since 2023, entry-level job postings in the U.S. have sunk 35%, according to labor research firm Revelio Labs.

The advent of AI is accelerating the entry-level apocalypse. Two-fifths of global leaders revealed that entry-level roles have already been reduced or cut due to efficiencies made by AI conducting research, admin, and briefing tasks, and 43% expect this to happen in the next year.

“While there’s steady hiring or even growth in the skilled trades, we’re seeing entry-level vacancies fall significantly in tech and customer service and sales roles,” says Mona Mourshed, founder of the workplace development nonprofit Generation. “Being in the business of training and placing people into entry-level roles, we find it deeply concerning.” Graduates are clearly not okay—but neither are the companies that decided they could do without them.

AI at work: the supercar with no driver

The logic was seductive in its simplicity. Cut costs, move faster, shrink training budgets, let AI and a leaner workforce handle the rest. In reality, it’s producing something else entirely: flattened teams with little agency, endless cycles of rework, and exhausted senior employees juggling all task levels at once.

One redditor who posted about how their company has stopped hiring entry-level engineers, received hundreds of other responses as others chiming in with similar stories. One commenter noted: “Not sure what the plan will be after the knowledge transfer is over.”

Isaac has watched this dynamic unfold firsthand. Leaders at his company see AI as a force multiplier, and are fixated on shipping features quickly. Isaac can see their point: “[AI] can straight up write better, faster, more legible code than most developers,” he admits. However, he points out, “any seasoned engineer knows the hard part isn’t writing the code, it’s the design and testing.” Yet, there’s far fewer people to delegate this work to, so senior developers are left to do this on their own.

Compounding the problem is the fact that AI doesn’t understand the problem it’s meant to solve. Left unchecked, it can go rogue. Isaac recalls multiple instances of chatbots deleting production stacks—unprompted—because they couldn’t figure out how to solve an issue. “Without an expert who knows how to prompt and guide it, AI is just a supercar with no driver,” he says. The team has seen their workload steadily increase in line with automation, so the time savings it creates have had little impact. Many seniors have checked out, with several burned out engineers signed off for medical leave.

Research from the project management platform Asana underscores this growing “efficiency illusion.” While 77% of workers are already using AI agents and expect to hand more off to them in the next year, nearly two-thirds say the tools are unreliable, and more than half say agents confidently produce incorrect or misleading information. The result is time down the drain: a U.S. study found that employees are spending an extra 4.5 hours a week fixing AI workslop.

“AI can make work look faster on the surface, but it can also create a lot of cleanup work—double-checking outputs, correcting errors, and redoing steps that were based on faulty information,” Mark Hoffman, Asana’s Work Innovation Lead, tells Fast Company. When something goes wrong, accountability is murky, he adds, and the responsibility often falls back on the employee to catch errors, explain outcomes, and manage the risk. It’s driving up already record-high levels of burnout; 77% of knowledge workers say their workloads are unmanageable, and 84% are digitally exhausted.

When errors slip through, the consequences are costly and embarrassing. Three-quarters of Americans report at least one negative consequence from poor AI outputs, including work rejected by stakeholders (28%), security incidents (27%), and customer complaints (25%). In October, Deloitte was forced to refund the Australian Department of Employment and Workplace Relations after a report was found to contain AI hallucinations and workslop. In the past, newbie consultants would have handled tasks such as this. However, notably, Deloitte cut its graduate cohort by 18% and slashed hundreds of early-career roles earlier that summer.

The demographic time bomb

Not only are workloads increasing, by hollowing out their junior ranks, businesses are putting themselves squarely in the path of a slow-burning demographic time bomb as seniors begin to retire in record numbers.

From 2024 to 2032, 18.4 million experienced workers age 55 to 64 with postsecondary education are expected to retire, but only 13.8 million younger workers (currently age 16 to 24) are entering with equivalent qualifications. Even in an AI-powered economy, where certain jobs will be automated, companies still need humans with judgment-, context-, institutional-, and sector-specific insight.

Yet plenty are making moves—at least for today—to wipe out the training ground that turns beginners into experts.

“There won’t be an endless supply of experienced hires to fall back on, so everyone will be fighting for the limited, increasingly expensive talent with domain expertise,” says Cali Williams Yost, futurist and founder of flexible-work consulting firm Flex+Strategy Group. “Companies have maybe five years to train younger workers to take over and gain the niche knowledge, so AI has something to augment.”

Moe Hutt, an entry-level recruitment marketing expert and director of consulting at recruitment marketing agency HireClix, has watched clients scale back or abandon entry-level hiring, citing AI-aided workflows and economic uncertainty. Hutt points to the less visible fallout within organizations beyond damaging the talent pipeline. “It’s human nature to want to help,” she says. “When there’s no release valve of training juniors, it creates friction everywhere.”

For middle and senior management, delegating, teaching, and watching someone grow is a reward for the experience. Research consistently shows that sharing knowledge and mentoring improves motivation, boosts psychological well-being, and reduces burnout among experienced employees. With no one to train or teach, disengagement spreads, eroding a workforce where most people have already checked out.

Being AI-savvy and being prepared for the demographic cliff aren’t mutually exclusive. Organizations can build pro-worker environments where employees are augmented with AI, without hollowing out their future talent pipelines. PwC—admittedly, another firm which has been open about its cuts to entry-level recruiting, at least in the U.K.—is experimenting with what that balance could look like by training junior accountants to become managers of AI. Entry-level employees gain early exposure to leadership and accountability, while the firm builds a cache of managers that are fluent in both human judgment and machine output. It’s proof that efficiency and succession planning can coexist.

This matters because disappearing entry-level jobs aren’t just a problem for the corporate workforce—it will be a societal crisis, too. A functioning society depends on younger generations steadily taking over from older ones.

AI might be able to write the code, but without people trained to guide it, question it, and eventually replace their elders, there will be no one left to keep the lights on.

ABOUT THE AUTHOR

Megan Carnegie is a London-based freelance journalist who specialises in writing features about the world of technology, work, and business for publications like WIRED, Business Insider, Digital Frontier and BBC. Her work is underpinned by a desire to investigate what’s not working in the working world, and how more equitable conditions can be secured for workers—whatever their industry.

https://www.fastcompany.com/91483431/companies-replaced-entry-level-workers-with-ai

Source: Time, Angela Haupt
Photo: Vertigo3d—Getty Images

Haupt is a health and wellness editor at TIME.

AI might not have taken your job yet—but it’s already writing your breakup text.

What began as a productivity tool has quietly become a social one, and people increasingly consult it for their most personal moments: drafting apologies, translating passive-aggressive texts, and, yes, deciding how to end relationships.

“I wholeheartedly believe that AI is shifting the relational bedrock of society,” says Rachel Wood, a cyberpsychology expert and founder of the AI Mental Health Collective. “People really are using it to run their social life: Instead of the conversations we used to have—with neighbors or at clubs or in our hobbies or our faith communities—those conversations are being rerouted into chatbots.”

As an entire generation grows up outsourcing social decisions to large language models (LLMs) like ChatGPT, Claude, and Gemini, Wood worries about the implications of turning the emotional work of connection over to a machine. What that means—for how people communicate, argue, date, and make sense of one another—is only beginning to come into focus.

When AI becomes your social copilot

It often starts as a second opinion. A quick paste of a text message into an AI chatbot. A question typed casually: “What do you think they meant by this?”

“People will use it to break down a blow-by-blow account of an argument they had with someone,” Wood says, or to decode ambiguous messages. “Maybe they’re just starting to date, and they put it in there and say, ‘My boyfriend just texted me this. What does it really mean?’” They might also ask: Does the LLM think the person they’re corresponding with is a narcissist? Does he seem checked out? Does she have a pattern of guilt-tripping or shifting blame?

Some users are turning to AI as a social rehearsal space, says Dr. Nina Vasan, a clinical assistant professor of psychiatry at Stanford University and the founder and director of Brainstorm: The Stanford Lab for Mental Health Innovation. People gravitate to these tools because they’re “trying to get the words right before they risk the relationship,” she says. That might mean asking their LLM of choice to draft texts to friends, edit emails to their boss, help them figure out what questions to ask on a first date, or navigate tricky group-chat dynamics.

Vasan has also seen people use AI tools to craft dating-app profiles, respond to passive-aggressive family members, and set boundaries they’ve never before been able to articulate. “Some use it to rehearse difficult conversations before having them,” she says. “Others process social interactions afterward, essentially asking AI, ‘Did I handle that OK?’” ChatGPT and other LLMs, she says, have become a third party in many of our most intimate conversations.

Meet the new relationship referee

Consulting AI isn’t always a welcome development. Some young people, in particular, now use LLMs to generate “receipts,” deploying AI-backed answers as proof that they’re right.

“They use AI to try to create these airtight arguments where they can analyze a friend’s statements or a boyfriend’s statements, or they especially like to use it with their parents,” says Jimmie Manning, a professor of communication studies at the University of Nevada, where he’s also the director of the Relational Communication Research Laboratory. (None of his students have presented him with an AI-generated receipt yet, but it’s probably only a matter of time, he muses.) A teen might copy and paste a text from her mom into ChatGPT, for example, and ask if her parents are being unreasonably strict—and then present them with the evidence that yes, in fact, they are.

“They’re trying to get affirmation from AI, and you can guess how AI responds to them, because it’s here for you,” Manning says.

Using LLMs in this way turns relationships into adversarial negotiations, he adds. When people turn to AI for validation, they’re usually not considering their friend or romantic partner or parent’s perspective. Plus, shoving “receipts” in someone’s face can feel like an ambush. Those on the receiving end typically don’t respond well. “People are still wary of the algorithm entering their intimate lives,” Manning says. “There’s this authenticity question that we’re going to face as a culture.” When he asks his students how their friends or partners responded, they usually say: “Oh, he came up with excuses,” or “She just rolled her eyes.”

“It’s not really helping,” he says. “It’s just going to escalate the situation without any kind of resolution.”

What’s at stake

Outsourcing social tasks to AI is “deeply understandable,” Vasan says, “and deeply consequential.” It can support healthier communication, but it can also short-circuit emotional growth. On the more helpful side of things, she’s seen people with social anxiety finally ask someone on a date because Gemini helped them draft the message. Other times, people use it in the middle of an argument—not to prove they’re right, but to consider how the other person might be feeling, and to figure out how to say something in a way that will actually land.

“Instead of escalating into a fight or shutting down entirely, they’re using AI to step back and ask: ‘What’s really going on here? What does my partner need to hear? How can I express this without being hurtful?’” she says. In those cases, “It’s helping people break out of destructive communication patterns and build healthier dynamics with the people they love most.”

Yet that doesn’t account for the many potentially harmful ways people are using LLMs. “I see people who’ve become so dependent on AI-generated responses that they describe feeling like strangers in their own relationships,” Vasan says. “AI in our social lives is an amplifier: It can deepen connection, or it can hollow it out.” The same tool that helps someone communicate more thoughtfully, she says, can also help them avoid being emotionally present.

Plus, when you regularly rely on a chatbot as an arbiter or conversational crutch, it’s possible you’ll erode important skills like patience, listening, and compromise. People who use AI intensely or in a prolonged manner may find that the tool skews their social expectations, because they begin expecting immediate replies and 24/7 availability. “You have something that’s always going to answer you,” Wood says. “The chatbot is never going to cancel on you for going out to dinner. It’s never going to really push back on you, so that friction is gone.” Of course, friction is inevitable in even the healthiest relationships, so when people become used to the alternative, they can lose patience over the slightest inconvenience.

Then there’s the back-and-forth engagement that makes relationships work. If you grab lunch with a friend, you’ll probably take turns sharing stories and talking about your own lives. “However, the chatbot is never going to be, like, ‘Hey, hang on, Rachel, can I talk about me for a while?’” Wood says. “You don’t have to practice listening skills—that reciprocity is missing.” That imbalance can subtly recalibrate what people expect from real conversations.

Plus, every relationship requires compromise. When you spend too much time with a bot, that skill begins to atrophy, Wood says, because the interaction is entirely on the user’s terms. “The chatbot is never going to ask you to compromise, because it’s never going to say no to you,” she adds. “And life is full of no’s.”

The illusion of a second opinion

Researchers don’t yet have hard data that provides a sense of how outsourcing social tasks to AI affects relationship quality or overall well-being. “We as a field don’t have the science for it, but that doesn’t mean there’s nothing going on. It just means we haven’t measured it yet,” says Dr. Karthik V. Sarma, a health AI scientist and physician at the University of California, San Francisco, where he founded the AI in Mental Health Research Group. “In the absence of that, the old advice remains good for almost any use of almost anything: moderation and patterns are key.”

Greater AI literacy is essential, too, Sarma says. Many people use LLMs without understanding exactly how and why they respond in certain ways. Say, for example, you’re planning to propose to your partner, but you want to check-in with people close to you first to confirm it’s the right move. Your best friend’s opinion will be valuable, Sarma says. But if you ask the bot? Don’t put too much weight on its words. “The chatbot doesn’t have its own positionality at all,” Sarma says. “Because of the way technology works, it’s actually much more likely to become more of a reflection of your own positionality. Once you’ve molded it enough, of course it’s going to agree with you, because it’s kind of like another version of you. It’s more of a mirror.”

Looking ahead

When Pat Pataranutaporn thinks about the effects of long-term AI usage, his main question is this: Is it limiting our ability to express ourselves? Or does it help people express themselves better? As founding director of the cyborg psychology research group and co-director of MIT Media Lab’s Advancing Humans with AI research program, Pataranutaporn is interested in ways that people can use AI to promote human flourishing, pro-social interaction, and human-to-human interaction.

The goal is to use this technology to “help people be better, gain more agency, and feel that they’re in control of their lives,” he says, “rather than having technology constrain them like social media or previous technologies.”

In part, that means using AI to gain the skills or confidence to talk to people face-to-face, rather than allowing the tool to replace human relationships. You can also use LLMs to help finesse your ideas and take them to the next level, as opposed to substitutes for original thought. “The idea or intent needs to be very clear and strong at the beginning,” Pataranutaporn says. “And then maybe AI could help augment or enhance it.” Before asking ChatGPT to compose a Valentine’s Day love letter, he suggests asking yourself: What is your unique perspective that AI can help bring to fruition?

Of course, individual users are at the mercy of a bigger force: the companies that develop these tools. Exactly how people use AI tools, and whether they bolster or weaken relationships, hinges on tech companies making their platforms healthier, Vasan says. That means intentionally designing tools to strengthen human capacity, rather than quietly replacing it.

“We shouldn’t design AI to perform relationships for us—we should design it to strengthen our ability to have them,” she says. “The key question isn’t whether AI is involved. It’s whether it’s helping you show up more human or letting you hide. We’re running a massive uncontrolled experiment on human intimacy, and my concern isn’t that AI will make our messages better. It’s that we’ll forget what our own voice sounds like.”

https://time.com/7357217/ai-social-life-texting-chat-gpt-clause-gemini

Source: Cosmopolitan, Madeleine Frank Reeves
Photo: Julia Dufossé

But…it’s not as scary as it sounds? In the biggest game changer since dating apps first came around, AI is poised to upend how we match and meet. Here, your indispensable guide to wielding this latest wave of tech to your advantage.

But first, an answer to your big question….That question, of course, being, “Will AI fix dating?” Can it even? Because if there’s one thing anyone with a dating app and an interest in hooking up (in any way, short or long term) knows, it’s that this whole current situation is…not ideal. Frustrating at best. Painful or dangerous at worst. And yet we’re all fully indoctrinated, trying en masse to fulfill our romantic and sexual urges via swipe, speaking a dating language—full of breadcrumbing and ghosting and beige flags and GGGs—as if it’s the only way to communicate. Hell, complaining about it all has become a subculture of its own. So yeah, there’s room for improvement. And the companies that have been driving dating for the past decade are betting that that improvement is AI.

If you know where to look, the story of the revolution to come is clear: In August 2023, Match Group, owner of apps like Tinder, Hinge, and OkCupid, appointed a vice president of innovation to lead a team focused on AI. Bumble has launched multiple new machine-learning-powered features, including one that harnesses AI based on preferences and past matches to increase the likelihood of success. A sea of brand-new AI-powered apps (many of them in the stories you’ll see below) promises to perfect your dating profile, finesse your flirting game, and generally help you put your best digital foot forward. And then there are businesses like Replika unrolling AI bots capable of having full-on virtual romantic relationships with you.

So back to your question. Will any of this actually work? After six months of researching, analyzing, and, yes, dating using AI, we can report that in some cases, it already is working. And that in others, not so much. We can also report that daters are generally open to this next iteration of dating tech: A new Cosmopolitan-Bumble survey (keep scrolling to read all of our juicy survey findings) found that 69 percent of you are excited about the ways AI could make dating easier and more efficient. Sixty-eight percent think AI can help you feel more confident on the apps. Eighty-six percent believe it could help solve pervasive dating fatigue, and 67 percent believe it can make dating apps safer. (There are plenty of skeptics among you too, as is natural and warranted, because issues like bias, privacy concerns, and catfishing are real.)

The other crucial thing we uncovered: an urgent need for an all-in-one-place manual of sorts that dives deep into what exactly is out there right now, what’s coming next, how to think about it, and, most importantly, how to actually use AI to better your dating life. And so us being Cosmo—your always-expert guide to all things relationships and therefore morally obligated to get here first—we’re giving you that manual. The stories ahead are packed with tangible advice on navigating all this now and in the future. Because although “artificial intelligence” and “romance” may sound as incompatible as they come, there’s no stopping this takeover. As 72 percent of you reiterated, an AI-infused dating future is coming fast, whether we’re ready or not. So let’s be ready, okay?

Here’s what you really think about AI and dating…

This exclusive data throughout this story comes from a new survey conducted by Cosmopolitan and Bumble between November 24 and December 12, 2023. We polled 5,000 single and actively dating Gen Zers and millennials ages 18 to 42 on their thoughts, feelings, and behaviors around AI and dating.

71 percent of you would use AI to help create or optimize your dating app profile.

81 percent of you would rather ask AI than your friends for help choosing dating profile photos.

65 percent of Gen-Z and 66% of millennials would be open to taking dating advice from an AI bot.

78 percent of you would use an AI bot to help you flirt on a dating app. Broken down by age, that includes 81% of Gen Z and 76 percent of millennials.

71 percent of you say that using AI-generated photos of yourself doing things you’ve done or visiting places you’ve never been qualifies as catfishing.

81 percent of you would share your message history with an AI tool to help guide dating app convos. Broken down by gender, that includes 86% of men and 77% of women.

71 percent of you believe that there should be limits to using AI-generated profile pictures and bios on dating apps.

66 percent of you would use AI to help create or optimize your dating app profile.

58 percent of men and 57 percent of women would be okay with their partner using AI to do romantic things like write love letters or plan dates, but 59% of you say it would be a turn-off if a partner used AI for everything in your dating life.

Your top concerns when it comes to AI and dating apps are…

1. Losing the element of authenticity

2. The potential increase in catfishing

3. The loss of emotional connection

https://www.cosmopolitan.com/sex-love/a46574186/ai-dating/?utm_source=livingsimply.com

Source: Vox, Jonquilyn Hill
Photo: NurPhoto via Getty Images

The world is on the precipice of a technological revolution. But how much disruption can a society take?

When it comes to artificial intelligence, few fears loom larger than the idea of robots coming to take our jobs. But if you talk to the AI evangelists among us, that could be a good thing.

Not in the Elon Musk robots-will-babysit-your-kids way, but in a way that helps us make better use of our resources and handles our busy-work. If the doom doesn’t come to fruition — and that is a big if — we could get the one thing there never seems to be enough of: time.

There’s actually a name for this best-case scenario: AI abundance.

Here’s how Anton Korinek — an economics professor at the University of Virginia and one of Vox’s 2024 Future Perfect 50 — recently explained the idea to the host of Explain It to Me, Vox’s weekly call-in podcast: “AI abundance essentially carries the notion that we could all be so much more wealthier than we can even imagine today…AI and robots will be able to produce a lot more goods and services than when we have in today’s economy, and would make us an order of magnitude wealthier and better off.”

But what would a world without work look like? And what would need to happen for AI to free us from work and provide everyone with a good, universal living standard? We discuss that on the latest episode of Explain It to Me. Below is an excerpt of our conversation with Korinek, edited for length and clarity.

You can listen to the full episode on Apple Podcasts, Spotify, or wherever you get podcasts. If you’d like to submit a question, send an email to askvox@vox.com or call 1-800-618-8545.

We keep hearing that a change of this scale is unprecedented. Is that true or is it hype?

I think it’s the first time of this particular nature, but if you want to go into history and look for any parallels, I think the closest parallel would be the Industrial Revolution. So you would have to go back some 250 years for anything that comes even close to what we are about to experience this time.

What can the Industrial Revolution teach us about this particular moment?

From a big-picture economic perspective, you can say work as we have it today didn’t even really exist before the Industrial Revolution. Because before then, the most important factor of production was the land that people worked in order to produce the food that they needed. Then all of the sudden you had these new technologies that didn’t rely so much on land as they relied on machines. It started with spinning and weaving in the textile sector, but then soon we had the steam engine and electricity.

The new thing that you needed to produce — in addition to the labor that people had to put in — were machines that you could easily copy and reproduce. That meant that there was nothing holding back production. And that meant that we could suddenly produce a lot more because that bottleneck of land was overcome. In some sense, you can say that’s the main reason why today people in advanced economies are something like 20 times richer, on average, than they were before the Industrial Revolution.

What did that mean for workers at the time? I imagine that transition wasn’t easy.

It was actually quite disruptive. If you were an artisan weaver or something like that, if you were a skilled professional doing your trade, then all of a sudden you had these machines coming along that could do what you were doing, but at an order of magnitude cheaper.

So those artisans lost their livelihood essentially overnight, and they were impoverished. But looking at the positive side, their descendants lived in a world where they had cheap textiles and soon all other kinds of cheap industrial goods, and they lived to be much wealthier than their artisan parents or grandparents who lost their job in the first wave of the Industrial Revolution.

This can be hugely disruptive and painful for the individual. But if we have a little bit of social protection, we can mitigate the disruption and we can make sure that in the end everybody actually benefits. Now, if there is a lot of disruption all at once, then it may become a lot harder.

There are people now who lived through another, more recent technology disruption: I’m thinking about the ‘80s and ‘90s with computers.

In some ways, the way that I see the Industrial Revolution is that it first consisted of building machines that could automate a lot of our physical strength. And then since roughly the middle of the 20th century, we created machines that could automate cognitive tasks: computers.

Those first computers could only perform highly routinized things like adding up numbers in a spreadsheet, and that was very useful for businesses. We are seeing that AI can perform more and more of the complex, really thoughtful cognitive tasks. So the big question is where will this stop? And will they leave anything for us?

You talked about land being the bottleneck during the time of the Industrial Revolution. Do we have a bottleneck now?

I would say the most valuable resource in our economy today is our human capital. It is you and me and everybody [reading] this. Because if we can have more workers, then we can increase the amount that the economy is producing. We may enter a world where they can just press a button and have one more AI worker perform work on their behalf and essentially expand our economic opportunities.

When it comes to the AI revolution, is this something that’s going to benefit our grandkids more than us?

I very much hope that we can all benefit. But whether or not that’s going to happen is a story that is yet to be written, and it’s going to be challenging.

At first, there will be small sectors where people are losing out, and then there’s going to be a debate, “Well, why should we help them? We didn’t help other workers in previous technological revolutions that much.” Then, eventually, most people will be affected by this. But it’s not going to happen overnight. It’s going be a somewhat slow process.

We work to get a paycheck. In a future where we don’t work anymore, how do we eat? How do we get health insurance? How do we pay for a place to live?

That’s going to be the most important and also the most fundamental challenge to our current system. In some sense, you can say the Industrial Revolution accidentally created a system where our labor became more and more and more valuable because we were so scarce. That has kind of underpinned all this material progress, all this increase in wellbeing that we have seen over the past 250 years.

But once the AI revolution really hits, there is no guarantee that we can earn a decent living based on the value of our labor anymore. I do believe that we are going to need a new system of income distribution at that point. For example, Universal Basic Income, compute allotments: everybody essentially gets a certain amount of computational power allocated that they can then either use or sell off. People are also talking about job guarantees. There’s a whole range of options out there from a big picture perspective.

The primary concern has to be that we’ll find some solution because if labor does get significantly devalued by this technological change and at the same time we have much more abundance in the economy, it would be such a failure if we don’t use that additional abundance to make sure that nobody’s left behind.

This series was supported by a grant from Arnold Ventures. Vox had full discretion over the content of this reporting.

https://www.vox.com/explain-it-to-me/472177/artificial-intelligence-world-without-work-explain-it-to-me

Source: CNet, Katelyn Chedraoui
Photo: AI video tools make it harder than ever to determine what’s real. (Lily Hailyeh/CNET)

There’s no one foolproof way to tell if a video is real or made with Sora. But there are things you can look for to try and bolster your odds.

If you’re even a little bit online, the odds are you’ve seen an image or video that was AI-generated. I know I’ve been fooled before, like I was by that viral video of bunnies on a trampoline. But Sora is taking AI videos to a whole new level, making it more important than ever to know how to spot AI.

Sora is the sister app of ChatGPT, made by the same parent company, OpenAI. It’s named after its AI video generator, which launched in 2024. But it recently got a major overhaul with a new Sora 2 model, along with a brand-new social media app by the same name. The TikTok-like app went viral, with AI enthusiasts determined to hunt down invite codes. But it isn’t like any other social media platform. Everything you see on Sora is fake; all the videos are AI-generated. Using Sora is an AI deepfake fever dream: innocuous at first glance, with dangerous risks lurking just beneath the surface.

From a technical standpoint, Sora videos are impressive compared to competitors such as Midjourney’s V1 and Google’s Veo 3. Sora videos have high resolution, synchronized audio and surprising creativity. Sora’s most popular feature, dubbed “cameo,” lets you use other people’s likenesses and insert them into nearly any AI-generated scene. It’s an impressive tool, resulting in scarily realistic videos.

That’s why so many experts are concerned about Sora, which could make it easier than ever for anyone to create deepfakes, spread misinformation and blur the line between what’s real and what’s not. Public figures and celebrities are especially vulnerable to these potentially dangerous deepfakes, which is why unions like SAG-AFTRA pushed OpenAI to strengthen its guardrails.

Identifying AI content is an ongoing challenge for tech companies, social media platforms and all of us who use them. But it’s not totally hopeless. Here are some things to look out for to identify if a video was made using Sora.

Look for the Sora watermark

Every video made on the Sora iOS app includes a watermark when you download it. It’s the white Sora logo — a cloud icon — that bounces around the edges of the video. It’s similar to the way TikTok videos are watermarked.

Watermarking content is one of the biggest ways AI companies can visually help us spot AI-generated content. Google’s Gemini “nano banana” model, for example, automatically watermarks its images. Watermarks are great because they serve as a clear sign that the content was made with the help of AI.

AI Atlas

But watermarks aren’t perfect. For one, if the watermark is static (not moving), it can easily be cropped out. Even for moving watermarks like Sora’s, there are apps designed specifically to remove them, so watermarks alone can’t be fully trusted. When OpenAI CEO Sam Altman was asked about this, he said society will have to adapt to a world where anyone can create fake videos of anyone. Of course, prior to OpenAI’s Sora, there wasn’t a popular, easily accessible, no-skill-needed way to make those videos. But his argument raises a valid point about the need to rely on other methods to verify authenticity.

Check the metadata

I know, you’re probably thinking that there’s no way you’re going to check a video’s metadata to determine if it’s real. I understand where you’re coming from; it’s an extra step, and you might not know where to start. But it’s a great way to determine if a video was made with Sora, and it’s easier to do than you think.

Metadata is a collection of information automatically attached to a piece of content when it’s created. It gives you more insight into how an image or video was created. It can include the type of camera used to take a photo, the location, date and time a video was captured and the filename. Every photo and video has metadata, no matter whether it was human- or AI-created. And a lot of AI-created content will have content credentials that denote its AI origins, too.

OpenAI is part of the Coalition for Content Provenance and Authenticity, which, for you, means that Sora videos include C2PA metadata. You can use the Content Authenticity Initiative’s verification tool to check a video, image or document’s metadata. Here’s how. (The Content Authenticity Initiative is part of C2PA.)

How to check a photo, video or document’s metadata:

1. Navigate to this URL: https://verify.contentauthenticity.org/
2. Upload the file you want to check.
3. Click Open.
4. Check the information in the right-side panel. If it’s AI-generated, it should include that in the content summary section.

When you run a Sora video through this tool, it’ll say the video was “issued by OpenAI,” and will include the fact that it’s AI-generated. All Sora videos should contain these credentials that allow you to confirm that it was created with Sora.

This tool, like all AI detectors, isn’t perfect. There are a lot of ways AI videos can avoid detection. If you have other, non-Sora videos, they may not contain the necessary signals in the metadata for the tool to determine whether or not they’re AI-created. AI videos made with Midjourney, for example, don’t get flagged, as I confirmed in my testing. Even if the video was created by Sora, but then run through a third-party app (like a watermark removal one) and redownloaded, that makes it less likely the tool will flag it as AI.

Look for other AI labels and include your own

If you’re on one of Meta’s social media platforms, like Instagram or Facebook, you may get a little help determining whether something is AI. Meta has internal systems in place to help flag AI content and label it as such. These systems aren’t perfect, but you can clearly see the label for posts that have been flagged. TikTok and YouTube have similar policies for labelling AI content.

The only truly reliable way to know if something is AI-generated is if the creator discloses it. Many social media platforms now offer settings that let users label their posts as AI-generated. Even a simple credit or disclosure in your caption can go a long way to help everyone understand how something was created.

You know while you’re scrolling Sora that nothing is real. But once you leave the app and share AI-generated videos, it’s our collective responsibility to disclose how a video was created. As AI models like Sora continue to blur the line between reality and AI, it’s up to all of us to make it as clear as possible when something is real or AI.

Most importantly, remain vigilant

There’s no one foolproof method to accurately tell from a single glance if a video is real or AI. The best thing you can do to prevent yourself from being duped is to not automatically, unquestioningly believe everything you see online. Follow your gut instinct — if something feels unreal, it probably is. In these unprecedented, AI-slop-filled times, your best defense is to inspect the videos you’re watching more closely. Don’t just quickly glance and scroll away without thinking. Check for mangled text, disappearing objects and physics-defying motions. And don’t beat yourself up if you get fooled occasionally; even experts get it wrong.

(Disclosure: Ziff Davis, CNET’s parent company, in April filed a lawsuit against OpenAI, alleging it infringed Ziff Davis copyrights in training and operating its AI systems.)

https://www.cnet.com/tech/services-and-software/sora-changed-the-deepfake-game-can-you-tell-whether-a-video-is-real-or-ai

Source: Knowledge@Wharton, Jerry Wind, Mukul Pandya and Deborah Yao
Photo: Illustration of a robotic hand drawing the Mona Lisa on a blue background

In a new book, Wharton’s Jerry Wind and his co-authors argue that creativity is a learnable skill that becomes more powerful when paired with intelligent machines.

In an era where AI can write poetry, create marketing campaigns and out-analyze entire business teams, the question isn’t whether AI will change creativity — it already has. Creativity in the Age of AI: Toolkits for the Modern Mind, by Wharton marketing professor Jerry Wind, Mukul Pandya, and Deborah Yao, teaches professionals how to harness this shift to augment their skills and stay one step ahead of the technology. The authors argue that creativity isn’t in-born but a learnable skill that becomes more powerful when paired with intelligent machines. Those who learn to collaborate with AI will redefine what it means to imagine, invent, and lead. Following is an excerpt from the book.

Picture this: Your company is losing market share to a nimble startup that seemingly came out of nowhere. Your team is stuck in the same brainstorming loops, producing variations of familiar ideas. Meanwhile, your competitor is leveraging AI to innovate at unprecedented speed. What’s their edge? Creative thinking enhanced by AI.

Or imagine a visionary architect sketching a sustainable city, blending nature with urban life, and with AI assistance, innovative architectural concepts emerge in hours instead of months — living buildings that breathe, streets that generate energy, and communities designed for harmony with the environment. A scientist, driven by curiosity and powered by AI analysis, spots patterns in complex data that others overlooked, leading to a breakthrough in disease treatment. A musician experiments fearlessly, using AI to fuse sounds from different cultures and eras, birthing an entirely new genre that captivates millions.

This isn’t science fiction, it’s happening right now.

This perspective is based on our conviction that while not everyone can match the creative genius of Leonardo da Vinci or Thomas Edison, each of us can nurture and develop our own creativity if we build a toolkit of creativity approaches and enhance it with the use of AI.

The Creative Imperative in Business

In today’s rapidly evolving marketplace, creativity is more than simply a “nice-to- have”; it’s a matter of survival. McKinsey research shows that companies in the top quartile for innovation achieve 2.4x higher revenue growth. Meanwhile, 70% of executives report that their teams struggle with creative problem-solving. The gap between creative leaders and followers is widening dramatically.

Consider the evidence:

Organizations using systematic creativity approaches report 25% to 40% faster innovation cycles

Teams trained in morphological analysis generate 3x more viable solutions

Companies applying trend analysis techniques identify market opportunities 18 months ahead of competitors
Businesses that integrate AI-enhanced creativity see productivity gains

Yet most professionals have never been taught how to be systematically creative — until now.

Most professionals have never been taught how to be systematically creative — until now.

For Business Leaders and Professionals: Your Competitive Edge

Whether you’re a CEO navigating industry disruption, a product manager seeking breakthrough innovations, a consultant solving complex client challenges, or an entrepreneur building the next big thing, this book provides battle-tested approaches used by companies like Google, Tesla, Netflix, and Airbnb, with 12 creativity approaches that have been proven in boardrooms, innovation labs, and startup accelerators worldwide.

Professional Impact You’ll Achieve:

Lead more innovative teams that consistently outperform competitors

Identify market opportunities others miss through systematic trend analysis

Reduce time-to-solution for complex business challenges

Build a culture of innovation that attracts top talent

Leverage AI tools to speed and amplify your ideation and analysis capabilities

Transform meetings from time-wasters into breakthrough sessions

The AI Advantage: Your Creative Superpower

Today, we stand on the cusp of an unprecedented explosion in creativity in the age of AI. AI models such as ChatGPT and others act as intelligent collaborative tools that can serve as launchpads for further innovation. They can write, create images, compose music, craft videos, code, brainstorm, research, analyze, and more — capabilities that can supercharge a broad swath of industries. Now, there are AI agents that go beyond AI chatbots to complete multi-step tasks for you autonomously.

But here’s the crucial insight: AI doesn’t replace human creativity — it amplifies it exponentially. Learn to use ChatGPT for rapid prototyping, Claude for strategic analysis, or emerging AI tools for market research, competitive intelligence, and scenario planning. Transform hours of brainstorming into minutes of AI-enhanced ideation. The professionals and organizations mastering AI-human creative partnerships are pulling ahead at lightning speed. The question is: Will you be among them?

Proven Results From Real Organizations

The approaches have been adopted by organizations that created industry-altering solutions:

Netflix used trend analysis (Approach #7) to pivot from DVD rental to streaming, revolutionizing entertainment.
Tesla challenged mental models (Approach #1) to redefine the automotive industry and force every competitor to go electric.

Amazon’s customer obsession (Approach #7) and experimental culture (Approach #8), exemplifies transformation processes that generated hundreds of billions in value.

Airbnb applied morphological analysis (Approach #3) to disrupt the hospitality industry worth $600 billion.

Google built a culture of curiosity (Approach #9) that spawned breakthrough products from Search to Android to AI.
AI doesn’t replace human creativity — it amplifies it exponentially.

Historical Context: Why Creativity Matters More Than Ever

Creativity, as we understand it today, has relatively recent origins. MIT Technology Review’s examination of Samuel Franklin’s The Cult of Creativity reveals that our modern understanding emerged primarily after World War II in America.

Creativity became a response to society’s growing conformity and bureaucratization, providing what Franklin describes as “a way to unleash individualism within order, and revive the spirit of the lone inventor within the maze of the modern corporation.”

This historical perspective shows why creativity has become a fundamental value in contemporary society. Silicon Valley particularly exemplifies this trend, valuing creativity precisely because it combines novelty with utility — two elements highly prized in technology markets. As AI increasingly participates in creative processes, understanding this context becomes more relevant. Our definitions and practices of creativity continue to evolve alongside technological and social changes.

Break Free From Institutional Constraints

At this point, you might protest that you’re not the creative type: most of us aren’t Beethovens or Picassos. But you don’t have to be a prodigy to benefit from being dramatically more creative in everything you do, from solving everyday problems to developing breakthrough strategies.

Ironically, the institutions meant to encourage creative thinking are the same ones stifling its emergence. Schools focus on rote memorization and standardized tests, often neglecting creative thinking development. Students are rewarded for conformity and regurgitating information rather than original thought and problem-solving skills. Organizations inadvertently suppress creativity through rigid hierarchies, bureaucratic processes, and resistance to change.

These societal shackles leave us trapped in old mental models that influence how we interpret information, solve problems, and make decisions. These models create blind spots and restrict our thinking to conventional pathways that block innovative solutions.

But here’s the exciting news: Challenging these mental models is the first step to unlocking extraordinary creativity. By changing your mind, you can change your future.

Excerpted from Creativity in the Age of AI: Toolkits for the Modern Mind, by Jerry Wind, Mukul Pandya, and Deborah Yao. De Gruyter, 2025. Reprinted by permission of De Gruyter Brill.

https://knowledge.wharton.upenn.edu/article/creativity-in-the-age-of-ai

Source: Fast Company, Mark Price
Photo: Freepik

Put simply, happier teams are higher-performing teams.

We are living through an AI revolution. Boards are green-lighting pilots and buying AI licenses to maximize employee productivity. However, the most powerful performance lever in the modern workplace isn’t algorithmic, it’s human. When people are happier at work, they create, collaborate, and stay. When they aren’t, the best tech in the world won’t stop the value from leaking out of your organization.

Gallup estimates that low employee engagement drains $8.9 trillion from the global economy, roughly 9% of the world’s GDP. Engagement also slipped globally in 2024, a reminder that culture is moving in the wrong direction for many firms.

Happiness isn’t soft, it’s a productivity system that can be measured. A well-known Oxford study found that happier workers are 13% more productive, based on a six-month analysis of thousands of BT (British Telecommunications) contact-center employees.

And, at WorkL, the employee engagement platform I founded, drawing on millions of survey responses across more than 100 countries, we see a striking pattern: National workplace-happiness scores map closely to national productivity. Happier teams are higher-performing teams.

AI can shrink a task, but only people can grow a business. In organisations with high trust and a positive mental health culture, AI accelerates learning and frees time for higher-value work. In cultures defined by fear or fatigue, AI simply compresses the day, raises targets, and intensifies burnout. The sustainable edge therefore comes from engineering happiness first and then letting technology amplify it.

Consider the working week and how this can impact workplace happiness, productivity, and commercial success. In the UK’s four-day-week pilot, featuring 61 companies including 2,900 employees, firms reported a 35% average revenue increase, 57% lower attrition, and 92% intended to continue the model. There’s no doubt that considering employee happiness, will help boost the success of a business. I call it happy economics.

Six steps to workplace happiness and how to execute them

Leaders often ask me “Where do we start?” After decades of managing large teams and now measuring workplace experience at scale, I recommend my six steps to workplace happiness. These are business disciplines that both employers and employees should be following.

Reward and recognition

Pay must be fair and transparent, or nothing else lands. But don’t wait for annual reviews to say thank you. Build weekly recognition rituals tied to outcomes, not “presenteeism.” Managers should set and co-set clear goals with their teams so recognition feels earned and specific.

Information sharing

Lack of sharing breeds rumor and disengagement. Adopt a “show the work” cadence where a monthly all-hands meeting includes reviewing real metrics, a working roadmap, and team-level dashboard for all to see. When people understand context, customers, competitors, and constraints, they make better decisions without escalation.

Empowerment

Empowering employees means involving them in decision-making, valuing their ideas, and integrating their feedback into the company’s strategies. Everyone brings unique experiences and perspectives to the table, and only by considering all views can a team achieve the best possible outcome. While individuals may not be perfect, together, the team can be.

Well-being

Employee well-being encompasses physical, emotional, and financial health. Addressing all three areas leads to improved engagement and productivity. A positive workplace culture can reduce absenteeism, as engaged employees tend to be healthier and more committed.

Instilling pride

Employees who take pride in their work and workplace naturally become advocates, sharing their positive experiences with colleagues, potential hires, customers, and the community. Their pride will be evident when they talk about where they work. Building this sense of pride goes beyond motivational talks or performance reviews, it’s about cultivating an environment where employees truly enjoy and take pride in their roles.

Job satisfaction

A range of factors influence job satisfaction, but two stand out; opportunities for personal growth and the quality of the employee-manager relationship. Employees are an organisation’s greatest asset, and high engagement is essential for success. Research shows that respectful treatment and trust between employees and leadership are key drivers of satisfaction. Poor relationships with managers are often the top reason employees leave, regardless of the company’s brand strength.

What to do right now

If happiness is the revolution, implementation must be practical. Three moves any company can make immediately:

Set a happiness baseline. Run a brief, anonymous pulse survey covering the six steps above, and segment by team and manager. Commit to sharing the results and to two actions per team within 30 days. At WorkL we’ve seen that transparency alone lifts scores on information sharing and empowerment.

Redesign one work practice for time and trust. Kill or cap status meetings; publish written updates instead. Pilot “quiet hours” or no-meeting blocks.

Fund wellbeing like a growth initiative. Choose one high-impact intervention, manager mental-health training, access to counselling, and measure outcomes. The finance case is robust; employers typically recoup multiple dollars per dollar invested.

Now add technology back in. When teams are trusted, recognized, and resourced, AI becomes a force for good for the health of the business. Ways of working are adopted and kept because employees helped design them, reskilling lands because it’s wrapped in conversations with employees, and experimentation flourishes because failure isn’t punished. In unhappy cultures, by contrast, AI can magnify control and anxiety.

Leaders don’t have to choose between AI and happiness. Engineer happiness first, through reward, information, empowerment, well-being, pride, and job satisfaction, and then let AI amplify the human advantage you’ve built. That is the real workplace revolution. And it’s one you can start today.

ABOUT THE AUTHOR

Lord Mark Price is former UK Trade Minister, founder of happiness at work platform WorkL, and author of Work Happier: How to be Happy & Successful at Work, published by Kogan Page on September 30, 2025.

https://www.fastcompany.com/91395058/the-real-workplace-revolution-isnt-ai-its-human-happiness-workplace-happiness

Source: Mindstream, Matt V
Photo: Google Flights

Google wants AI to pick your next trip

Google is bringing AI into travel with a new experiment inside Google Flights.

The feature, called Flight Deals, is designed to help people find affordable trips without needing a fixed destination in mind.

Instead of entering a specific city, you can describe the type of trip you’re after, say, “a countryside weekend with kayaking” or “a European break with good wine in May.”

The AI then pulls together options that match your preferences.

The results can feel like a mix of the expected and the surprising.

Tropical searches bring up the usual choices like the Bahamas or Puerto Rico, but a query for “Europe with hiking” suggested places such as Cluj-Napoca in Romania and Ljubljana in Slovenia, spots you might not immediately think of.

That said, it doesn’t always get it right. A search for a short tropical trip from Orlando showed Miami and Key West, which isn’t quite what most people would expect.

Worth noting:

Trips can be searched by activities, flight duration, or general themes instead of fixed destinations.

Suggestions range from predictable hotspots to more unusual cities.

The beta launch is limited to the US and Canada for now.

And a cherry blossom trip to Japan left the AI with no results at all. Still, for travellers looking for inspiration and budget-friendly ideas, it could be a useful tool.

Flight Deals is currently rolling out in beta to users in the US and Canada, available on both the dedicated page and through Google Flights.

Google out here planning my chaotic getaway. Love that for me.

https://www.mindstream.news/p/google-wants-ai-to-pick-your-next-trip

Source: Fortune, Jessica Coacci
Photo: AI is attracting wealth faster than a ChatGPT search, bringing in record pace billion-dollar valuations, like Dario Amodei’s Anthropic. (Chesnot—Getty Images)

AI is minting billion-dollar startups faster than the dot-com era, with 100 unicorns born in the last two years, including OpenAI, Anthropic, and Scale AI. They join a total of nearly 500 AI companies with valuations of $1 billion or more, according to CB Insights. And the gold rush is far from over.

No longer do business leaders need to spend decades building the next big thing to join the ranks of Bill Gates, Mark Zuckerberg, and Jeff Bezos at the top of the billionaires club; they just need to build an AI company.

There are now some 498 AI unicorns, or private AI companies, valued at $1 billion or more, with a combined value of $2.7 trillion, according to CB Insights.

A complete 100 of them were founded since 2023. There are more than 1,300 AI startups with valuations of over $100 million.

Take Mira Murati, the former CTO of OpenAI, for example. Her startup, Thinking Machines Lab, has just closed a $2 billion seed round at a $12 billion valuation.

We’ve not seen a tech boom like this since the late 90s and early 2000s, which propelled many of the tech giants of today, from eBay to Google, into the mainstream. While the dot-com boom can’t be directly compared because the “unicorn” label didn’t exist then and billion-dollar private valuations weren’t tracked, AI is creating billionaires at a record pace—and could even ring in an era of trillionaires.

The AI billionaire boom

With a boom in company valuation also comes hefty paydays for its founders, investors, and C-suite.

In March, Bloomberg reported that four of the largest private AI companies, including OpenAI, Anthropic, Safe Superintelligence, and Anysphere, have created at least 15 billionaires with a combined net worth of $38 billion. More than a dozen unicorns have been crowned since then.

AI startups are receiving massive investments, resulting in high valuations and wealth for founders and early investors. According to data from Crunchbase, global venture funding in 2024 edged above 2023’s totals, with AI showing the biggest leap in amounts year-to-year.

For the founders of Anthropic, including CEO Dario Amodei, reports indicate the Claude chatbot maker is in talks to raise $5 billion at a valuation of $170 billion. Amodei’s net worth is now over the billion-dollar mark.

Also joining the billionaire club is Liang Wenfeng. The founder and CEO of Chinese AI company DeepSeek is likely worth over $1 billion based on the estimated value of the low-cost AI company.

And as investments into AI continue to boom, so do the net worths of billionaires working in them. Nvidia’s CFO Colette Kress and EVP Jay Puri have become billionaires, joining its CEO Jensen Huang after its market cap surpassed $4 trillion. Similarly, Palantir’s first billion-dollar quarter is dramatically increasing the wealth of the company’s cofounders and C-suite. Peter Thiel and Alex Karp have each seen their net worth jump by $17 billion collectively.

https://fortune.com/2025/08/13/ai-creating-billionaire-boom-record-pace-now-498-ai-unicorns-worth

Source: Dezeen, Saudatu Bah
Photo: Courtesy of LeafyPod

Technology brand LeafyPod has unveiled an AI-powered smart planter at this year’s Consumer Electronics Show (CES).

Made from durable plastic materials, the LeafyPod aims to address what the brand identifies as the four main causes of plant death: soil moisture, light, temperature, and humidity.

“The materials were chosen specifically for their resistance to water exposure and ability to maintain structural integrity over time”, Cleo Song, co-founder of LeafyPod, told Dezeen.

The device has sensors that detect light, humidity, and temperature and relay the data to the LeafyPod app.

“Our AI-powered watering system automatically adapts to each plant’s specific needs by monitoring environmental conditions and adjusting the watering schedule accordingly, ensuring optimal care regardless of the plant variety”, Song said.

The LeafyPod app works alongside the plant, learning its routine over time and automatically adjusting the watering schedule for optimised care.

“The planter’s clean, minimalistic design in classic white conceals its sophisticated technology – including multiple environmental sensors and watering systems”, Song continued.

Users can recharge the device, while a built-in water reservoir ensures the plants stay hydrated, even during extended trips.

“The app sends timely notifications for all maintenance needs, from water refills to filter cleaning or replacement”, Song said.

“The cordless design with USB charging capability further simplifies the user experience”.

The gadget can be voice-controlled by integrating it with smart devices like Alexa and Google Assistant.

The device features a dual-filter system, with a reusable filter on the pump that can be cleaned and a replaceable filter at the bottom of the transparent inner pot.

The LeafyPod also has an adaptive watering system that adjusts based on plant type and real-time environmental data.

“We designed the water tank to require refilling only once every two weeks to a month, optimizing water usage while maintaining plant health”, Song said.

“The system’s AI-driven approach helps prevent both overwatering and under-watering by continuously monitoring soil conditions and adjusting water delivery accordingly.”

Other devices showcased at this year’s CES fair include the Hormometer hormone testing kit and a solar-powered car.

https://www.dezeen.com/2025/01/17/leafypod-unveils-ai-powered-self-watering-smart-planter-at-ces