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Your company has rolled out AI like its a new office uniform. Everyones using it. And unlike most uniforms, people are using it even when they are told not to. As a result, your inbox clears itself, your reports write themselves, and meetings collapse into neat little summaries at the click of a button. You may be even be fantasizing about sending your digital clone to those pointless meetings, and perhaps your colleagues have done so already (which may explain their perfect attendance record). And yet, theres a difference between outsourcing pointless tasks to AI, and making work better (which also requires you to figure out what to do with the time you save). Plainly put, if you are running faster in the wrong direction you will only get to the wrong place faster. This may explain the recent resurgence of an old paradox, Robert Solows law, which in the late 1980s noted that You can see the computer age everywhere but in the productivity statistics.” What are you really using AI for? Right now, most companies treat AI like an espresso shot for knowledge workers. A jolt to help fire off emails, draft decks, or summarize meetings. It feels like magic, but magic tricks dont grow the bottom line. Saving a few minutes here and there is like sweeping the kitchen when the roof is leaking. Part of AIs seduction is its smooth, conversational interface. Ask, and you shall receive. But business value doesnt appear by asking polite questions: It usually requires hard structural change. And so far, AIs biggest impact has been making existing processes leaner, often by replacing the interns and juniors who used to do that work. Think of it as corporate liposuction: It trims the fat, but it doesnt build new muscle. To be sure, as the great Peter Drucker noted, there is nothing so useless as to make more efficiently what should not be done at all, which may explain why, in a resurgence of Solows law, AI is everywhere except in the productivity stats. Cutting costs makes humans twitch Behavioral economists call it loss aversion: We hate losing more than we enjoy winning. Announce that AI will eliminate jobs, and people panic, even when the math adds up. History, though, shows a different pattern: As old tasks disappear, new ones emerge. Just as the rise of spreadsheets created a need for finance analysts, AI will create demand for data governance, ethics, and human oversight. The long arc of technology bends toward job growth, but the bumps along the way are brutal. The real promise of AI isnt subtraction, its addition Netflix recently used generative AI to add an impossible scene to a show, something too costly and complex with traditional methods. Thats the story leaders should chase: holding baseline costs steady and producing something better. AI at its best is not a fancier calculator; its a time machine that lets you create what yesterday was impossible. So what makes a great AI project? Right now, too many organizations are wandering around with a hammer, mistaking everything for a nail. A CEOs blanket mandate, everyone must use AI, is like ordering an army to march without telling them where the battle is. Great AI projects share three ingredients: Volume: Attack the most common, repetitive activities that drive your business. Shave seconds off the thing done a million times, and youve found your goldmine. Variability: Raise the floor. Get average performers closer to your best. Its like tightening a symphony so fewer notes are off-key. Human Glue: Fix the broken joints between systems. AI shines when it eliminates the soul-crushing cut-and-paste that holds organizations hostage. But heres the kicker: speeding up one cog in a broken machine doesnt make the whole machine run better. Unless you reimagine end-to-end processes (often across teams and departments) youre just moving bottlenecks around, and should really not expect great results. Data: the ceiling that caps your ambitions AI is like a gourmet chef: It can cook only with the ingredients you give it. If your data is stale, inconsistent, or scattered across warring silos, dont expect a Michelin-starred meal. Most firms have exquisite data in a few areas (finance, operations), but HR and talent data? Thats like a pantry filled with mystery cans. You know who got promoted, but not why. You feel when a team clicks, but cant quantify it in machine-readable terms. Without proprietary, well-structured data, your competitive advantage is just reheating the same meal as everyone else. Culture: the silent killer Even the sharpest AI project can crash into an organizations immune system. A culture obsessed with cost-cutting breeds fear. Misaligned incentives choke collaboration. A weak communication culture makes change management impossible. Remember, 80% of change projects fail, and AI doesnt get a free pass (it is still a change management task, and very much led by humans). Layoffs may feel like the obvious shortcut, but decades of research show that slashing headcount first is like burning the furniture to heat the house. It buys a little time, but undermines long-term survival. Leaders need to show courage, humility, and clarity. Employees, meanwhile, can choose to be architects of change instead of passive victimsreimagining work, learning new skills, and using AI as a career lever rather than a threat. Doin Better Right now, too many firms are playing the corporate equivalent of toddler soccer: everyone chasing the ball, no strategy, lots of shouting. Winning with AI depends on three foundations: The right technology, deployed against the right problems The right data, accurate and unique The right culture, aligned and prepared for change Everything else is noise. The lesson is clear: AI is not the main course, it is the fire. It can burn the house down, or it can cook a feast no one thought possible. What separates the two outcomes is not the cleverness of the algorithms, but the imagination of the people deploying them. If leaders see AI only as a knife for trimming costs, they will eventually cut into the bone of their own organizations. But if they see it as a telescope (an instrument that lets us glimpse horizons we couldnt see before) then AI becomes a catalyst for growth, innovation, and human potential. The future wont be won by those who use AI most quickly, but by those who use it most wisely: to create new value, to elevate human talent, and to turn technological possibility into strategic reality.
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E-Commerce
When people think innovation, they tend to think startup. Theres no question that the most transformative ideas in business often emerge from young ventures: new entrepreneurs building new companies powered by new ideas. At Fast Company, we peer around a lot of corners, trying to identify the most compelling stories emerging from this undiscovered terrain. But I have a little secret to share. While I love the shock of the new as much as the next business journalist, theres a subset of innovation coverage that I tend to find more surprising and inspiringgreat stories about legacy businesses that are innovating from within. This issue is full of fine examples of this, starting with our cover story on Starbucks and its CEO, Brian Niccol, by global design editor Mark Wilson. Shortly after taking the Starbucks job a year ago, Niccol launched a back-to-basics strategy. He culled the bloated menu, launched an ad campaign that refocused consumers attention on the quality of the coffee itself, jettisoned those printed drink-order stickers on cups for cute handwritten Sharpie notes, and worked to improve the physical experience of sitting in a Starbucks and enjoying your drink. All of these moves acknowledged that in its pursuit of operational efficiency (including a gold-standard app for pickup orders), the coffee giant had lost some magic. Niccol has stabilized Starbucks, but the strategy has yet to deliver the results shareholders expect and demand. He insists that its early still, and that his plan for year twoincluding a full redesign of 1,000 storeswill move the numbers in a meaningful way. Wilson explains and analyzes this plan in detail. Later in the issue, senior staff writer Elizabeth Segran talks to Latriece Watkins, the chief merchant at Walmart and a two-decade veteran of the company. Watkinss delicate task: attracting affluent shoppers to the value chain without alienating its budget-conscious consumer base. And I interviewed ESPN chairman Jimmy Pitaro about the sports behemoths new eponymous streaming service, which finally debuted in late August after years of planning and half-measures such as ESPN+. Among the topics we covered was gambling, an increasingly integrated feature of the ESPN experience. Is that innovative? Sure. Is it good for sports (and society)? Almost certainly not. Theres probably another reason I like to readand publishjournalism about innovation at legacy companies: Fast Company is itself a legacy brand. We turn 30 this fall. In November 1995, Bill Taylor and Alan Webber, whod formerly worked at the Harvard Business Review, launched this sui generis business magazine. It immediately spawned a flurry of imitators, such as Business 2.0, Red Herring, and The Industry Standard. Only Fast Company remains. I like to think that its because we take what we cover so seriouslyand learn from it. Happy birthday to us! And thank you, as always, for being here.
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E-Commerce
Media companies have filed so many lawsuits against AI companies over the past two years that the act has become routine. When I report on these in The Media Copilot newsletter, they’re often digest items, adding to the pile of publishers who want fair compensation for the content AI labs have ingested to create large language models (LLMs). There are so many that elaborate infographics are required to keep track of them all. Penske Media’s copyright lawsuit, however, is anything but typical, and that’s because of its choice of target. The Rolling Stone publisher is going after Google. Google is in many ways the big fish in the AI world. It’s true that more people use OpenAI’s ChatGPT than they do Google Gemini, but Google has the distinction of being both a frontier AI lab and the current owner-operator of the primary way people get information on the internet. If you count AI Overviews in search, Google is arguably bringing AI to more people than anyone on the planet, period. {"blockType":"creator-network-promo","data":{"mediaUrl":"https:\/\/images.fastcompany.com\/image\/upload\/f_webp,q_auto,c_fit\/wp-cms-2\/2025\/03\/mediacopilot-logo-ss.png","headline":"Media CoPilot","description":"Want more about how AI is changing media? Never miss an update from Pete Pachal by signing up for Media CoPilot. To learn more visit mediacopilot.substack.com","substackDomain":"https:\/\/mediacopilot.substack.com\/","colorTheme":"blue","redirectUrl":""}} And because of that, the media is starting to feel serious pain. As more Google searches result in answers instead of 10 blue links, people aren’t clicking like they used to, and the referral traffic that publishers depend on is drying up. To add insult to injury, Google uses a single crawler to index websites for both regular search and AI, forcing publishers to allow it to harvest their content for Overviews even while search is sending them fewer and fewer referrals. The dam is bursting Still, nobody wants that referral number to go to zero, so virtually no one in the publishing world has dared poke the big G. When News Corp sued Perplexity last year, there weren’t that many AI search engines yet, but there was at least one more: Google. Everything News Corp cited in its complaintthat Perplexity ingested content, used it to build a competing product in its AI answers, and didn’t bother to pursue content licensingcould equally apply to Google, yet no second lawsuit was filed. Will that change now that Penske Media has made its move? And I don’t mean just for News Corpif the publisher of Variety, The Hollywood Reporter, and Billboard has looked at the numbers and decided legal action is worth the cost and risk, how many others are coming to the same conclusion? On the other hand, this might play out more like The New York Times v. OpenAI, with other publishers mostly watching from the sidelines, reasoning they could play it safe and still benefit if there’s a decision favorable to the media. We’ll know the answer to that soon enough, and yes, technically Penske Media isn’t the first content provider to sue Google over AI Overviews; Chegg, an online educator, filed suit against the $3 trillion tech giant back in February. But Penske’s lawsuit does something else: It exposes Google’s claim that AI Overviews send “higher quality” traffic to publishers as a meaningless consolation prize. Last fall, when the effects of Overviews were just beginning, Google said that people who click on links in the summaries were more intentional users, and thus more likely to engage and even transact with the sites they click on. And that may be true, but it’s telling that Google still hasn’t provided concrete data to back up that claimspecifically how much Overviews reduce click-through rates overall. And that’s OK, because now we have third-party data on the click-through rates of AI answer engines, and they’re dismal. Pew Research, Similarweb, and TollBit have compared the crawl-to-referral ratios for AI engines to search engines, looking at how many users they actually send versus how often they scrape content (which usually is indicative of a search), and they don’t look good. Click-through from AI search is 90% lower than regular search, per TollBit. In other words, the drop-off in referrals from AI summaries is so massive that, in almost all cases, the “higher-quality” visitors couldn’t possibly make up for the loss in business from the lost search referral traffic. And remember: Google doesn’t separate its search and AI botsyou either let both crawl your site, or you get nothing. Google Nero? Google is rumored to have begun talks with publishers to license content for its AI, which would be a massive shift, and possibly quell the impulse for other publishers to join Penske in the legal arena. However, that would turn Google AI search results into another OpenAI: summaries that included content from publishers big enough to have leverage, leaving smaller players with little recourse but to continue to provide their content to Google for free. If the two Google crawlers were separate, things would be different. Publishers of any size could opt-out of AI Overviews while maintaining their position in regular search. The fact that Google is considering paying publishers for AI is evidence that the two technologies are governed by different business models. Forcing a site to give up content for both is like a gas station that forces you to get a car wash before it’ll fill up your tank. Over the past decade, the publishing world has woken up to the predations of Big Tech. The search/social era didn’t turn out well for the industry, and now it wants to choose a different path with AI. Except now tech companies like Google have so much leverage over distriution, the choice has been taken away. Can a lawsuit get it back? Maybe, maybe not. But at least it shows the media is no longer afraid to try. {"blockType":"creator-network-promo","data":{"mediaUrl":"https:\/\/images.fastcompany.com\/image\/upload\/f_webp,q_auto,c_fit\/wp-cms-2\/2025\/03\/mediacopilot-logo-ss.png","headline":"Media CoPilot","description":"Want more about how AI is changing media? Never miss an update from Pete Pachal by signing up for Media CoPilot. To learn more visit mediacopilot.substack.com","substackDomain":"https:\/\/mediacopilot.substack.com\/","colorTheme":"blue","redirectUrl":""}}
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