An Explosion of AI Slop Is Pushing People Offline and Back Into the Real World

There was a time, not so long ago, when the internet was a pretty fun—and useful—place. There was silliness aplenty, with sites like The Fish Doorbell. There were absolutely useless sites such as Zombo or The Useless Web that were still, somehow, fascinating. We came together watching iconic videos. And when there was a major news event, there was a wealth of coverage from both professional outlets and eyewitnesses. Today, though, people describe the internet with a word that would have seemed insane in those golden years: boring. It’s not that many of the oddities that made the internet so fun in the first place have vanished. It’s the things that have come since. AI slop and a perceived lack of creativity are turning more people away from the web and back towards the real world. A survey of 8,400 people across Europe, the U.S. and Latin America by ReverseLookup found that people are spending less leisure time online. Some 61 percent of the respondents said they want to spend more time in offline or local communities over the next year, while 44 percent said they are actively trying to reduce passive scrolling. It’s not that there’s less to do online. There’s more content today than ever. In just one second, an estimated six new websites go live, Redditors post 41 comments, Facebook users post more than 4,000 photos and there are 500 minutes of video uploaded to YouTube. The majority of that, though, is garbage. “For many users, [the] sense of discovery has weakened,” wrote ReverseLookup. “The internet has not become empty. It has become crowded with sameness.” When asked about the quality of online content today, 57 percent of the people surveyed said they now encounter more posts, images, captions, comments or articles that feel artificially generated or low-effort. And 49 percent said online spaces feel less original these days because of the continued spread of “synthetic content.” They’re bypassing AI and suspected-AI content, too. Some 42 percent said they have recently skipped or closed content because they suspected it was produced by AI instead of a person with something specific to say. They’re probably right. Earlier this month, Cloudflare reported the number of bots accessing websites outnumbered human web users for the first time. The trend has held, with 57.7 percent of web traffic coming from bots in the past seven days. That represents a turning point not only for web users, but for how businesses use the web to grow their business. “By 2030, the web as we know it will be dead,” says Rajiv Garg, a professor at Emory University’s Goizueta School of Business. “We’re moving from human-to-screen to machine-to-machine. It’s a total shift. … The value of local, unique data is about to skyrocket. The companies that win will be the ones holding the best raw ingredients for AI.” Of course, the internet isn’t going anywhere. It has woven itself into people’s lives and will remain essential for work, information, support, safety, and connection. But the growing abundance of slop and repetitive content is making more people think of the online world as less of a destination and more of a utility. They’ll still utilize it, but the fun factor that came with the internet less than 20 years ago has disappeared. And in its place is a more mundane and often divisive tundra. And that makes the real world a lot more interesting once again. “The offline revival is not a rejection of modern life,” wrote ReverseLookup. “It is a rejection of the parts of online life that have become predictable, performative and synthetic. Offline life is gaining value not because it is always more exciting, but because it is harder to mass-produce. For many people, the most interesting place left may be the one that does not ask them to scroll.” BY CHRIS MORRIS @MORRISATLARGE

Half of AI Job Cuts Will Be Reversed by 2027, Gartner Says. Here’s the Real Lesson

Half of the companies that cut workers for AI-related reasons will hire those roles back by 2027, according to Gartner. Forrester’s Predictions 2026 report had already documented the underlying cause: Fifty-five percent of employers who restructured for AI now regret the decision. The pattern points to a specific mistake. As I’ve explored before, the question of when to trust data versus judgment matters more than most executives acknowledge. The companies reversing course replaced jobs with AI that required human judgment and got information retrieval instead. Research into how AI is actually being used inside organizations shows that humans need to be in the loop when real judgment of tradeoffs is required. Don’t assume that because AI can access everything your people know, it can do everything people do. Those are two entirely different things. And that’s the leadership mistake underlying both the Gartner projection and the Forrester data. The Cost of Getting This Wrong Consider what it would mean to hire a surgeon who had only read surgery textbooks. The information is complete and the reading is thorough, yet the surgeon has never operated on anyone. You’d never hire that surgeon. But companies across industries made the equivalent decision when they replaced workers whose value came from having done the job under real pressure, thousands of times. Klarna ran this experiment at scale. In 2024, the Swedish fintech claimed its AI chatbot did the equivalent work of 700 customer service agents and projected tens of millions in savings. By May 2025, they publicly acknowledged that while automation takes on more of the high-volume, simpler queries, they still needed human agents equipped for complex, sensitive cases like fraud disputes, complex billing issues, and emotionally charged customer situations, a different profile than traditional outsourced support. They began directly hiring a small number of high-skilled humans into the customer service process to identify where the human touch brings the most value to customers. AI is indeed a transformative technology. People are scared it’s going to take their jobs. When jobs are lost to AI, it’s disruptive to the organization. But then to reverse course shortly thereafter, it creates a whipsaw effect that can have negative effects on the people who remain, and the culture. The Human Gaps in AI Technology AI can categorize problems and retrieve policies at speeds no human can match. Sitting with a frustrated customer, rebuilding trust after a systemic failure, and deciding in the moment that this person needs an exception are calls it has never made. The distance between those two categories is the same one that opened up when Klarna’s chatbot was given jobs that required having experienced something nuanced before and needing to draw on personal judgment about it. There’s a profound difference between reading about surgery a thousand times and having done surgery a thousand times. Same goes for customer service when it comes to upset customers. One produces knowledge, and the other requires judgment. Many organizations confuse the two. Three Things to Get Right The leaders closing this gap are deploying AI for what it’s built for and protecting the people who supply what it can’t access. Here’s what to do: Audit AI Capabilities. Ask honestly whether the roles you’ve automated require simple task execution, experience under pressure, or tradeoffs requiring judgment. Treat Experience as Infrastructure. The pattern recognition, institutional memory, and client trust carried by experienced workers are harder to rebuild than most leaders realize until those assets are gone. Design for Human-AI Teams. The most effective deployments use AI to process what’s routine and protect the people who handle what requires a depth of experience. What This Moment Is Really About Underneath the Gartner projection and the Forrester data is a deeper truth about what AI is and does. It’s the most powerful information system ever built, and information and judgment are different things entirely. AI has read everything. But it’s lived nothing, and providing it with “rules” that replace human judgment based on experience may not ever be feasible, or desired. The judgment behind a complex customer decision, a high-stakes negotiation, or a leadership call in the middle of a crisis comes from having navigated those situations before under real consequences. That lives in the kind of intelligence that only experience builds. EXPERT OPINION BY SOREN KAPLAN, WSJ BESTSELLING AUTHOR, KEYNOTE SPEAKER, AND LEADERSHIP STRATEGY ADVISOR

Why AI May Be the Best Thing to Happen to Creativity in Decades

There is a collective consensus, on my feeds at least, that AI is eroding creativity. But the people actually building with these tools in innovative ways are combating that messaging with their imagination. At Magnific’s annual Upscale Conference in San Francisco, they made that abundantly clear. I went into it curious, not knowing what to expect. I found a room full of people who weren’t replacing creativity with automation, but instead a gathering of entrepreneurs, filmmakers, and artists using these tools to make the most personal, ambitious work of their careers. The message to the doomsayers was consistent across every keynote: you’re not watching creativity die. You’re watching the gate come down. The system was always broken. Before diagnosing what AI is doing to the culture of creativity, it’s worth asking what it looked like before. Magnific co-founder Joaquín Cuenca had a clear answer. “The system, beautiful as it is, is kind of broken because so few people can enjoy working in that system,” he explained. Creative industries have always been denominated in years of training, proximity to the right institutions, and gatekeepers deciding whose vision was worth funding. Cuenca calls what’s emerging the “No-Collar Economy,” a third civilizational wave alongside the industrial and digital revolutions, except this one restructures who gets to participate in creative and entrepreneurial work entirely. “There are very, very few opportunities to really define history,” he said. “Very few breakthroughs that were so deep that didn’t change one job but changed one entire industry. It’s almost like you go from creating a company to creating an economy.” The entrepreneurial implication is enormous. When the cost of execution collapses, the only remaining differentiator is the specificity of what you have to say. Your story is your IP. Nobody on that stage understood this more viscerally than Momo Wang, animation director and founder of Bunny Galaxy. “When the tools are easy and cheap to access, nobody has to give up their dream anymore,” she reflected. “And when everybody has access to the same tool, the only thing that makes a difference is you. Every moment of your life, up and low, the happy ones, the painful ones, the embarrassing ones — every part of your life builds up your voice, your perspective, your story. And that’s something no tools can generate, and no prompts can replace.” History rhymes — if you’re listening Writer, director and head of AI and innovation at Echobend Pictures, Noah Wagner, titled his Upscale keynote Nothing Has Changed. He meant it as both provocation and thesis. “I keep thinking about the 1960s and 70s — the new Hollywood era — when the studio system was weakening and cheaper, more flexible production tools gave way to a new generation of exciting filmmakers like Scorsese, Coppola, Spielberg, Lucas, everyone with their own stories to tell,” he said. “History constantly rhymes if you listen for it.” In a follow-up conversation, Wagner pushed the idea further. “I try not to follow fads,” he shared. “I’m just old enough to have experienced some 20 and 30-year patterns where I’ve heard those rhymes.” Wagner read on the current moment isn’t fear but pattern recognition. The tools change, but the fundamentals don’t. “We can’t lose sight of the fact that we’re doing all of this for an audience of humans,” he encouraged. He went on to share that the meticulous human decision-making process about what to keep is where the art lives. “Intention is the difference between art and slop,” Wagner said. “In a world where there’s so much abundance, scarcity can be a superpower.” The person behind the prompt I told Cuenca that after the two days of keynotes, networking, and immersing myself in the vibrant community, the conference had made me look again at how we look at my own creativity through the lens of being a shadow artist, with instincts and references but always one step removed from making the thing itself. He didn’t flinch. “Your life is the most precious thing,” Cuenca concluded. “That’s the thing that separates artificial intelligence from human intelligence. We, as entities, live a set of experiences that are unique to us.” Then simply: “Your taste is your DNA.” Wagner, in our follow-up, put the uncertainty of this moment in perspective. “There’s a lot of uncertainty, but there’s a lot of possibility in that uncertainty,” he noted. The No-Collar Economy doesn’t promise ease, but it does provide unprecedented access and opportunity. The entrepreneurs who stay ahead will be those who understand that the tool is only as interesting as the person behind the prompt. EXPERT OPINION BY SOPHIE MEHARENNA, FOUNDER + NARRATIVE STRATEGIST, @WORDYSOPH

The Hidden AI Problem No One’s Talking About: It’s Destroying Customer Trust

AI is in nearly everything now. It’s easy to see some of the disruption this is causing, including the mass layoffs that continue to make the news. But there is an effect that AI is having in another area, too: consumer trust. As people see more AI in their everyday life, they may become less likely to immediately trust what they see, hear or read. Think about the last time you read a marketing message. Did you believe it at first sight? Or did you question things? More specifically, did you wonder if it was AI-generated? And if you did, when was the last time you thought that and ended up trusting what you were looking at? AI may be contributing to lower trust at first contact “Is this AI?” It’s a relevant question in 2026. It’s also a subtle yet important new part of the consumer filter. The simple act of asking whether something is AI, even if it isn’t, can reduce trust in what a person is seeing. The average person interacts with around 5,000 ads every day. That’s ten times the number of ads they had to sift through in the 1970s. Now, complicating this constant ad exposure is the fact that many of these ads are filled with AI-generated copy. They have photos, songs and videos that aren’t human — or at least aren’t fully human. This is because everything from visual clips to news stories to blog articles can easily be created and shared now at a fraction of the cost compared to traditional, human-made marketing assets. Complicating matters further, the multi-billion-dollar AI industry is working to make these AI look-alikes more sophisticated all the time. They are working to make AI-generated material more difficult for the general public to identify. This new reality raises the stakes for business owners, chief marketing officers and anyone trying to get a promotional message out there. Trust is no longer something companies can automatically count on simply by maintaining a strong product and good reviews. If you want a potential customer to notice you in the first place, you increasingly need to demonstrate value quickly. Trying to prove value in a trustless AI space AI is increasing the importance of trust. Companies need to think more carefully about how they can build trust with their target audiences. Traditionally, trust has come from some pretty basic activities. If you could maintain consistent brand messaging and be honest and transparent, over time, consumers would trust your brand. Now that AI can replicate many common marketing approaches, marketers need to be more deliberate about how they use their marketing assets to help build trust. One way to do this is by investing in resources that are less flashy and more substantial. BioStem Technologies is one example. The regenerative-medicine company openly addresses the scientific complexities behind its work. In fact, it has built entire pages on its website devoted to explaining the science behind its business philosophy. Other resource pages tackle deep, complex questions surrounding its products. Providing detailed information instead of relying primarily on broad marketing language signals to potential clients that the company has invested in its solutions. You can also demonstrate value that builds trust by showing your commitment to adhere to industry regulations. Companies already need to follow regulations. This shouldn’t be a back-room-only element of a business. Instead, companies should repurpose the effort they put into following regulations into their marketing, too. They can build consumer-friendly, customer-facing resources that are framed as a business code of conduct. These can share details about investments made to uphold ethical behavior or integrity in how a business operates day to day. Again, this can signal to clients that a business is not focused solely on revenue growth. There are real integrity boundaries in place. Creating accessible resources that demonstrate this investment without heavy legal jargon can help reassure customers and build trust alongside other marketing materials. Investing in trust in the AI era As consumers sift through a growing quantity of AI content, business leaders should recognize how valuable consumer trust has become. Marketing leaders must lean on less “thin” content and look for ways to build strong, substantial resources. These should go beyond marketing slogans and aim to demonstrate data-backed science and clearly defined company philosophies. If marketers can integrate these integrity-based elements into their strategies, they may be better positioned to build trust with customers as AI contributes to greater skepticism around content. EXPERT OPINION BY JOEL COMM, AUTHOR AND SPEAKER @JOELCOMM

20 Incredibly Useful Things You Didn’t Know Google’s Gemini AI Could Do

When we hear about Google’s Gemini AI engine these days, it’s almost always the result of some wildly ambitious and futuristic-sounding advancement. You don’t have to look far to find examples. Gemini, like other generative AI systems, is increasingly being positioned as an agent that can handle complex tasks for you, as we heard about throughout Google’s I/O conference keynote last week. They span everything from shopping and purchasing tickets to planning travel and even meandering around the web on your behalf. And, of course, there’s vibe-coding your own custom apps without needing to know a lick of code. That’s all well and good, but for most of us, it isn’t exactly the sort of stuff we’re relying on in day-to-day life. In reality, it’s Gemini’s more mundane and less marketing-worthy wizardry that’s likely to be most useful in an ordinary moment. And those are exactly the types of tricks that are underemphasized and go unnoticed—often because they’re off the beaten path and buried. So today, we’re going to skip over the standard superlatives and focus instead on the wow-worthy little gems lurking within Gemini that you don’t usually hear about and might otherwise never encounter. Check out the 20 truly useful Gemini abilities below and see how Google’s AI can actually help you. (Note that, Gemini, like all generative AI systems, can at times be inconsistent and may relay inaccurate info. The use cases I’m highlighting here generally minimize that risk and focus on more confined data sets and task-oriented missions that play to the technology’s strengths—but, as always, proceed with caution and approach all results with a critical eye. AI may be powerful, but the human touch around it very much still matters. And that part’s on you to provide.) 1. Act as your on-demand memory expansion Sometimes, the simplest feats really are the most valuable of all. The next time you find yourself facing some manner of random fact you need to remember—the name of someone’s partner or kids, the gate or door code at a particular place, the license plate on your vehicle or rental vehicle, or anything else imaginable—just tell Gemini: “Remember that Susan’s husband is named Carl.” “Remember that the gate code at Josh’s apartment is 8934.” And so on. Then, whenever you next need that nugget of info, all you’ve got to do is ask. 2. Set a timely reminder in no time Speaking of remembering, don’t forget that Gemini can also perform the simple but supremely useful task of helping you recall specific things at specific times—thanks to its native integration with the oft-forgotten Google Tasks service. No matter what device or interface you’re using, ask Gemini to remind you about anything at any date and time you want. It’ll set the reminder in Tasks and then pop up an alert when the right moment arrives. Just make sure you’ve got the Google Tasks app installed and set up on your phone—be it Android or iPhone—so you see the notification. 3. Help you find your way back anywhere One final reminder-related resource that’s worth tucking away in your memory bank—a two-parter: First, if you’re using the Gemini mobile app on a phone, make yourself a mental note that you can always ask Gemini the only slightly embarrassing question of “Where am I?” So long as you’ve allowed the app the proper location-sensing permissions, it should then tell you roughly where you are—with a city name and, depending on your whereabouts, also potentially the name of a specific business or address. Then, if it’s a place you want to remember for the future, ask Gemini to “remember that location as”—followed by whatever description you want (e.g., “remember that location as the best place to park in Westwood”). You can then ask Gemini for that info anytime down the road, and it’ll zap you right back to the spot you need. 4. Dig up details from a video You probably know that Gemini can summarize most any text you show it. One of its even more mind-blowing powers is its ability to summarize and analyze any video you feed into its metaphorical maw. Now, when you’re watching something for pleasure, this probably isn’t a power you’ll need. But when you encounter a video that you need to parse for purely informational purposes and you don’t feel like sitting through 22 minutes to get a shred of knowledge that’d take you 10 seconds to read, you can upload the video file or simply copy and paste its URL directly into Gemini—then tell Gemini to “summarize this video” or “give me a short bulleted summary of the high points.” If you’ve got something super-specific you’re seeking, you can also just ask Gemini about it: “What does this person say about battery life?” “Does the interview reveal anything about when the product will be released?” “What sort of screwdriver does this say to use for installation?” You get the idea. 5. Create your own personal podcast On the flip side of that last item, if you’ve got a dense document that you need to digest and you think you’d do better hearing it as a conversation, try uploading the doc into Gemini and asking it to “Generate a 10-minute conversational podcast between two experts discussing the findings.” You can get as nuanced as you want with your request, and Gemini should spit back out a personalized play-ready creation that’s ready for your aural consumption. 6. Skim over your emails Provided you’ve got Google’s Personal Intelligence option available and active, you can always ask Gemini to summarize your most recent incoming emails—or even get more specific. For example, you can ask it what the last email from your lawyer said, what your roofer quoted as the estimate for repairs, or anything else that might make sense for your inbox. 7. Find you a killer deal If you aren’t in a rush to make a purchase, try telling Gemini to monitor the price of a specific item and alert you if a certain kind of sale ever comes along. You can get as broad or as specific as you want with it: “Monitor the price of the Pixel 10 Pro and notify me if it goes on sale.” “Monitor the price of the Pixel 10 Pro on Amazon and notify me if it goes on sale.” “Monitor the price of the Pixel 10 Pro on Amazon and notify me if it drops below $900.” Your future self will thank you. 8. Create custom product comparisons All deal-seeking aside, Gemini can work wonders when it comes to comparing products and serving up exactly the info you need. Ask it to compare the battery life on two phone models you’re considering or to compare a series of specific refrigerators you see in a store and then tell you how they’re actually different—or even just to give you a table-style comparison of the most important differences across certain products from a purely practical perspective. 9. Decipher doctor-style handwriting Got a note that you can’t for the life of you read? Snap a pic of it and ask Gemini to decipher the writing. You’d be surprised how often it manages to interpret even the messiest script. 10. Act as your error-interpreting technician No matter the device or appliance, whenever you next encounter an error code that looks like gibberish, ask Gemini to help figure out what it means and how you can fix it. The more specific you can get, the better—telling it the manufacturer and model name of whatever’s giving you the error, for instance, or just showing it a picture—but even if you don’t know all the details, there’s a decent chance it’ll be able to point you in the right direction. 11. Serve as your handyman helper While we’re on the subject of repairs, you can show Gemini a photo of a random screw, connector, or component of any sort and ask what it’s called and where you can find a replacement—or anything else you might need to know. Whether you’re a seasoned repair pro or a befuddled homeowner with next to no handy knowledge, the answer it coughs back may be invaluable. 12. Parse an impossible document With the hopefully obvious caveat that you should absolutely consult with a lawyer for anything truly important and before making any consequential decisions, Gemini can be surprisingly helpful when it comes to going through dreadful-seeming documents filled with endless clauses and clusters of legalese. If nothing else, it can help you wrap your head around the info within and any sticking points you might want to mull over. For instance, I fed in an agreement for an upcoming bouncy-house rental for a kiddie (and, if I’m being fully honest, also adult) party we’re having in our backyard. Gemini identified a couple of potentially problematic and not-at-all-necessary sections that were easy enough to ask the vendor to remove. Similarly, I used it to compare a few vexingly similar insurance policies and translate the differences into real-world terms. For those sorts of scenarios or even as a pre-lawyer-meeting preparation, Gemini’s ability to ingest mountains of complex material and then identify and explain important points can be indispensable. 13. Become your manual magician Now that Google’s NotebookLM system is essentially integrated into Gemini, the feat I suggested in my recent collection of practical NotebookLM revelations can also apply to Gemini itself. That involves creating confined notebooks to hold specific manuals and then asking natural-language questions anytime there’s knowledge you need. I did this with the digital version of a manual for a recently acquired vehicle and was blown away by how much easier it became to find info simply by asking what a particular button does. The same strategy can work equally well with manuals for appliances, electronics, you name it. 14. Perform fast web fixes for you Human designers and developers are undeniably important when it comes to creating high-quality web work, but for those teensy little tweaks and frustrating fixes where you used to have to pester a professional, Gemini can now step in to help you come up with a correction—and help your coding-minded colleagues focus their time on higher-level concerns. Try showing Gemini a screenshot of a website you’re responsible for and then explaining what’s wrong or what you want to have changed, while providing any pertinent details about your setup—that you’re using WordPress with a particular theme, for instance—and see what it suggests. It can sometimes take several rounds of back-and-forth iteration, but if you’ve got the patience (and a solid staging site for low-risk experimentation), it can get you to the finish line much more easily than you’d expect. 15. Cook up some spreadsheet sorcery Speaking of coding chops, one area where specialized knowledge has traditionally been required is in the ever-confounding arena of spreadsheets. And while there’s certainly still a place for spreadsheet expertise, you can make your life a heck of a lot easier by letting Gemini guide you toward crafting complicated formulas. Just fire it up, explain what you want to have happen, and ask it to give you the formula you need—for Google Sheets, Microsoft Excel, or whatever specific program you’re using. Or, on the flip side, paste a formula you’ve found somewhere into Gemini and ask it to tell you what, exactly, it accomplishes. 16. Create custom Chrome extensions While full-fledged vibe coding can help you dream up all sorts of insanely customized complete programs, you might not be ready to take the plunge just yet. But you can dabble with the same sort of superpower and feel a sense of its addictive effects by asking Gemini to create a custom browser extension on your behalf. Unlike native applications, web-centric extensions require no compiling or separate steps beyond just taking a series of plain text files Gemini gives you and then plopping them into your browser. (It’ll even walk you through the exact process of doing that.) And with all the time you probably spend working on the web, you can accomplish some pretty spectacular stuff by doing that—like changing the appearance of web apps to better suit your preferences or giving yourself pop-up panels with simple tools you’ve never quite been able to find. It’s also incredibly fun and empowering to play around with—without requiring you to venture into exceptionally geeky waters. 17. Become your prompt-mastering guide Oftentimes, the biggest challenge with Gemini—or any AI chatbot—is figuring out the right approach for wording a request and getting the bot to do what you want. In an amusingly meta-twist, Gemini is actually quite good at advising you on the best way to phrase prompts for itself. The next time you’re struggling to get the service to do your bidding properly, consider asking it what the best prompt would be for the purpose you have in mind. It seems silly, but it often works astonishingly well. 18. Wear the hat of an AI detection agent In a similarly entertaining sense, Gemini is impressively effective at detecting images that were generated by Gemini—or another similar AI tool. It’s not foolproof, but it’s right up there with the best options we’ve got at the moment. If you’re ever trying to decide if an image is genuine or AI-generated, ask Gemini and see what it says. 19. Answer in whatever way you like Maybe you’re someone who prefers reading things in conversational paragraphs—or in short, succinct lists. Or maybe you like having a detailed, in-depth answer with a “TL;DR”-style summary at the start. Whatever the case may be, if you ask, Gemini shall oblige. Tell the service exactly how you prefer to have your info provided as part of your next prompt—or, if you want it to always follow a specific formula, tell it to always answer in that way, and it’ll adjust your account-wide preferences. You can also check any saved settings along those lines and modify them directly on the Gemini instructions page. 20. Transform into an entirely new personality Why stop at formatting? Gemini has the ability to completely adjust its personality and act in any way you want—again, either for a specific prompt or in a more generalized and ongoing sense. You could ask it to become a tough but supportive coach, for instance, or a lifelong friend who’s always brutally honest and direct with you. Or you could request it to take on the role of specific jobs, like a veteran software engineer, a travel agent, or a legal adviser—or even some combination of different identities. The possibilities are practically endless, and you never know what might resonate and prove to be useful until you try. By JR Raphael

AI Was Supposed to Replace Sales Teams. Here’s What’s Happening Instead

“Distribution is the new moat” is the hot new phrase in business circles. VCs are saying it. Consultants are saying it. Entire frameworks have been built around it. They’re right that distribution matters. They’re wrong about what distribution actually means. The popular argument goes something like this: AI has collapsed the cost of building software, so the only remaining advantage is to build an audience and get to those customers before a competitor. That’s the starting point. But it’s not a moat. Distribution is more than building an audience Anthropic, the mega-AI company behind Claude, has millions of social media followers and created one of the most viral products in history. Yet as of this writing, the most in-demand role at the company is… sales. You read that right. Anthropic is currently hiring more salespeople than engineers and product managers. The company that predicted AI would replace salespeople is now hiring hundreds of them. Here’s what Anthropic knows better than anyone: Building a viral product and massive audience is not the same as having a distribution moat. Real distribution muscle comes from the capacity to build relationships at scale, expand your footprint within organizations, and turn one-time customers into repeat business. In other words, real distribution muscle is built in the sales organization. The distribution moat is created through expansion and retention So, distribution is about landing new business? Yes, but that’s just the beginning. The real distribution moat starts to form when you have a system designed to retain and expand existing customers. Wasabi, a Boston-based cloud storage company, is a case study I’ve taught at Harvard Business School for years (full disclosure: I’m also on the board). They scaled from a few hundred thousand dollars in revenue to hundreds of millions. Their strategy? Good ol’ fashioned channel sales. Working with resellers is not sexy or on trend, but it’s one of the most durable distribution channels around. Resellers have relationships with the end users you want. You are creating essentially two layers of lock-in: One with the resellers and one with the resellers’ customers. Today, over 14,000 channel partners work hard to sell and expand Wasabi’s install base. But making this channel a success was not easy. Wasabi made two key changes: First, they aligned sales incentives to compensate their own salespeople for selling through channel partners. They created a special version of their product to encourage channel salespeople to sell Wasabi cloud storage over competing cloud and on premises storage. Channels sales reps started pushing Wasabi over Amazon cloud storage or EMC on premises storage. Second, they changed how they measured success. Onboarding channel partners is one thing. But could they actually sell the product? Wasabi decided on a KPI of “Time to Second Sale,” to measure and incentivize their top partners. Anyone can make one sale. The second sale is proof of a relationship. And relationships, not features, are what competitors can’t copy. Relationships—not distribution—are the real moat In the age of AI, everyone can build. But not everyone can sell, expand, and retain. Founders who treat distribution as audience-building are playing a different, shallower game than founders who treat it as relationship-building at scale. The moat isn’t how many people have heard of you. It’s how many people can’t imagine operating without you, because someone at your company took the time to understand their business, earn their trust, and keep showing up. AI can help you reach people faster. It cannot replace the human judgment, persistence, and relationship-building that turn a first sale into a second, a second into an expansion, and an expansion into infrastructure. Before you hire your next engineer, ask yourself: do you have the sales and customer success capacity to actually turn your distribution into a moat? BY LOU SHIPLEY, SENIOR LECTURER, HARVARD BUSINESS SCHOOL

Bots Now Outnumber Humans Online. Here’s What It Means for Your Business

It was only a matter of time before bots outnumbered humans on the internet, but many experts thought the flesh and blood majority would stand for a few more years. They were wrong—and the impact on business owners could be significant. New data from Cloudflare shows the number of bots accessing websites over the past seven days outnumbers human web users, with about 57 percent of web traffic coming from bots, who are busy browsing, querying, summarizing, shopping, researching, and scraping, increasingly via AI agents. “Welp, that happened faster than I predicted,” wrote Cloudflare CEO Matthew Prince in a social media post. “Thought it would be end of 2027, then early 2027, but agentic traffic [is] growing so fast that bots have now passed human traffic online for the first time in the internet’s history.” For business owners, that could mark the beginning of a new phase in how to handle business online. Instead of using the internet to attract human customers, it could be time to consider whether to structure your site to attract bots, say some experts. “Stop building for the human eye and start building for the machine mind,” says Rajiv Garg, a professor at Emory University’s Goizueta School of Business. “If an AI agent can’t read your data, you don’t exist.” The hurdle with that approach, though, is just as human visitors might either be customers or hackers looking for a weakness, not all bot traffic is the same. Some bots are malicious. Some are crawling for search engines. And some are sent from AI agents on behalf of potential customers. The challenge for businesses — and their tech teams — is figuring out which bots are which. “There is no protocol to verify whether an AI agent is acting on behalf of a real person, whether it has been authorized to perform its actions, or whether it is benign or hostile,” says Zach Meltzer, CEO and founder of Miami-based VeryAI, a ‘proof of reality’ platform designed to verify human identity and prevent AI-driven fraud. “Platforms cannot differentiate between a personal AI assistant booking a flight for its owner and a bot farm scraping data. The current workaround — forcing agents to impersonate humans via browser automation — is inefficient for legitimate agents and trivially bypassed by malicious ones.” There are also cost issues with bot traffic that business owners need to consider. Automated traffic can chew up bandwidth and impact analytics without generating any revenue. That could result in higher than expected bills, which could hurt the bottom line of companies that have smaller infrastructure budgets. While customer acquisition is expensive, human visitors are more likely to result in a sale, a subscription, or a viewing of content. Additionally, as bot visitors increase, it becomes more difficult for business owners to connect web traffic with customer demand. Garg suggests that the era of winning customers with creative web design is coming to a close, and future online iterations should move away from visual interfaces and more toward lean sites that emphasize behind-the-scenes data exchanges. “The internet is shifting from a destination [that] humans visit to an invisible infrastructure that AI agents navigate for us,” he says. “Your tech budget needs to shift from beautiful UIs to robust bot interfaces. Don’t build a better website. Build an MCP (Model Context Protocol) server that lets the AI ecosystem seamlessly transact with your business.” For instance, one SaaS company, Monday.com, has created an AI agent-only sign-up flow on its website. It employs a reverse CAPTCHA system that it says only AI can get through. That could increase your business’s chances of AI chatbots recommending your site to users, much like today’s search engines do. The shift from primarily human users to primarily bots is one experts have been predicting for quite some time. Automated traffic across the internet grew almost eight times faster than human activity in 2025, according to the 2026 State of AI Traffic report from cybersecurity firm Human Security. Cloudflare calls it the next phase of the internet’s evolution, but cautions that it will create challenges that current IT infrastructure and cybersecurity were not designed to handle. “IT leaders now face fundamental questions about trust, visibility, and control that traditional architectures can’t answer,” the company said in a blog post. “The organizations that recognize this shift — and redesign their infrastructure accordingly — will shape how the internet evolves. Those that don’t will find themselves constantly outmaneuvered.” BY CHRIS MORRIS @MORRISATLARGE

The Flaws in Mass Layoffs for AI Productivity Are Beyond Obvious Now

Just when I thought I was done calling out tech CEOs for horrible mass layoff decisions, one of those CEOs doubles down on the mass layoff rhetoric. So here’s what we’re gonna do. You know how, when your mom or dad tried to give you solid life advice that just didn’t stick, they ended up sitting you down and listing out the flaws in your reasoning one by one? Well, sit down, kid. And like I tell all my kids: Look, I’m gonna yell at all of you, but I’m really only yelling at one of you. You’ll quickly figure out if you’re the one I’m actually yelling at, but it’s not gonna hurt any of you to hear what I have to say. This Could Be Any Corporate Tech CEO My opening histrionics aside, I want to make it clear that I’m not really trying to smack anyone individually. What I’m about to criticize is not the work of a single misguided leader, it’s the culmination of a spreading misguided follow-on leadership strategy. I also want to apologize if any of this comes off as flaming the writer or the publication behind the article I’m going to use as an example, because it literally could have been any tech CEO speaking to any publication after cutting double-digit percentages of their workforce and being all super-pumped about the future. It is such a bad look, so good job exposing it. But I guess we’re all numb to it now, when we read things like: “What [tech company’s] mass layoff tells us about the future of work” I encourage you to read the article. Go ahead and give the author some respectful clicks, because they get it right at the end, with facts. But ultimately you don’t have to read it because I’m about to take apart the “fire-all-the-humans-and-replace-them-with-AI” strategy point by point. This Isn’t a New or Novel Strategy Let’s start at the top: “Zeb Evans, CEO of the collaboration software startup ClickUp, claims that this shift is imminent. Last Thursday, Evans announced on X that the company, which was last valued in 2021 at $4 billion, had laid off 22% of its workforce.” A couple of things are quickly evident. First, this appears to be the same “everybody’s gonna eventually do it” reasoning that Jack Dorsey used when Block laid off 4,000 people just a couple months ago. Second, it’s not a coincidence that the company was last valued in 2021 at $4 billion or that that might have been its peak. 2021 was the acceleration point of the Great Labor Arms Race, and Corporate Tech companies across the industry started hiring people ill-equipped for poorly-defined roles at salaries that would have broken the bank if money wasn’t so cheap—or even free, via automatically forgiven loans. But the pretzel logic that gets used here is what makes this follow-on strategy especially obtuse. When Cutting Costs Isn’t Cost-Cutting The CEO “characterized that reduction as not a cost-cutting measure, but rather a radical embrace of AI that will propel the company to the next level.” Quick question: When is cutting 22 percent of your labor costs not a cost-cutting measure? I’ll just let that one hang. I’m not a mean person, really. The Biggest Mistake a CEO Can Make “‘Most savings from this change will flow directly back into the people who stay. We’ll be introducing million-dollar salary bands. If you create outsized impact using AI, you’ll be paid outside of traditional bands,’ Evans wrote.” One of the best lessons a mentor ever gave me about leadership is: The worst mistake a leader can make is looking at a chart that goes up and to the right and believing that chart will always go up and to the right. It never works out that way, but the temptation to think it will is always there. Using my mentor’s advice, I have several questions: Is this CEO talking about paying a percentage of profits based on whatever metrics they invent to show “outsized impact created by using AI”? Does the CEO plan to keep paying that employee their $1-million salary when the “outsized impact created using AI” returns to the mean? Quick follow up: Does that keep going until it breaks the budget or is this just, like, an MLM thing? If not, and the CEO does the sensible thing that every other company in the history of companies has called “commission,” won’t that employee just hop to the next company when that company offers them a $1-million salary to do what they just did? And then finally, let’s do the cut-throat AI thing that serves as the reason for the 22 percent “savings” in human labor: Once that “outsized impact created by using AI” materializes, why do you still need that employee? Especially if you’re now paying them a million-dollar salary? Isn’t that more “savings” just waiting to be “saved”? Making a Fortune Babysitting That last question kind of introduces another question: What are we paying these employees a $1-million salary for? “ClickUp recently introduced roughly 3,000 internal AI agents to handle a wide range of complex tasks on behalf of its employees…. Instead of performing the work themselves, staff members are now expected to direct these agents and ultimately review the output to ensure it meets the company’s standards.” Are we planning on paying million-dollar salaries to babysit agents? Because the last year has shown us that’s not where the seven-and-eight figure salaries are going. The 100x Productivity Myth “Evans’s goal, according to his X post, is for AI to turbocharge ClickUp into a ‘100x org.’” I’ve been on the AI front for over 16 years, and I get called a “100x guy” or a “10x guy” a lot. I don’t know what that means, but it sounds cool so I just smile and say thank you and get back to the data. Actually, I do know what it means, in another context, because I’ve spent my entire career as an entrepreneur and/or consultant, and have worked with a vast array of venture capital and private equity firms and their strategies. One of those strategies, familiar to everyone, is to create ROI by what I’m going to dub “numerator-maxxing” (see, I can make up buzzwords too). The strategy starts out logical enough. The company that the firm is investing in is doing something very right. Their numerator—the value that the company is generating—is a lot higher than their denominator—the money and sweat effort and brainpower being put into the company. The firm believes that the company’s numerator is artificially low and is being constrained by a weak denominator. So the firm dumps a bunch of money into the denominator. That’s their bet. When this happens, the numerator almost always increases. Where it goes wrong is when, a couple years into it, the numerator has not increased by orders of magnitude to compensate for being weighted down by a heavy denominator. One hundred over 10 is a much bigger number than 1,000 over 1,000,000. Sorry for the math. So yeah. Machines are less weight in the denominator than humans, and you can also add exponentially more of them to the denominator without it getting much heavier. But what do they add to the freaking numerator? Where AI and agent productivity is concerned, no one—no one—is looking at the numerator. Well, no, wait. Gartner took a look. Vindication Isn’t What It Used to Be Like I said, the writer gets a lot right at the end, and does it without my cartoonish fist shaking. In response to the metric most commonly used to measure that “outsized AI impact”: “[C]ritics argue that “tokenmaxxing”—as this concept is known—is the wrong metric because it simply racks up AI expenses.” In response to the company’s incredibly circular claim that people who automate their jobs with AI will always have a job: “But if AI keeps taking over more tasks, ClickUp will eventually need fewer and fewer people.” However, the most damning truth came from a quick mention of a quiet study from Gartner on ROI from AI-as-labor-replacement, just three weeks ago, from which I wish the writer had pull-quoted: “Many CEOs turn to layoffs to demonstrate quick AI returns; however, this disposition is misplaced,” said Helen Poitevin, Distinguished VP Analyst at Gartner. “Workforce reductions may create budget room, but they do not create return. Organizations that improve ROI are not those that eliminate the need for people, but those that amplify them by aggressively investing more in skills, roles and operating models that allow humans to guide and scale autonomous systems.” Am I still Don Quixote for screaming about this for the last 16 years? In fact, I said the same thing yesterday when highlighting the unintended consequences of this misguided follow-on leadership strategy, and it still feels like the loud part being said far too quietly. It will always be the humans behind the tech that will make the tech successful—not the babysitters, not gamification, not agentmaxxing, tokenmaxxing, or numerator-maxxing. So if any of those leaders see this rhetoric and still believe these mass layoffs are about AI and not about mistakes made by leadership a few years ago in hiring the wrong people for roles that were never clearly defined at salaries that never should have been offered, I’m begging you, think twice before you agentmaxx. The flaws are now obvious and documented. There is nowhere left to hide. EXPERT OPINION BY JOE PROCOPIO, FOUNDER, JOEPROCOPIO.COM @JPROCO

Anthropic suspends all access to Mythos model after US government bans foreign nationals use

AI company Anthropic has disabled customer access to its most capable systems after the US government ordered it to suspend all use by foreign nationals, Anthropic said in a statement Friday evening. The move is the latest in a series of adverse Trump administration actions targeting the company. The broad directive to Anthropic’s Mythos 5 and Fable 5 models is one of the furthest-reaching actions the government has taken in response to the advanced capabilities of an AI model. Anthropic said the US government gave it the directive, citing “national security” issues. The company said the government didn’t provide specific details about the national security concerns, though it believed the government had “become aware” of a method of “jailbreaking” Fable 5, or getting around its internal safety guardrails. “We reviewed a demonstration of this specific technique being used to identify a small number of previously known, minor vulnerabilities,” Anthropic said in its statement. “These vulnerabilities all appear relatively simple, and we have found that other publicly-available models are able to discover them as well without requiring a bypass.” Anthropic said it had instituted several safeguards for its newest models to “greatly reduce the likelihood” that they are “misused for tasks related to cybersecurity,” noting they’ve received complaints from users about those guardrails being too strict. Anthropic also noted it has worked with the US government to “red team” Fable’s safeguards and that no model is completely resistant to any jailbreak. Anthropic said that while they are complying with the directive and removing access to the models for everyone, “we disagree that the finding of a narrow potential jailbreak should be cause for recalling a commercial model deployed to hundreds of millions of people.” “If this standard was applied across the industry, we believe it would essentially halt all new model deployments for all frontier model providers,” the company added. The restriction means that many foreign nationals working for Anthropic will not be able to touch those models. The Commerce Department, which issued the restriction, did not immediately respond to a request for comment. Axios reported the government’s directive would require Anthropic to obtain a license “for the export, re-export or domestic transfer of those Anthropic models.” Anthropic’s newest model, Mythos, has spooked the US government and Wall Street with its capabilities, which experts say can exploit cybersecurity vulnerabilities at an unprecedented pace. The model was seen as so capable, Anthropic initially limited its release to a group of key partners in order “to secure the world’s most critical software.” Anthropic released Fable 5 last week as a version of Mythos that is safe for general use. The model also helped spark the Trump administration’s recent executive order on AI, which asks companies to voluntarily share new models deemed to have advanced cyber capabilities with the government up to 30 days before providing access to other partners. One source with knowledge of early discussions of the executive order said the idea of banning foreign nationals from working on such models had been floated for that order, but the idea never made it into a draft. The government has had a complicated relationship with Anthropic. Earlier this year, the Trump administration blacklisted the company, declaring it a “supply chain risk” in military dealings over Anthropic’s insistence that the Pentagon include certain safety guardrails for the government’s use of AI in warfare. Anthropic sued the government over the designation as “unprecedented and unlawful” and notched at least one early win in the ongoing case. Despite President Donald Trump’s directive at the time of the designation for all of the federal government to cease working with Anthropic products, the White House has stayed in close touch with the company, and some parts of the federal government have found a workaround to continue accessing Anthropic’s models, especially after the release of Mythos. Anthropic was also deeply involved in helping draft the latest executive order, sources familiar with the situation told CNN, and its executives had been invited to the White House for a signing ceremony that was ultimately canceled at the last minute. By Hadas Gold

AI Is Wreaking Havoc at Starbucks and Pizza Hut. Social Media Is Having a Field Day

AI woes are coming for the food service industry, and social media can’t help but celebrate. This week, both Starbucks and Pizza Hut made headlines for negative news about their internal applications of artificial intelligence. At Starbucks, an inventory tool got the chop after making frequent counting mistakes, while at Pizza Hut, a delivery tool drove a franchisee to file a lawsuit. Social media users are saying the two stories may point to a larger trend—that for the first time in the AI era, more companies will pull away from AI than embrace it. Starbucks walks back an AI tool On Monday, Starbucks told employees it was retiring an inventory-counting tool powered by AI after the technology led to inaccurate counts and mislabeled products. “Starting today, Automated Counting will be retired,” said an internal company newsletter verified by Reuters. “Beverage components and milk will now be counted the same way you count other inventory categories in your coffeehouse.” In a statement to Fast Company, a spokesperson for Starbucks explained that the company’s choice to axe its Automated Counting tool is in line with its larger AI strategy, which is based on trial and error. “We test ideas in our coffeehouses, listen closely to partner feedback, and make changes to deliver a better, more consistent experience.” Starbucks’s move to ditch one AI tool doesn’t mean the company is forgoing the technology entirely. The company is still investing in internal AI applications, including an AI assistant for baristas called Green Dot Assist and an AI-powered order-sequencing system called Smart Queue. The brand is also experimenting with an integrated Starbucks app within ChatGPT. Pizza Hut’s delivery system backfires Where Starbucks’s choice to nix its AI tool came from the top down, the anti-AI sentiment at Pizza Hut started with a disgruntled franchisee. In a lawsuit filed on May 6, franchisee Chaac Pizza Northeast, which operates more than 100 Pizza Hut locations, alleged that the company forced it to adopt an AI tool called Dragontail, which inadvertently pushed average wait times from under 30 minutes to over 45 minutes in more than half of all orders. The complaint explained that the issue wasn’t with Dragontail itself, but with the information the tool provided to DoorDash drivers. Dragontail is meant to optimize food delivery by giving delivery drivers real-time updates on order preparations and timing. But according to the lawsuit, its implementation in 2024 caused “cascading operational breakdowns and customer dissatisfaction,” resulting in more than an estimated $100 million in lost business and enterprise value. Reportedly, once DoorDash drivers could see the real-time status of multiple orders through Dragontail, they would wait inside restaurants until multiple orders were ready, meaning some orders were being held for up to 15 minutes after they were ready for delivery. Because Chaac Pizza Northeast relies on DoorDash for all of its deliveries, the franchisee alleged that the forced change to its delivery model had a major impact on its sales. At its New York City locations, Chaac said its sales swung from positive 10.19% to negative 9.78% after implementing Dragontail. “With the intention to improve efficiency and service to the customer, Dragontail did the exact opposite,” the lawsuit stated. “It caused significant delays and pummeled consumer satisfaction.” Pizza Hut has not responded to Fast Company’s request for comment. Social media sees a trend With the stories from Starbucks and Pizza Hut breaking in quick succession, social media users are drawing connections between the two food service chains’ AI troubles. “Over the next 1-2 years we’re going to start hearing more reports about companies pulling back from AI than adopting AI, and markets aren’t ready,” one X user theorized. “The AI bubble might burst quicker than I thought,” echoed another. “You’re going to be hearing a lot more about forced AI integration and what a disaster it is for businesses and consumers,” a third user agreed. Other users pointed out that all of these problems could have been avoided if tasks hadn’t incorporated AI in the first place. “To err is human,” one person quipped, “but to really screw things up, you need a computer.” By Jude Cramer

Instagram’s AI Support Bot Made a Costly Mistake. It’s a Warning for Every Company

Sometime last weekend, hackers asked Meta’s AI support bot for access to someone else’s Instagram account. The bot said yes. The method, reported first by 404 Media, was almost insultingly straightforward: instruct the chatbot to add a new contact email to a victim’s account, confirm the change with a code sent to that email, then use it to reset the password. In some cases, all that was also needed was a VPN to spoof the victim’s location. Among the accounts taken over: the former White House page from Barack Obamaʼs presidency, cosmetic chain Sephora, and the chief master sergeant of the U.S. Space Force. While this hack was obviously a security flaw, most businesses should consider that this blunder also reveals a management error. The front door is now automated AI customer service is everywhere. According to MarketsandMarkets, the global AI customer service market was valued at $12.06 billion in 2024 and is projected to reach $47.82 billion by 2030, growing at a compound annual growth rate of around 25.8 percent. The economics are hard to argue with: AI scales cheaply, doesn’t require shift management, and doesn’t call in sick. AI has been shown to cut response times by 37 percent and reduce operational costs by 35 percent. Companies have moved quickly. Banks use it for dispute resolution, airlines use it for rebooking, telecoms route complaints through it, and e-commerce platforms use it to handle returns. Around 80 percent of companies are either currently using or planning to adopt AI-powered chatbots for customer service by 2025. Meta is not unusual for deploying AI support at scale. When Meta launched its AI support assistant in March, it was presented as a way to help users reset passwords, regain account access, and report problematic content. These are not trivial tasks. Account recovery involves identity, security, and trust—the kind of territory that, not long ago, companies deliberately kept behind a human review process because the consequences of getting it wrong were considered too serious to automate away. Meta has also reassigned thousands of employees into AI-related roles and used AI to automate risk assessments of updates, safety features, and content moderation—all of which are tasks that previously required human review. Therefore, the support bot exploit arrived in an organization that had been replacing human judgment with automated processes across multiple functions simultaneously. Authority without judgement The exploit worked not because the AI behaved unpredictably, but because the AI behaved more or less as it was designed. A user asked it to update a contact email, and it updated the contact email. The system executed a process it was authorized to execute, but in doing so, handed a hacker the keys. This distinction matters enormously for anyone responsible for deploying AI systems. Authority can be automated, but judgment is a different problem entirely. A junior employee in a similar situation might also make a bad call. Humans fail too, but organizations know how to supervise, train, audit, and escalate human decisions. Real people typically offer something an AI system can’t: the ability to notice that something feels off. In this case, hesitation at an unusual request, the instinct to double-check account history, and the recognition that a request arriving via VPN from an unfamiliar location (asking to change contact details on a high-profile account), warrants a pause that could have prevented disaster. Gartner forecasted that 20 to 30 percent of businesses will replace human customer service agents with AI by 2026. The efficiency case for doing so is well established, but what’s less well examined is the category of decisions that look like processes but aren’t. Account recovery looks like a process, but embedded within that process is a judgment call: Is this request legitimate? Humans often make that call poorly too. The difference is that when a human makes it poorly, the failure is legible. There’s accountability. There’s someone to fire. Victims of the Instagram account takeovers told 404 Media there was no way to escalate their problem and speak to an actual human. Historically, high-stakes support requests — account recovery, fraud disputes, identity verification — were escalated to human agents because the potential for harm was too high to leave it to a scripted response. The escalation path was a precaution for the edge cases that automated systems weren’t designed to handle. Research published in the Journal of Consumer Research found that customers evaluate service provided by bots less favorably than identical service provided by humans, partly because they perceive automation as the firm cutting costs at the customer’s expense. That perception hardens quickly when customers discover there’s no human available at all. The harder problem The lesson here isn’t that companies shouldn’t deploy AI in customer service, but the quality of the decisions being made around where AI gets authority and what happens when it exercises that authority incorrectly. The questions that matter aren’t technical; they’re structural. What decisions can AI make autonomously, and which ones require a human to sign off? What triggers an escalation, and who owns it? When the AI gets something wrong — not if, but when — can a customer reach someone who can fix it? Gartner concluded in mid-2025 that half of the organizations expecting to significantly reduce customer service headcount because of AI would abandon those plans by 2027, and that 95 percent of service leaders planned to retain human agents in a digital-first but not digital-only model. The companies that arrived at that conclusion before Meta’s incident are in a better position than the ones who’ll arrive at it after. The Instagram story will probably be remembered as an AI security vulnerability, and will likely get fixed as one. As of June 3, it reportedly still hadn’t been patched. As companies race to automate customer interactions in pursuit of lower costs and faster resolution times, they’re discovering that it’s far easier to reduce the cost of executing a decision than it is to replace the judgment behind it. With better training, retrieval-augmented verification, anomaly detection for suspicious requests, and well-designed human-in-the-loop escalation, AI systems may be able to take on increasingly sophisticated judgment-like tasks over time. But deciding which requests deserve more scrutiny than the process allows remains, stubbornly, a human problem for now. AI can execute authority at scale, but the question that the Instagram incident forces into the open is a simpler one: When it gets things wrong, who’s responsible? Right now, the answer at too many companies seems to be nobody. BY CONNOR JEWISS

How to AI-proof your job

Meta. Nike. Intuit. UPS. It seems every day a new company announces layoffs, often citing AI as the cause. AI is already reducing US monthly payroll growth by roughly 16,000 jobs in the past year, according to a recent Goldman Sachs report. Knowledge workers face the sharpest exposure, as their output is exactly what AI replicates best, at superhuman speed, around the clock. “The most valuable jobs, the ones that we tell people to go to school for – software engineer, finance professional, accountant, lawyer – a lot of these cognitive professions, those are the ones that are the most vulnerable… to AI automation,” David Shrier, professor of AI & Innovation at Imperial College London, told CNN. But humans will always be needed in some form – and there are steps you can take to increase the chances you’ll protect your own job. Audit your role Before you can future-proof your career, you need a clear-eyed view of what you do in your job. Think of jobs as a “collection of tasks we switch between, often many times a day,” Oded Nov, a professor of technology management at New York University, told CNN. Consider which of those tasks are the most repeatable, rule-based computer tasks, like processing expense reports, which takes raw data and converts it into a different form. The more predictable a function, the more vulnerable it is to automation. The CEO of Cloudflare wrote in an opinion piece for the Wall Street Journal that he recently laid off 20% of his work force, focusing on “measurers”: middle management and those who work on audits, operations, compliance, etc. “AI isn’t coming for builders or sellers, but it is coming for measurers,” he wrote. “Tireless, independent, efficient and available, AI systems can now measure an organization with a level of objective detail and precision that was previously impossible even for the best employees.” Some jobs, such as those in hospitality, healthcare and skilled trades, still need someone physically present to do much of the work. Robotics is at least a decade away from replacing those roles. Invest in skills that are structurally hard to automate After your self-audit, focus on skills that are not repeatable, predictable and rule based. In addition to physical duties, AI is not yet as good at handling tasks that require emotional and social awareness, such as “understanding organizational culture or group dynamics,” Nov said. AI tends to be recursive, rather than inventive or creative. “AI is bad at creativity, but it’s surprisingly good at elaborating on creative prompts,” Shrier said. “But you still need the human to come up with the idea and guide the AI to do something interesting.” Invest in those skills. If part of your job involves sales and convincing people to sign a contract, focus on the interpersonal skills that help you build trust with clients. Customers might go to AI to research, but they usually still want to deal with a human being when making big purchases. Embrace AI and learn how to make it work for you AI will soon become a pervasive part of our lives, just like the internet. Get familiar with the major AI systems – ask various AI chatbots about your job and how they can help make your work more efficient, then give their suggestions a try. Play around with new coding tools that help you create your own app and website without needing to write your own code. But chatbots aren’t what makes AI so useful in the workplace, it’s AI agents, or programs that run automatically, make decisions and take actions autonomously. You can learn how to make your own, and a chatbot can help. Try the prompt: “I want to learn how to make an AI agent. Walk me through the steps to create an agent that can do [specific task]”. “In some ways it’s never been a better time to be an entrepreneur, because if you can think of it, you can make it,” Shrier said. “There are people making robust enterprise-grade software that is built off of a prompt in plain English.” Humans can’t be entirely replaced Even roles that include a lot of AI-achievable tasks will still need humans in some way. AI has particularly affected the coding industry. But Anthropic employees still edit and review code even if they’re not writing it, CEO Dario Amodei said at the World Economic Forum in January. “In best-case scenarios, the more mundane tasks that are part of people’s jobs today will be handed over to AI, while the more interesting and rewarding tasks will be done by humans, probably with some support of AI,” Nov said. “It’s very likely, if history is a guide, that new jobs, consisting of new collections of tasks, will be created.” By Hadas Gold

AI ‘voice cloning’ scams are on the rise. Here’s how to protect yourself

A California mom says she was scammed out of thousands of dollars this month after receiving a call that sounded like her daughter in distress. She now suspects it was an artificial intelligence-generated hoax. She’s one of many who have been targeted by so-called “voice cloning” scams as AI tools allow anyone to create a convincing replica of someone’s voice with only a few seconds of real audio. Americans lost more than $893 million to AI-related scams last year, including voice cloning attacks along with AI-generated phishing emails, romance scams and other hoaxes, according to the Federal Bureau of Investigation. Scammers can mimic anyone from family members and friends to coworkers or professional services workers. Banks including the United Kingdom’s Starling and the Commonwealth Bank of Australia have warned customers to watch out for voice cloning scams. Experts say AI voice replicas have gotten so realistic that most people can no longer reliably distinguish them from real human voices. “For the everyday person, it is just not fair to expect them to be able to spot this stuff,” said Henry Ajder, an expert on AI-generated media who consults for governments and companies. “I struggle with it. Most people do.” How do AI voice scams work? Scammers can create an AI replica of someone’s voice using a short recording of their speech — often pulled from social media or an earlier scam call that was surreptitiously recorded. Social media can also provide a trove of information about family members and close friends who could be targeted. Fraudsters will typically make it sound like the loved one they’re mimicking is in distress, purportedly having been kidnapped or in jail. Then they’ll urgently demand money in exchange for their loved one’s release. “There was no time to think,” Gary Schildhorn, a Philadelphia attorney who was targeted by an AI voice scam mimicking his son, told CNN last year. “It was all, ‘I have to react to help my son. He’s in trouble.’” In some cases, the AI voice may be more than just a single recording. Sophisticated attackers could use text-to-speech tools or “voice skinning,” which manipulate a scammer’s voice so they sound like the person they’re imitating in real time. Those techniques facilitate back-and-forth conversations between the target and the AI clone voice, potentially making the scam more convincing, Ajder said. Hackers can also make it appear as if a call is coming from a known number through a tactic known as caller ID spoofing — so you can’t necessarily trust that a call that appears to be coming from your mom is indeed her. How to avoid falling victim to AI voice scams Strange pauses or vocal fluctuations were previously considered red flags that a caller’s voice might be AI-generated. But those signals may no longer be present now that AI has advanced. Instead of trying to determine whether a voice is authentic, look for other general scam warning signs, Hany Farid, a professor at UC Berkeley and chief science officer at GetReal Security, told CNN last year. Is the person on the other end giving a deadline or introducing a sense of urgency? Are they encouraging you not to tell anyone else what’s happening? Are they asking you to move large sums of money in unusual ways? Those are the types of questions experts say to keep in mind. Targets who receive these types of calls should try contacting their loved one through other means, such as via a text message, calling them on another person’s phone or reaching out to someone who would know where they are. Deborah Del Mastro, the California mom recently targeted, told ABC7 News that she called her daughter only after sending money to the scammers. Her daughter answered right away and was at work. Families or coworkers can also establish a precautionary “code word” that can be used to verify each other’s identity. It should be a word or phrase that only a small group of people know and isn’t discoverable online. “Ultimately, if you suspect that something might not be right, it is much better to have your mum or your brother or your friend laugh at you for thinking that they’re a robot,” Ajder said, “than it is to potentially be running to an ATM.” By Clare Duffy

Nobel Prize-Winner Demis Hassabis Says AI Job Cuts Are Dumb. Research Agrees

Across America, graduating college students are booing commencement speakers who mention AI, and communities are battling data centers. A backlash against AI is clearly underway. It’s not hard to see why. With their talk of a jobs apocalypse and general creepiness, plenty of AI CEOs these days don’t seem to realize they often sound like Hollywood supervillains. But there is one notable exception — Demis Hassabis. If you’re not already familiar with him, Hassabis is the head of Google-owned DeepMind. That seems like a position with supervillain potential. But he also won a Nobel Prize in chemistry for his work using AI to solve one of biology’s most vexing problems — predicting the shapes of proteins — and then releasing the solution to the world’s scientists for free. Rather than using AI to replace workers, cheat on everything, or flood the world with slop, Hassabis enthuses about its potential to help cure disease and engineer energy abundance. He’s soft-spoken and bespectacled rather than square-jawed and cape bedecked, and he positions himself as AI’s science-minded good guy. His latest public stance is likely to add to this reputation. As Wired recently reported, he called the recent mania for AI-fueled job cuts basically just dumb. Why AI-driven layoffs are dumb Speaking at Google’s I/O event, Hassabis explained that DeepMind doesn’t look at AI as a way to eliminate jobs and cut costs. Instead, he sees the technology as a way to help businesses dream bigger and do more. “Perhaps there is an ulterior motive for putting those messages out; raising money or whatever,” Hassabis said of other firms slashing headcount supposedly because of AI. “From my point of view, from DeepMind and Google’s point of view, if engineers are becoming three or four times more productive, then we just [want to] do three or four times more stuff.” Sure, companies can use potential productivity gains of AI to trim headcount and pad profits for the benefit of investors. But there’s no shortage of other ways they could deploy the resources freed up by handing many tasks over to the bots. “I have a million ideas, from lab drug discovery to game design,” Hassabis continued. “I’d love to have some free engineers to go and do those kinds of things.” Companies trimming tech talent may be suffering from “a lack of imagination—and a lack of understanding of what’s really going to happen,” he believes. Research shows that layoffs usually backfire Is Hassabis right that companies chasing a short-term boost through AI job cuts may come to regret the decision? We’ll all have to wait for a definitive answer to that question. But there are good reasons to think he might have a point. First, research shows that layoffs in general are often a stupid idea. Of course, they save money. Sometimes they’re genuinely unavoidable (though that mostly doesn’t apply to the mostly super profitable firms doing them now). But multiple studies show that a short-term bump in performance is usually followed by a longer-term decline. Stanford’s Jeffrey Pfeffer summed up the research this way: “Layoffs often do not cut costs. … Layoffs often do not increase stock prices, in part because layoffs can signal that a company is having difficulty. Layoffs do not increase productivity. Layoffs do not solve what is often the underlying problem, which is often an ineffective strategy, a loss of market share, or too little revenue. Layoffs are basically a bad decision.” That’s not even taking into account the human cost to workers. Other research has found that being laid off increases a person’s risk of suicide by two and a half times and increases mortality by 15 to 20 percent over the following 20 years. So why do layoffs? As Hassabis suggests, some firms may be peakcocking for Wall Street. Others may genuinely need to free up funds for a strategic shift. But mostly, Pfeffer insists, “layoffs are the result of imitative behavior. These companies … are doing it because other companies are doing it.” An AI-specific reason layoffs are dumb That’s the general case against layoffs, and it’s pretty strong. But there is another argument against AI-driven layoffs specifically. On the MIT Sloan Management Review website, consultant and author Andrew Winston points out that when firms use AI as an excuse to trim headcount, they also diminish their pipeline of talent. They may save a few dollars. They may also find themselves short of skills and talent when they need them in the future. You can ignore this problem, but it might come back to bite you. As the case of climate change proves, asking CEOs to forego a quick performance bump for longevity and resilience later may be borderline hopeless. Winston continues to point out this inconvenient truth about AI anyway. “I’m asking companies to accept potential (short-term) competitive disadvantages on the basis of uncertain future benefits and collective responsibility. That’s a hard sell,” he acknowledges. “But I have a sneaking suspicion that we will look back at early 2026 and kind of wish we had just stopped.” Don’t get caught up in AI layoff FOMO All of which is a warning to other bosses looking on at tech company layoffs with FOMO. When some of the biggest names in business are all slashing jobs, you might feel like you’re missing a trick if you don’t follow suit. But both Nobel-winner Demis Hassabis and a whole bunch of research suggest leaders should take a breath and really consider whether they want to get swept up in AI job-cut mania. Cutting costs has obvious benefits for your bottom line. But what profit-making possibilities will you not pursue because of those job losses? How will the departure of their colleagues affect the state of mind and productivity of those left behind? Will you likely regret the move later when you find your team is burned out and your bench of experienced talent is incredibly thin? Before you cut jobs, take a minute and consider whether Hassabis is right. Doing more things because of AI could be a smarter choice than employing fewer people. EXPERT OPINION BY JESSICA STILLMAN, CONTRIBUTOR, @ENTRYLEVELREBEL

AI May Replace 80 Percent of Skills. This Last 20 Percent Will Make You Irreplaceable

I work in front of a screen. And I’ve been thinking about how AI will change my work. What does it even mean for my future? It’s completely normal to wonder about this. Most people are convinced artificial intelligence is a threat to their careers. But what they are forgetting is the human value they bring to their work. Aaron Levie, CEO of the enterprise cloud company Box, recently pointed out that when people watch AI at work, they are most likely seeing it take over the first 80 percent of a task—the heavy lifting of repetitive processing. The last 20 percent is where you come in. Your domain expertise, judgment, and relationships. That is what makes you irreplaceable. AI can finally give you the space to add human value at work. “The extra 20 percent, it turns out, is all the value creation of that profession. All the expertise and domain knowledge is in that last 20 percent, not the text that got generated,” Levie said in an interview with Casey Newton of Platformer, the online publication about tech and democracy. I couldn’t agree more. Your judgment is valuable Take the work of a lawyer. Junior associates spend most of their week reading precedents, looking for case connections, and summarizing legal statements. That’s the 80 percent of the work. The long, tedious, trainable, reproducible task. No client hires a lawyer just for that. They expect them to make a better and more persuasive case for them to win. To convince the judge. To save the dying deal. The 20 percent only you can do. The practical human value. AI work feels like completion, but it’s not. Not even close. It’s good at execution, but the meaning and context are all up to you. The career anxiety you feel about AI is normal, but it may be misdirected. When people say “AI is taking my job,” they usually mean it’s taking their tasks. Writing code, analyzing long documents, and doing the research. The first pass. And yes, super-intelligent machines are coming for those. If you built your professional identity entirely by executing tasks, that’s hard reckoning. The good news is, your knowledge from doing and experience is still relevant. All of that makes your judgment valuable. AI cannot replicate that. Domain expertise under pressure must count for something. A cybersecurity engineer knows exactly what steps to take when an attack is live. Making that call in real time with incomplete information changes their approach. Data doesn’t always give a clear answer. You have to decide anyway. Who bears that decision? Not the AI. It can notice the patterns. But it’s the engineer who must come up with a specific solution to solve the problem. Most companies are limited by execution capacity. They can’t pursue every good idea because they don’t have the people to execute them all. When AI takes care of the execution, the constraint becomes the quality of the ideas. The clarity of human judgment. And the client relationships they can’t afford to lose. If you still want to hold onto the 80 percent, you’re running in the wrong direction. You can’t compete with AI on speed. Focus on honing your quality of judgment. The value and usefulness only a human perspective can fill. Your clients don’t buy your services just for the deliverables; they buy the peace of mind too. And they also like to work with people with a better reputation. Trust is not a digital asset. In the future of work, the world will reward the 20 percent more. The calculator case When calculators became universal, they didn’t make mathematicians obsolete. They just took over repetitive math, which freed mathematicians to spend more time on quality and better mathematical thinking. The profession evolved upward. The entry-level work disappeared. The high-level work expanded. AI is doing the same thing to knowledge work. At scale. Only it’s happening everywhere, in every field, all at once. Build the kind of expertise that requires better judgment. And relationship capital that compounds over time. Develop your specific point of view at work. What AI can’t do is replace your original perspective earned through engagement with practical problems over time. Your distinct angle on your field, built from specific experience, failures, and observations is what matters. It’s the experience that makes your presence valuable in the room. The threat from AI is understandable. The pace of change is insane. Some jobs and skills are becoming less valuable. Don’t stay terrified. Fear takes away your ability to think clearly. It makes us hold onto the routine tasks we feel safe doing. But routine tasks are exactly what the machines want. If you’ve been doing meaningful work for any serious amount of time, you’ve accumulated things AI cannot access. AI is taking the parts of your job you probably didn’t love that much anyway. Even that requires your input. If you feed AI the wrong ideas, it will give you a brilliant, highly optimized wrong answer. The rarest skill right now is the ability to diagnose the actual problem before rushing to fix it. You are still needed for work that requires your specific experience. Don’t underestimate what you’ve already built. You have what it takes to survive AI. By Thomas Oppong FAST COMPANY

Apple’s Siri Update Could Include a Major AI Privacy Twist

More rumors about Siri’s big makeover are leaking ahead of Apple’s annual developer conference—and one big change could have a lot to do with data privacy and security. Apple is expected to launch a standalone app for its embattled AI assistant, Siri, which will operate as a chatbot-like interface, similar to Anthropic’s Claude or OpenAI’s ChatGPT. Users are expected to be able to type or speak requests. Although the app will be able to store conversations to mine for contextual information for future requests, Apple is expected to differentiate itself from its competitors by allowing users to auto-delete their conversations, according to a report from Bloomberg. This is much like the way Apple allows users to auto-delete their text messages, which works so well, Bloomberg notes, that it has invited complaints over government officials using the feature to delete their messaging histories. Apple also plans to establish stricter guidelines around what information does hang around in the system and how long it can be kept. Competitors typically allow users to toggle on temporary incognito modes that prevent conversations from being used to train AI models. It’s worth noting that Apple has brought in Google’s Gemini and cloud infrastructure to keep the Siri update functioning and on schedule—after costly delays. Apple first introduced its Apple Intelligence as a mix of on-device and cloud-based computing that it billed as similar to iPhone security but in the cloud. Called Private Cloud Compute, it was expected to operate on Apple’s own servers and chips. Bloomberg reports that Apple will still call its system “Private Cloud Compute,” but the mechanics of how it might operate aren’t clear, given the Google integration. The two-year delay around the roll out of an updated Siri has proved to be a stain on Apple’s recent track record, as well as an expense, because of a recent $250 million settlement on a class-action suit that alleged false advertising. But if Apple is successful in relaunching Siri with an emphasis on privacy, it could justify to consumers the longer wait time, especially as concerns gather about what people are sacrificing in the name of cutting-edge AI features. Apple’s Worldwide Developers Conference will kick off on June 8. The tech giant is expected to announce iOS 27, as well as software for Mac computers and iPads. And the graphic for the conference, featuring glowing lettering, hints at a new look and functionality for Siri. BY CHLOE AIELLO @CHLOBO_ILO

They Won a Prestigious Writing Prize. Then These Key Giveaways Sparked Allegations of AI

A London-based literary competition is facing major scrutiny after three of five winners have been accused of using AI—partly or wholly—to write their prize-winning stories. The 2026 Commonwealth Short Story Prize selected one winner each from five regions that span Africa, Asia, Canada and Europe, the Caribbean, and the Pacific. Following publication of the winning entries in literary magazine Granta, online sleuths called foul. The Caribbean regional winner, Jamir Nazir, was praised for the “lyrical precision and haunting atmosphere” of his short story “The Serpent in the Grove,” as well as “the confidence and restraint of its voice,” according to a post on social media platform X by Commonwealth Foundation Creatives. But internet denizens allege that the very same voice that won the prize may not be human at all. Nabeel S. Qureshi, an AI marketing entrepreneur and a former visiting scholar at the Mercatus Center at George Mason University, flagged certain signs he said were AI tells such as “‘Not X, not Y, but Z’ sentences,” as well as the use of the word “‘hum,'” in a post on X. He concluded by writing: “A major milestone for AI, at any rate …” Following the allegations, Wired ran the text of “The Serpent in the Grove” through AI detection tool Pangram, which the publication notes has consistently outperformed other similar tools. It determined that the text was 100 percent AI-generated. It’s worth noting that no AI-detection tools are totally accurate. “The Serpent in the Grove” isn’t the only story under scrutiny. Pangram determined that “The Bastion’s Shadow” by John Edward DeMicoli, the winner from Malta, was also fully AI-generated and that “Mehendi Nights” by Sharon Aruparayil, the winner from India, was partially written using AI. Holly Ann Miller’s “Second Skin,” and Lisa-Anne Julien’s “Me and Ma’am,” however, were ruled “fully human-written” by Pangram, according to Wired. The regional winners were chosen from 7,806 entries, which the Commonwealth Foundation noted on its site is the “second highest number in the Prize’s history.” A final winner from among the five will be announced on June 30. Following the allegations, the Commonwealth Foundation released a statement on its website, acknowledging the challenges generative AI poses to literary and creative work. The statement also noted that the foundation’s judging process is robust, but judges do not currently use AI checkers in any stage. “We are aware of allegations and discussion regarding generative AI and our Short Story Prize. We take these claims seriously and are committed to responding to them with care and transparency,” the statement reads. “When they submit stories to the Prize, writers accept our entry rules and guidelines. These include confirming that their submission is their own original work. All shortlisted writers have personally stated that no AI was used and, upon further consultation, the Foundation has confirmed this.” The foundation also noted that until a reliable tool emerges with which the organization can screen unpublished work for AI, the prize competition “must operate on the principle of trust.” As always, Redditers had much to say about the subject, some assuming AI guilt, others questioning the accuracy of the AI checking tools, and many picking at the quality of the stories more broadly. “This…doesn’t surprise me given the state of contemporary literary prose. It honestly just reads like bog-standard ‘MFA voice,’” one Redditor wrote of Nazir’s story. A recent report from digital marketing agency Graphite found that since the debut of ChatGPT in 2022, there has been a meteoric rise of AI-generated content on the internet. The number of articles written by AI now equals that of human-written content, although the overall share seems to have plateaued. Axios reported at the time that the quality of AI-generated writing has meaningfully improved, not to mention that it can be difficult to determine what constitutes AI writing. Whereas some content is mostly or entirely AI-generated, some writers use AI tools throughout the process of drafting and editing. BY CHLOE AIELLO @CHLOBO_ILO

AI is changing the internet forever. Here’s how

There’s a simple reason Google is making sweeping changes to its iconic, decades-old search engine: users are making complicated requests. “People are asking much longer and harder questions that no longer have a clear response anywhere on the internet,” said Robby Stein, vice president of product for Google Search. Stein spoke to CNN about a new feature that lets Google generate custom visuals, interactive graphics and even mini-apps running on Google’s search page in response to queries by piecing together sources from across the web. It’s one of many updates the internet giant announced at its annual conference this week. The most valuable real estate on the internet is evolving to reflect the new ways people find information online, the latest example of how artificial intelligence is changing the internet across search, social media, online shopping and more. People are starting to use longer, more specific search terms instead of succinct generic keywords, according to Google, and are increasingly beginning their searches in apps like ChatGPT, experts say. Fake, AI-generated influencers are causing a stir on social media. And people are increasingly using AI to compare and buy products. It’s getting impossible to avoid using the internet without somehow encountering AI, despite growing anxiety about the tech and its impact on jobs, safety and the environment. “After a while, it just becomes part of the way you live,” said Joseph Turow, a University of Pennsylvania media professor who will soon be releasing a book about AI’s impact on internet advertising. ChatGPT ‘trained’ people to search differently Google says its search box is getting its biggest upgrade in 25 years. The new search field expands to fit more text and makes it easier to add other media to a search — like photos, files and Chrome browser tabs. The goal is to shrink the number of steps for a user to complete a search, according to Stein. That includes tasks like performing a search based on a photo or switching to Google’s AI Mode before asking a follow-up question. Searches that involve questions based on snapping a photo or circling something on a phone screen are growing 60%, year-over-year, he said. Searches in AI Mode, or the version of Google tailored for back-and-forth interactions, have more than doubled every quarter since they launched a year ago, and AI Mode queries are triple the length of a regular search on average. Data from SEO and marketing firm Semrush indicates some people are starting to search Google the way they type to ChatGPT. Searches containing 11 words or more increased from 3.27% to 5.37%, and conversational queries jumped from 5% to 20%, while keyword-style searches decreased. Yet the median query still contains just three words, suggesting that most people still search the old-fashioned way. Robert Langenback, president of SEO marketing agency Eight Oh Two Marketing, said he’s observed people typing in more searches that range from three to five or five to 10 words instead of two to three words. That started before ChatGPT’s arrival in late 2022, although it’s ramped up significantly since then. “(AI has) really almost trained people how to search differently,” he said. People generally use a mix of AI apps like ChatGPT and Google. More than 20% of ChatGPT referral traffic goes to Google, Semrush found after analyzing 1 billion lines of US clickstream data, or “trails” of user activity across the web. Google is typically used for direct questions or transactions, while ChatGPT is used for summarizing information, making comparisons and drafting materials, Semrush said in an email to CNN. “There’s a lot of just, ‘I’m trying to find something and help me get to it right away,’ that is the bulk of the queries that have gone into Google over time,” said Leigh McKenzie, director of organic visibility at Semrush. The rise of AI influencers AI’s reach extends far beyond search. Take Aitana Lopez’s Instagram profile. Online she looks like any other social media influencer, photos showing her posing at glitzy events, hitting the gym and sharing beauty tips to nearly 400,000 followers. But she’s not real. Lopez is one of the most prominent AI-generated characters to rise to internet stardom, along with Lil’ Miquela, Lu do Magalu and Granny Spills. Nearly 80% of marketers have increased spending on creator content that uses generative AI in the last 12 months, according to social agency Billion Dollar Boy. There are even awards celebrating the best AI-generated internet personalities. AI personalities are appealing to brands because they’re typically cheaper than high-profile human influencers and can morph to fit specific campaigns, said Turow. Tech giants want to make AI an even bigger part of social media. Meta is integrating its Muse Spark model into apps like WhatsApp, Instagram and Facebook and is testing side chats with its AI assistant in group conversations. On Tuesday, Google announced Gemini Omni, a new AI model that people can use to generate realistic avatars of themselves. The race to own online shopping Traffic to US retail sites from AI services grew 393% year-over-year in the first three months of 2026, according to Adobe, with Meta, Amazon, Google and OpenAI all introducing AI shopping tools. Google this week introduced a new “universal” shopping cart that allows users to add items from different retailers across the web. Amazon recently folded its Rufus shopping assistant into a new tool called Alexa for Shopping, which incorporates the AI helper into the online retailer’s search bar so shoppers can ask it to compare products and pricing history, among other things. But even as AI directly answers shoppers’ questions at the top of Google, Stein says there’s still a need for quality websites created and maintained by humans. Google says it still send billions of clicks to websites every day, although Pew Research data last year found that Google users are less likely to click links when viewing an AI summarized answer. Langenback says that while his clients are seeing less traffic, the traffic they are getting is leading to higher engagement — completing a purchase, booking an appointment or requesting a quote. “You just have to be ready to adapt, because (search) could look a lot different six months or a year from now,” he said. By Lisa Eadicicco

Google is making its biggest change to the search bar in years

To get ahead in the new internet age, Google wants to help you google less. The company on Tuesday revealed a flurry of AI-powered features for its search engine, AI assistant Gemini and other services. It’s part of Google’s latest effort to revamp its decades-old business model to fit the era of artificial intelligence. Among those updates is a new version of the search bar that can crawl the web on a user’s behalf and a new mode in Gemini that can work autonomously over periods of time. The changes bring Google’s search engine closer to the likes of its biggest competitors today: Anthropic and OpenAI, whose sophisticated AI models have taken over some of the duties of search tools and web browsers. Revamped search Google for years has been moving away from delivering a list of blue links in response to search queries. But the refreshed search engine, which runs on the company’s new Gemini 3.5 Flash model, represents what may be its biggest shift yet toward AI and away from traditional search. The new search field expands to accommodate longer queries that are more conversational, aligning with the way one might type or talk into Gemini or ChatGPT. Users will be able to create “agents” in Google’s search engine that can track or research topics on their own. Google says it’s useful for tasks that require tracking and monitoring announcements and listings over time, like apartment hunting or new apparel releases. One can, for example, enter a query like “Keep me updated when any of my favorite athletes announce sneaker collabs or signature drops” to prompt Google to monitor announcements from notable athletes and brands, the company cited as an example in a press release. Google will also now generate custom visuals and mini apps in response to certain requests, such as creating a fitness tracker that incorporates a person’s location, weather data and apps connected to their Google account. A new Spark Since it launched the AI-powered Gemini, Google has struggled to differentiate the assistant from its main search engine. Spark, a new mode within Gemini that can work on tasks in the background, is its latest attempt to change that. Spark will be able to work on recurring long-term tasks like monitoring credit card statements and email inboxes for important updates and creating summaries or to-do lists. It can also reference content across certain apps, like compiling notes from Google Docs, Gmail and Slides, and the company says more third-party apps will be supported in the future. The company is also adding Spark to the Gemini app on Mac computers so that it can work with local files, and users will be able to monitor what their agent from their phones through a new feature called Android Halo. The agent will stay active even when the person’s laptop is closed or their phone is locked, Google says. The focus on autonomous features seems like a direct response to OpenClaw, the buzzy AI agent that made waves in Silicon Valley earlier this year for its ability to run programs and commands without constant prompting from the user. Building AGI Google has been pursuing AI agents for years, although use cases have mostly focused on specific tasks like shopping or email management and haven’t taken off with consumers broadly. That’s largely because the technology simply hasn’t been reliable enough. “I think there’s this uncanny valley where the models aren’t yet good enough, so you can’t trust them fully, and so you aren’t really sure what you can and cannot do,” Tulsee Doshi, senior director of product management at Google DeepMind, told CNN. Google hopes the updates will bring it closer to its big-picture goal of developing artificial general intelligence: a theoretical stage of AI in which the technology becomes as intelligent as a human at broad range of subjects. OpenAI, Meta and others are racing to be the first to get there. But AI will have to get better at updating its own intelligence before AGI is possible, said Koray Kavukcuoglu, chief technology officer at Google’s DeepMind AI lab and the company’s chief AI architect. “Right now, our models (have) some sort of capability in doing that, but you can imagine that they’re a little bit static in time,” he told CNN ahead of Google’s conference to announce the updates. DeepMind DeepMind is at the center of the company’s AI strategy and has become one of its biggest assets in the AI race. It’s Google’s “secret weapon in the AI wars” according to Dave McCarthy, an analyst covering cloud and infrastructure services for market research firm The International Data Corporation. Most tech companies don’t have massive consumer reach and direct access to a research lab and cloud systems. “Google is the only company that I can think of that actually has a play in every one of those areas,” McCarthy said. Yet Anthropic and OpenAI are largely perceived as being ahead of Google in AI business products; Anthropic has been releasing new models and AI agents for coding, finance and other office work at a rapid clip this year. Anthropic accounted for 34.4% of paid AI business subscriptions in the US in April while OpenAI accounted for 32.3% and Google’s share was just 4.5%. That’s according to finance platform Ramp, which analyzed contract and transaction data with AI companies from more than 50,000 American businesses. AI is also causing concerns over the future of jobs, safety and the impact of data center construction on local communities and the environment. Half of American adults say the increased use of AI in everyday life makes them feel more concerned than excited, according to Pew Research. But Google, like many companies, is staking its future on the technology. Gemini now has more than 900 million active users, and the company expects to spend about $180 to $190 billion this year on expenses related to AI infrastructure and chips, Alphabet CEO Sundar Pichai said in a press briefing ahead of the conference. And the technology will undoubtedly continue to move quicky. Varun Mohan, a director at Google DeepMind who works on Google’s Antigravity AI coding product, said they ship a new release “close to every day” for internal developers. “We’re open to the fact that we are going to need to make changes very quickly, because otherwise we are going to have a product that is old for our users,” he said. “And we’ll be doing our users a disservice if we just hold on to our ideals of what the product is today.” By Lisa Eadicicco