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• The environmental cost of putting data centers in space

  When SpaceX filed an FCC application earlier this year proposing to launch a million satellite data centers into orbit, the company argued the project would have no meaningful environmental impact. On SpaceX’s website, Elon Musk made the case for space-based AI infrastructure in simpler terms: “It’s always sunny in space,” he wrote, arguing that orbital data centers are “obviously the only way to scale.”

  When SpaceX filed an FCC application earlier this year to launch a million satellite data centers into space, the company said that the plan wouldn’t have any environmental impact.

  But researchers say the climate calculus is far more complicated than that.

  Yes, orbital data centers could theoretically run around the clock on solar power. But the tradeoffs extend far beyond electricity consumption. “The social and environmental consequences are far greater than what we’re currently looking at with Earth-based alternatives,” says Peter Howson, a researcher at Northumbria University who recently authored a paper examining the risks and challenges of space-based computing infrastructure.

  First, the emissions from each rocket launch are large—a single SpaceX Starship launch burns around a kiloton of liquid methane and produces as much climate pollution as a small city does in a year. Black soot emitted from rockets is long-lasting in the upper atmosphere and can cause significantly more global warming than the same pollution on the ground. “Soot that comes out of the tailpipe in a car normally lasts maybe a few weeks in the lower atmosphere,” Howson says. “But when you put it into the upper atmosphere, it could stay there for years.” Water vapor emissions also act as a potent greenhouse gas.

  Around 2 million liters of water are also used to protect launch pads at every launch, and that process can wash toxic dust and debris into local ecosystems. In Texas, the state’s Commission on Environmental Quality and the EPA previously found that SpaceX repeatedly violated the Clean Water Act.

  Launches can go wrong. In 2023, when the first Starship test flight lost control and was destroyed after a few minutes, the wreckage covered the nearby Boca Chica State Park, home to endangered species, and started a fire. Five Starships have exploded on their flight paths since then.

  The launch and satellite equipment uses toxic chemicals, including hydrazine-based propellants for maneuvering, lead solder, and ammonia for thermal control. Accidents or “rapid unscheduled disassemblies” can release hazardous substances—and in some cases, rather than staying in orbit, those materials can reenter the atmosphere and potentially rain down on people on Earth.

  Once in space, the equipment wouldn’t last long, and then would create e-waste. “The environmental impacts of satellite ablation (atmospheric burning) are not well understood,” Howson writes in the paper, which was published in the journal Energy Research & Social Science. “However, materials and gases released are likely to contribute to ozone depletion while potentially affecting the Earth’s ability to regulate solar radiation.”

  Space is already crowded with satellites—and the number is quickly growing as tech companies race to add more space-based internet access and private weather satellites, among other things. But the tech company vision for data centers could dwarf that. SpaceX’s Starlink network has around 10,000 satellites now. Starcloud, one startup working on orbital data centers that raised $170 million in a Series A round of funding in March, wants to have 88,000. SpaceX, as noted above, wants to have as many as a million orbital data centers. Many other companies are working on similar technology, including Google, which wants to deploy its “Project Suncatcher” in space by 2027, and is now also reportedly in talks with SpaceX on a new rocket launch deal. Jeff Bezos’s Blue Origin and others are also working on the technology.

  With more satellites in orbit—including cheap satellites that are more likely to malfunction—it’s also increasingly likely that there could be a crash that triggers “Kesler Syndrome,” a chain reaction of collisions that creates a huge debris field that blocks satellites from some regions.

  Space data centers are still an unproven idea, with major technical challenges and the possibility that it may not ever be economically viable. But their promise is accelerating an industry that’s already causing real-world damage, including social impacts. In Indonesia, the government plans to let SpaceX build a spaceport on the island of Biak, Papua, where dozens of indigenous people have been killed after protesting the project. In Texas, the Carrizo-Comecrudo tribe says that SpaceX’s Starbase sits on a sacred site. In northern Sweden, where the Swedish Space Corporation has a spaceport, Sámi herders now have to dodge falling rocket parts.

  Orbital data centers are also unlikely to replace the massive fossil-fueled data centers that are already under construction on Earth. But Howson argues that companies are pursuing orbital data centers because they need to answer shareholder questions about how to source the energy needed to maintain growth. And perhaps investors are attracted to wild ideas.

  “They’re doing it, I think, just to maintain investor excitement,” he says. “Because the cost involved is 10 times more when you put it into space. So it doesn’t make a lot of economic sense. And it certainly doesn’t make any environmental sense.”

• The global oil crisis is proving the case for sustainable aviation

  As the conflict in Iran strains the world’s oil supplies, a lot of attention has focused on gasoline: Average gas prices have increased more than a dollar a gallon since the war began, exceeding $4 a gallon for the first time in four years.

  But vehicle travel isn’t the only type of transportation affected. Jet fuel prices have roughly doubled in that same time frame. In March, U.S. airlines spent 56% more on fuel as compared to February, per Bureau of Transportation Statistics.

  When it comes to cars, rising gas prices have highlighted the benefits of—and spurred more interest in—sustainable alternatives like electric vehicles. The conflict has underscored the fact that EVs and renewables aren’t just good for the environment; they’re also a buffer against geopolitical instability. 

  The same thing is now starting to happen in the airline industry with sustainable aviation fuels. But meeting that demand may be a challenge. 

  Sustainable aviation fuels aren’t just for climate goals

  “Sustainable aviation fuel is not just for sustainability,” says United Airlines CEO Scott Kirby. “I tell everyone [jet fuel is] our biggest cost. It’s our most volatile cost. …and guess what happened?”

  Kirby, a self-proclaimed “climate change geek,” has long been interested in sustainable aviation fuels (also called SAFs) as both a way to reduce airline emissions and a tool to reduce costs. 

  SAF makers echo his arguments. “SAF not only supports emission reductions and propulsion for aviation, but also strengthens fuel security and reduces exposure to these external shocks,” says Chris Cooper, CEO of sustainable aviation fuel company XCF Global. At its refinery in Reno, XCF can produce SAF using domestic waste feedstocks, turning fuel from a global commodity to a more stable, local one. 

  Still, SAF remains a small portion of airlines’ overall fuel usage. United, a leader in terms of SAF usage, has invested in the production of more than 5 billion gallons of SAF. Even so, SAF accounted for just around 0.3% of the airline’s fuel use as of December 2024, according to the company’s most recent impact report.

  To ramp up SAF production and use, Kirby says the industry needs “the kind of government carrots that worked for wind and solar.” 

  The Inflation Reduction Act was a start; the Biden-era legislation provided tax credits and grants to make SAFs more cost competitive to conventional fuels. President Donald Trump’s One Big Beautiful Bill Act, however, cut those tax credits nearly in half—from $1.75 per gallon to just $1 per gallon.

  Challenges to scaling up SAFs

  The political environment has companies across different industries, including airlines, quieter about their climate goals. In April, Delta Airlines erased some environmental targets from its sustainability web page, including its pledge to use SAF for 10% of its jet fuel by 2030. 

  The turn away from sustainability is happening outside the U.S. as well: In 2024, Air New Zealand abandoned its 2030 climate goal.

  Kirby says a lot of these airlines had set environmental goals with an ambitious 2030 deadline—in line with the Paris Agreement targets. For some companies, it seems that date is proving hard to meet, so they’re rolling back their commitments.

  “Our goal was always 2035,” Kirby says. United aims to cut its greenhouse gas emissions intensity 50% by then, compared to 2019 levels, and 100% by 2050. “There’s no way we’re going to get this done in 2030,” he says. “It just wasn’t going to happen.”

  The high price of SAF has also made some airline executives reluctant to commit to the climate solution. “I’ve heard other CEOs who I like and respect say, ‘if someone produces SAF and it’s cost competitive, I’ll buy it,’” Kirby says. “Okay, but we should try to help make that happen.” 

  Even with jet fuel prices currently soaring, the price gap is notable. SAF costs over $3 more a gallon than conventional jet fuel, according to the trade association Airlines for America. 

  As a SAF producer, Cooper says that the industry needs more support. Before becoming CEO of XCF, Cooper was president of Neste, a SAF producer that has partnered with United multiple times, including to bring SAF to the Houston, Newark, and Dulles airports in late 2025. “This isn’t a simple solution that a producer such as XCF can simply produce enough product that creates economies of scale, that then allows an airline to participate,” Cooper says. 

  To get that participation, passengers have to be involved as well, Cooper adds. They have to be willing to pay more to make it a viable solution.

  “An airline only participates in cost increases when their corporate [partners] and or traveler participates,” he says. “They put a first class meal on an airplane because there’s a first class seat that they sold; the person paid a premium. So when we all work together and the passenger, whether it’s a corporate business or a tourist, pays for sustainability, then the airlines are able to participate and wholly adopt this new energy source for their needs.”

  Airline emissions will only keep growing

  Currently, aviation is responsible for about 2% of global greenhouse gas emissions. That adds another challenge to the efforts to decarbonize this type of transportation.

  “If you’re going to spend a million dollars to decarbonize the economy, the bang for your buck spending it on SAF is a lot lower than just electrifying road transport,” Kirby says. “That doesn’t mean we shouldn’t be preparing for it and doing the work. We should. But the bang for the buck is bigger in other places.”

  To that point, Cooper has a counter: Aviation may account for just 2% of global emissions right now, but that figure is growing. Between 2000 and 2019, aviation emissions grew faster than rail, road, or shipping emissions, according to the International Energy Agency. The International Civil Aviation Organisation forecasts that by 2050 international aviation emissions could triple compared to 2015. 

  “The airline industry knows that” its emissions will increase, Cooper says. “They themselves have discussed the continual growth and expansion of demand into many, many years to come. …They’ll quickly become a greater percentage than 2%.”

  Sustainable aviation fuels will be critical to mitigating that increase and decarbonizing the sector, experts say. Cooper hopes that the current fuel crisis will help highlight all benefits of the fuel alternative and hasten its adoption.

  “Energy security is a global concern,” he says. “Periods of geopolitical instability have repeatedly exposed these vulnerabilities. And those disruptions have helped accelerate interest in SAF.”

• Ikea’s newest furniture makes Scandinavian design fun again

  Inside Ikea’s movie studio-size marketing and production facility at the company’s headquarters in Älmhult, Sweden, a corner of a vast soundstage is piled with a multicolored array of what look like props from some fantastical children’s show. There’s a bench that rocks from side to side, a bright blue lamp that hides two transformative elbows in its skinny post, a glass vase with jug ears sticking out from its sides, and a clock on the end of a curvaceous red tube that looks like a worm wiggling its way out of the dirt.

  

  These whimsical items are all part of Ikea’s new PS collection, a once-in-a-while recurring product drop that the company uses to stretch its experimental design muscles. Now available in stores and online, this year’s PS collection is the 10th since the company set out in 1995 with a line of products intended to take some ownership over the increasingly widespread proliferation of Scandinavian design.

  

  The PS collection is a flag-planting moment for the global home furnishings giant, staking a claim over the present and future of Scandinavian design, and plotting a way forward for its own design intentions. That includes softly curved plywood chairs, a clever square table with a drawer that can slide through from one side to the other, and a wacky adjustable stool that uses a sawtooth mechanism to ratchet up to different heights.

  

  “The brief was ‘less but more, simple but not a bore,’” Maria O’Brian, the creative leader behind the PS collection. “And this is what came back.”

  She’s standing amid the collection in Ikea’s soundstage in early April when I visited the company headquarters for an exclusive look at its prototyping shop, where many of the 1,500 to 2,000 new products Ikea releases every year are meticulously developed.

  

  During my visit, part of the collection was being prepped to ship out to Milan for the annual Salone del Mobile furniture fair. Once the exclusive domain of the high-end design world, Salone got its first infusion of Ikea’s low-cost “democratic design” with the inaugural PS collection in 1995. More than 30 years later, O’Brian sees the new PS collection doubling down on its original purpose.

  

  “Scandinavian design is all about simplicity, the material, the functionality, the directness of design. And it’s also about resourcefulness and being smart with the materials and ornamentation. You don’t want to just slap something on there for the sake of it,” O’Brian says. “But it’s not boring.”

  

  That’s how a seemingly infeasible product like an inflatable easy chair is now making its way into hundreds of Ikea stores around the world. During my visit to Ikea’s headquarters, I saw some of the dozens of prototypes it took designer Mikael Axelsson more than a decade to develop in his aim to turn his inflatable furniture idea into something comfortable that could also be manufactured at Ikea’s vast global scale.

  

  I also saw the grueling trial and error between designers and production facilities to realize designer David Wahl’s foldable side table, a briefcase-like portable table that opens in one smooth motion and clicks into place. In Ikea’s prototyping shop, Wahl pulled out four prototypes of the design, each with slightly different hardware and fittings, and each a wobbly mess. “We called it a dancing table,” he told me, rocking an early version like a hula dancer. It took nearly a year of back-and-forth work to achieve the millimeter-precise locking mechanism that kept the table steady.

  

  Other products in the PS collection have easier origins. The bright floor lamp with two pivot points in the lamp post came from designer Lex Pott sawing 46-degree cuts into a broomstick. Designer Friso Wiersma used his background as a boatbuilder to create a highly refined storage cabinet with doors that look woven like baskets.

  

  “I asked him to make some storage for the collection. He was like, okay, see you in a week,” O’Brian recalls. “He showed up with two final, amazing cabinets. And then we just took the discussion from there.”

  

  A few other highlights from Ikea’s new PS collection include a puffy chair that flops open to become a bed, and a pared-down chair with a backrest that can be used sideways as an armrest or even backwards as a place to prop up your elbows.

  “The point of PS is that we do challenge ourselves. We challenge what we think we can do or how we do it,” O’Brian says. “We wanted to push our boundaries.”

• Lyft CEO David Risher on his first job and what he learned from it

  I mowed a lot of lawns and cleaned a lot of gutters as a kid, but my first consistent job was delivering newspapers. Today that sounds quaint, but it was a rite of passage back in the day.

  I grew up in Chevy Chase, Maryland, just outside Washington, D.C., raised primarily by my mom and in the most modest house of anyone I knew. She used to say we were never poor– we just didn’t have a lot of money. So at age 15 when I heard that a Washington Postdelivery route paid $100/month, I jumped at the chance.

  This was the Post in its prime, not long after its reporting on the Watergate scandal made the paper famous. Every home in the area had a subscription. Politicians, lawyers, lobbyists, staffers – they all woke up and reached for the same paper, expecting to be on their porch by 6:30am. And even if I was just the kid making sure it landed there, it felt important.

  So at 5:30am seven days a week, I was out the door, ready to fill the bag slung over my shoulder and walk porch to porch. There’s something clarifying about that hour. No one is asking anything of you– it’s just the work in front of you and the responsibility to get it done. I loved it.

  Except Wednesdays. Wednesdays were brutal. Coupon inserts from Safeway and Giant turned what was already a heavy bag into something you felt in your shoulders for days. And it was doubly brutal if it rained that day. But people were counting on the Post showing up. Someone was going to pour their coffee, sit down at the kitchen table, and reach for it, rain or shine. Coupon day, or not.

  Looking back, what that job really taught me wasn’t just about showing up on time, though it was that, too. It was about understanding that reliability is a form of respect. Everyone wants to be seen. When you commit to being there for someone – and you follow through – you’re telling that person: I see you. You matter.

  That sits at the center of what we do at Lyft. Every ride is a commitment. A driver heading out at 5 a.m. (and there are a lot of them) is honoring the same promise I made on that paper route: I’ll be there. They’re getting to the airport, to the hospital, to a job interview.

  The stakes are higher than a twelve-year-old delivering a Wednesday newspaper. But my commitment is the same, seven days a week, 24 hours a day, a billion times a year.
  
  It’s a valuable lesson no matter what you do.
  
  My First Job is a recurring series in which prominent business leaders share what their first job was and what they learned from it.

• The Demi Moore-AI debate is missing the point

  Oops, it happened again. A celebrity was asked what they think about artificial intelligence and, after sharing their reflections, received intense blowback on social media.

  The latest such case is Demi Moore, who is currently serving on the jury for the Cannes Film Festival. At a May 12 press conference meant to introduce the broader film event, Moore was asked by a journalist about AI, its impact on Hollywood, and potential regulation.

  “I always feel ‘againstness’ breeds ‘againstness.’ AI is here,” Moore responded, clearly thinking on the spot. Rather than fight a “losing” battle, Moore suggested that artists figure out how to “work with” the technology. This, she opined, would be a far more productive path forward. The Substance star then proceeded to suggest that there is probably not enough being done in terms of regulating the technology, before concluding with one final and trite, though seemingly heartfelt, salvo.

  “The truth is: There really isn’t anything to fear because what [AI] can never replace is what true art comes from, which is not the physical. It comes from the soul,” she asserted. “It comes from the spirit of each and every one of us sitting here . . . to each and every one of us that creates every day. And that they can never re-create through something that’s technical.”

  Moore has since been pilloried in some corners of the internet. She’s facing both fair criticism and a bevy of offensive insults, many of which dismiss her as a pro-AI shill or, perhaps worse, a pro-AI dunce.

  Moore joins a growing number of celebrities who have either volunteered to comment on, or been asked about, AI, and subsequently been sorted into camps of support and opposition.

  On one side are skeptics like Guillermo del Toro, who would “rather die” than use generative AI, and Nicolas Cage, who is a “big believer in not letting robots dream for us.”

  On the other are more accommodating voices like Sandra Bullock, who says AI should be used in a “constructive” way, and Reese Witherspoon, who, quite inartfully and with the verbiage of a sponsored-content hack, encouraged women to get in the game and use the tech. These statements all tend to come with attendant cheers or barbs from online fans eager to police any positive statements about the technology.

  This new micro-trend of celebrity AI takes—and AI takedowns—comes as Hollywood looks to position itself in relation to a technology that stands to rapidly transform cinematic production on the whole. Through automation, AI could, critics argue, threaten jobs, further abuse intellectual property, cheapen the process of art-making, and fuel the influence of Silicon Valley firms over creative industries.

  Of course, there’s also a flip side: AI advocates say that while the arrival of these new platforms does challenge a traditional business model, they also lower the barrier to entry and constitute a new way to democratize the creation of art. Think about it: Now anyone with access to a few powerful models can produce high-quality animations, even if they don’t have a multimillion-dollar film budget or fancy studio.

  But the problem with forcing anyone, including celebrities, into pro- and anti-AI camps is that AI is already here. Artificial intelligence also continues to be a wildly vague term that can refer to anything from machine-learning algorithms used to catch typos in scripts and assist in video editing to extremely impressive visuals rendered with just a few prompts to a large language model. In the jumble of online discourse, all of these phenomena are swept together into pro-AI or anti-AI contingents.

  Yes, celebrities are making all sorts of cringey comments on AI, but lambasting them for acknowledging the technology is here, likely already endemic, and even comes with some compelling use cases isn’t progressing the conversation. AI is currently shaping our digital and material lives in ways that are useful and exciting and noxious and terrifying, often through mechanisms that are mostly beyond the consumptive or creative purview of any one person.

  What might be more important is pushing people to think specifically about what they mean when they talk about AI and more critically about the ways AI is influencing the distribution of power, wealth, and even creativity. Dealing with AI requires looking for a more equitable vision of these tools, rather than polarizing ourselves as pro or against a technological category that remains extremely poorly defined.

  Consider the thoughts expressed by Paul Laverty, a screenwriter and lawyer also serving on the Cannes Film Festival jury, in a follow-up to Moore.

  “I think we have to look at the first thing and see who owns it, because they decide on the algorithms that affect our lives in the deepest way,” Laverty said. “People are beginning to realize that we should not let these tech bros—billionaires who are mostly right-wing libertarians—dictate how we live our lives. What’s the effect to be [on] workers, beyond artists, ordinary workers and society and our children?”

  Which is to say: Maybe we ought to spend less time policing celebrity AI takes and more time interrogating the people building the systems themselves.

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• The app this Nebraska roofing company built to help its business has become a super tool for contractors nationwide

  There are many ways to measure the success of CompanyCam, a Lincoln, Nebraska-based startup unicorn that popularized a photo-focused construction tracking app that’s become popular within the roofing industry.
  
  But one of the clearest signs that its design, utility, and functionality are hitting the mark is the variety of users the app continues to attract.

  There are shipbuilders who use it to track how vessels are built and to certify the strength of a hull. Retail merchandisers love the ability to showcase product setups and track subcontractors. Property managers use it to oversee buildings.

  “We have some aestheticians—which I think our terms of service say they shouldn’t use us for—doing ‘before’ and ‘after’ photos for CoolSculpting,” said chief financial officer Tullen Mabbutt. “One thing that has always fascinated me about our business is all of the interesting use cases that we never intended to solve.”

  The firm grew out of founder Luke Hansen and his family business, White Castle Roofing, which his father started in the 1980s and he took over with his two brothers, Dane and Jake, in the mid-2000s. The Hansen brothers wanted to scale up and expand the firm, and through the process of growing, came up against the challenges of workplace documentation for roofing contractors.

  Insurance companies needed detailed images of damaged roofs and the finished repairs. Homeowners wanted to know if the crews on top of their homes were damaging things. And the company had challenges while overseeing multiple crews: getting updates when projects finished, and managing materials and labor flows with quick updates from job sites.

  Photos became central to the company’s processes and its reputation locally, and helped back up its motto, “Built by trust, proven by time.” By the late 2000s, before more sophisticated phone photo apps became de rigueur, White Castle crews were carrying a digital camera with an SD card to job sites, tracking work and then sending the photo card back to the office after every shift. 

  In 2015, Hansen started searching for an app that could help them handle their contracting and recordkeeping work, and help White Castle progress beyond a shared drive or Dropbox. Disappointed that he couldn’t find a suitable option, he hired a local development studio in Lincoln, Agilx, to develop one, and soon launched CompanyCam. The app offers easy-to-navigate recordkeeping tools—photo annotation, shared files and project records, and in-app communication for workers in the middle of a workday. 

  The team soon realized they were on to something when they started seeing the benefit of the live feed that was embedded in the early release, which automatically uploads and syncs photos and video clips from job sites so the entire team can see; now, managers could see exactly when a job was finished, or track work in real time, making it much easier to oversee a large contracting business. 

  “What started as a better way to put project photos into folders quickly turned into this accountability, quality management, and project management tool,” Mabbutt said. “All of a sudden, as a business owner, you could sit in the office and know the status of every single project.”

  They began marketing it as a general-purpose project management tool, as opposed to one simply for construction contractors, and now CompanyCam boasts users from 30,000-plus companies. 

  As the company has grown over the last decade, it’s continued to keep pace with its customer base and technology. Being local and hands-on—the other Hansen brothers still run White Castle Roofing and sit on the board of CompanyCam—gives Hansen insights into product usage and development. Product teams get insight into real user experience questions; when it’s 105 degrees, and a user is 20 feet in the air leaning over a ladder, is it really the right time to ask them to click a button? 

  “We think we’re in a unique position, especially with AI, to help contractors get more done from the job site without having to click 10 buttons,” he said. “Contractors spend a lot of time in their truck. We want to act as a field agent that helps them get stuff done while they’re rolling.” 

  And they’ve fully embraced AI. It turns out that having a huge database of job site photos gives them a considerable edge when it comes to designing useful artificial intelligence tools. So far, CompanyCam has very practical AI features, like daily project recaps or voice-to-text features that replace the ubiquitous job site notebook. But eventually, the goal is to create a marketing suite that can utilize client photos to help their advertising campaigns. They just launched a generative AI tool to help create project portfolios and conduct marketing via social media. 

  After a $415 million raise last August that valued the company at nearly $2 billion, CompanyCam just acquired Beam, a fintech company for contractors, in order to add even more functionality for its user base. But its origins in Lincoln helped it find its identity.

  “Early on, being able to cobble together a ragtag group willing to work on this was a huge advantage,” Mabbutt said. “Building a tech company in Nebraska forces this close, collaborative relationship with other tech companies in the area. What we lack in density, we make up for in collectivism, if you will.”

• This tiny Maine town used AI to make a new logo. Its residents had other ideas

  After proposing a new design for its municipal logo on Facebook, one tiny Maine town faced backlash in the comments section when it admitted the mark was generated by AI. The post and page are now private.

  Newburgh, Maine, population 1,520, is some 25 miles from the coast, just outside Bangor. In its Facebook post late last month, the town didn’t hide the fact that its proposed farm-theme logo was AI-generated, and even asked for feedback.

  “It’s time to update our town logo that we use on our letterhead,” the post read, according to Bangor Daily News. “This is what AI and I came up with as I am no artist. Also, attached is what our old logo looked like. We wanted to know thoughts on the new design and if it represents Newburgh.”

  

  The logo shows a farmhouse with a silo inside of a round seal with hills in the background. In the foreground, there are rows of crops and a pine tree, a longtime Maine symbol. The AI authorship of the logo is obvious in text written along the bottom, where the two number 1s in “1819” are upside down and the letter I in “Incorporated” is a number 1.

  Residents from the small town were not happy. David Aston, who lives in Newburgh and owns the nearby Timber Hearth Tattoo Co., offered to design a logo for the town.

  “I think it’s important for local governments to go human-made because it reinforces the importance of design and art as a human endeavor that’s just as important as the other functions of government,” he tells Fast Company.

  The AI logo was a take on Newburgh’s current logo, an illustration of a farmhouse that’s too detailed to look good when shrunken down. On town letterhead, the current farmhouse mark appears along with Word Art-style text in a concave shape that writes out its year of incorporation. It looks dated, and the town is well intentioned to consider a new logo.

  Redesigning town or city logos is inherently fraught, though, since everyone has an opinion about graphic design, especially when it’s about where they live. When it comes to winning over the public, using AI is likely to make the process even harder.

  A Pew Research Center survey released in March found nearly 40% of U.S. adults believe data centers are “mostly bad” for the environment and home energy costs.

  That’s especially true in Maine, where growing backlash culminated in the first statewide ban on data centers in the U.S. The ban, passed by state lawmakers in April, lasts more than a year and covers data centers that surpass a certain size.

  Representatives for Newburgh didn’t respond to a request for comment, but taking into account the small size of the town staff and government (its town manager, for example, serves as clerk, treasurer, tax collector, registrar of voters, and general assistance administrator), it’s perhaps not surprising they might turn to AI for logo ideas.

  Graphic design experience is not a requirement for public service, and not every municipality has the budget or resources for design-forward government services. Still, the blowback in Newburgh is instructive.

  Getting public input was smart, and what town officials found was that for many residents, an AI design doesn’t represent them. When it comes to branding the places we call home, a human touch is key.

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• ServiceNow CEO Bill McDermott: Silicon Valley is getting enterprise AI wrong

  Enterprise software has long operated on a relatively stable hierarchy of power: The companies that owned the interface largely owned the customer relationship. Employees moved through dashboards, tabs, forms, and menus; software vendors sold more seats, expanded across departments, and steadily compounded recurring revenue.

  Agentic AI is beginning to destabilize that model. Increasingly, enterprise users no longer need to navigate software directly to complete routine work. AI agents can coordinate actions across multiple systems through natural-language commands alone.

  That possibility has rattled the software industry. Earlier this year, SaaS stocks sold off sharply as investors questioned whether AI agents could weaken sticky interfaces, compress seat growth, and erode the economics that powered enterprise software for decades.

  The question now hanging over the industry is whether AI agents will hollow out enterprise software altogether, or if they’ll reorder where value accrues within it. Few executives have pushed back against that first narrative more aggressively than Bill McDermott, the longtime ServiceNow CEO who argues investors fundamentally misunderstand how enterprise AI will actually get deployed inside large organizations.

  “AI thinks,” McDermott tells Fast Company. “It’s got tremendous compute power. But it doesn’t act.”

  That distinction sits at the center of ServiceNow’s broader AI strategy. While many investors worry that hyperscalers and foundation model companies will eventually absorb large portions of enterprise software, McDermott argues the rise of AI is actually increasing the importance of orchestration, workflow governance, and operational execution systems.

  “When you’re running a company, and you want the digital agents to work with the humans, or even in a lot of cases do the work that the humans are doing, they just have to execute along the lines of the business process so things actually get done,” he says.

  So far, investors’ fears around AI disruption have not materially slowed ServiceNow’s growth. The company still expects more than $15.7 billion in subscription revenue in 2026, while its Now Assist AI business reached $750 million in annual contract value in Q1 and is targeting $1.5 billion by year’s end.

  The company argues AI adoption is deepening customer reliance on the platform rather than weakening it. According to ServiceNow, 91% of net-new annual contract value in 2025 came from deals involving five or more products, while Now Assist deals that included three or more products grew nearly 70% year over year.

  Why operational reality still slows AI disruption

  Daniel Newman, CEO and chief analyst at Futurum Research Group, says the current AI cycle is moving faster than any prior enterprise technology transition, but many investors initially underestimated the operational inertia built into large organizations.

  “The deepest moat that’s making transformation and change to new technologies much harder is merely that humans change much slower than technology,” Newman says.

  That operational reality has become central to how many incumbent software companies now defend themselves against AI disruption. While Silicon Valley increasingly imagines autonomous AI systems replacing large swaths of enterprise software, companies still face governance, compliance, security, transaction, and data privacy constraints that remain difficult to solve at enterprise scale.

  McDermott argues much of the market still misunderstands the complexity involved once companies move beyond chatbot experimentation and into real operational systems.

  “You can’t just say, ‘Here’s the model. Good luck running your company with it,'” he says. McDermott also rejects the assumption that hyperscalers will inevitably absorb the enterprise execution layer entirely.

  “These are significant companies with billions invested in infrastructure,” McDermott says of the major cloud providers. “By spreading our wings and using those clouds, it actually alleviates concerns because this is about expansion in the global economy.”

  Still, parts of the original SaaSpocalypse thesis are already beginning to materialize. “I do think there’s going to be seat compression,” Newman says. “I think if you had 100 seats before AI, maybe you have 80 now.”

  The larger shift, he argues, is economic. “Seat-based pricing is dead,” Newman says. “It’s not going to be about the number of users anymore. It’s going to be about agents deployed and tokens consumed.”

  The AI stack is reordering in real time

  That transition is already forcing many enterprise software companies to rethink how they package and monetize AI products. Workday cut 8.5% of its workforce earlier this year amid broader AI restructuring pressures. Atlassian recently reported its first-ever enterprise seat-count decline, intensifying concerns that AI-native coordination systems could weaken traditional collaboration platforms.

  McDermott says ServiceNow is already navigating that transition internally. Roughly half the company’s revenue now comes from consumption-based pricing, though he argues customers still prefer hybrid models blending seats with usage-based billing.

  “That’s the Goldilocks formula,” he says.

  The new enterprise moat may be workflow depth

  Pat Casey, ServiceNow’s CTO and one of the company’s earliest cofounders, argues ServiceNow’s AI positioning stems from architectural decisions made long before generative AI emerged.

  “I think if you look at the way most of the industry is applying AI, it’s what I’d call a horizontal assistant layer,” Casey says.

  ServiceNow, by contrast, increasingly positions itself as the operational layer sitting beneath enterprise AI systems. Casey argues many systems of record were never designed to be orchestrated externally once real-world business processes begin cascading across approvals, sourcing, compliance, and downstream operational dependencies.

  A FedEx demonstration shown during ServiceNow’s Knowledge 2026 conference became one of the clearest illustrations of that thesis.

  In the demo, ServiceNow Otto, the company’s unified AI interface combining Moveworks and Now Assist, helped a FedEx distribution manager assess whether the company was prepared for a Mother’s Day shipping surge. Otto reviewed staffing coverage, identified a 37-person staffing gap, generated a compliant hiring requisition, scheduled interviews, and deployed an AI agent to manage follow-ups.

  “Putting the request in is maybe one percent of the work,” Casey says. “The actual delivery process—that’s where the complexity and the bodies are buried.”

  The hyperscaler threat may be bigger than SaaS companies admit

  That operational complexity increasingly sits at the center of the enterprise AI battle. Historically, infrastructure companies rarely stop expanding upward once they control distribution. Nearly every layer of the enterprise stack now risks abstraction from above. Data platforms remain central to enterprise AI development. Workflow platforms increasingly control operational execution. Governance layers may emerge as critical trust infrastructure.

  At the same time, open interoperability standards and emerging multi-agent protocols could eventually commoditize portions of the orchestration layer itself.

  As enterprises deploy larger fleets of AI agents, governance has emerged as one of ServiceNow’s biggest strategic priorities. The company’s expanded AI Control Tower strategy aims to govern AI models, agents, workflows, and datasets across environments spanning Microsoft, Google, Amazon Web Services, OpenAI, Anthropic, and third-party systems.

  “There’s always the risk somebody put a Mac Mini in a closet, installed an open-source model on it, and now it’s quietly doing HR tasks nobody authorized,” Casey says.

  For now, the enterprise software market appears caught between competing possibilities: foundation model companies expanding upward into enterprise execution, hyperscalers consolidating infrastructure power, or incumbent workflow platforms using operational complexity itself as the next moat.

  Newman believes many foundation model companies are already discovering how difficult enterprise deployment becomes in practice. “That’s why OpenAI is partnering with consulting companies and Anthropic has partnered with every one of these enterprise software companies,” he says.

  Still, he believes not every SaaS company survives the transition equally well.

  “The companies I worry about most are what I call features masquerading as companies,” Newman says, pointing toward lightweight productivity and collaboration platforms. “The Notions, the Mondays, the ClickUps. Those are the companies I think face the most pressure because they’re really productivity wrappers around human coordination.”

• The 3 career narratives keeping designers stuck (and how to break them)

  I’ve sat across from enough designers to know that the moment someone starts questioning whether to leave their role, they rarely lack options, they lack permission. And most of the time, that permission is being held hostage by a story that got repeated so many times it just became as normal as talking about the weather.

  Now I’m not talking about fear you can name and argue with. What I’m describing is different. Quieter. It’s the background noise that makes staying feel like wisdom and leaving feel like recklessness. It shows up in how designers talk about their timelines, their readiness, their gratitude. And it is, almost without exception, learned.

  The scripts I hear most often aren’t random . . . they’re specific. They get reinforced by performance culture and by LinkedIn mythology and in the particular way UX organizations reward compliance. After enough years of coaching UX professionals through transitions, I’ve stopped being surprised by these stories and started being angry on behalf of the people carrying them.

  Let’s dive into the top three career narratives keeping UX folks stuck.

  #1) “Just one more year”

  This one is seductive because it doesn’t sound like avoidance . . . it sounds like strategy. It has a number attached to it and so it implies you have a plan.

  But watch what happens to that plan. More times than not, one more year becomes contingent on a promotion. Then the promotion happens and there’s a reorg, and now there’s one more major initiative they want you on. The initiative wraps up and the economy shifts and suddenly it’s not the right time to leave. Three years pass and the goalpost has continued to move every single time. And it moved so incrementally you barely registered it.

  I’ve watched designers lose years of their professional life to this one sentence, because it sounds reasonable and it speaks in the language of patience and responsibility.

  But beyond the years, you lose trust in your own read of a situation. Every time you decide you’re not ready yet, you’re practicing the belief that you are not capable of assessing your own life. You train the instinct out of yourself, and the instinct you’re training out of yourself is the same one that makes you good at your work.

  I often encourage my clients to sit with themselves and ask these two questions: what are you actually waiting for, and who gets to decide when that condition is met?

  #2) “I need more experience”

  This one sits in the gap between what you’ve actually built and what you’ve been taught to believe counts as legitimate. And I see it most in designers from historically marginalized backgrounds, women, first-generation professionals who grew up learning that credentials are the price of taking up space. That you have to be more ready than everyone else just to be considered ready at all.

  The logic is simple enough: if you’re not ready yet, you haven’t failed yet.

  So there’s always one more certification to get, one more title to hold, one more thing to add to the portfolio before real exposure ever has to arrive. Until you find yourself years later, staying in motion without going anywhere.

  I’ve worked with enough designers who made the leap to know that the experience you’ve built does not belong to the organization where you built it. The research skills, the way you hold complexity while moving toward clarity, the instinct for where a system is breaking . . . none of it stays behind when you leave. It comes with you. It is yours.

  What doesn’t come with you is the story that none of it was enough.

  Readiness, in corporate environments, is designed to stay just out of reach. That’s not a conspiracy, it’s just how organizations retain people. And what I need you to understand is that naming the dynamic isn’t cynicism, it’s an opportunity to see possibility outside of the corporate career ladder.

  #3) “I should be grateful”

  This is the one I find hardest to watch, because it’s the most difficult to push back on directly. Gratitude is real and it’s worth something. And acknowledging what a role gave you isn’t wrong either. However, there’s also a version of this story that often functions as a muzzle.

  It gets used, especially with designers from historically underrepresented communities or during times of economic upheaval, to make wanting more feel like ingratitude (and to reframe naming harm as not being a team player). The message underneath isn’t really about gratitude, it’s that access, even access to a place that’s diminishing you, is something you should protect. That you’re lucky to be in the room and that asking for more is overstepping.

  I’ve seen designers stay in genuinely harmful situations for years because they couldn’t shake the feeling that leaving would mean failing to honor what it cost to get there. That’s not gratitude: that’s something closer to self-betrayal dressed up in a virtue.

  But here’s the thing, you can hold both things at once. You can mean it when you say a role shaped you and still know you’ve taken everything from it that it has to offer. You can respect how hard it was to get in the room and still decide the room isn’t serving you anymore.

  How to Break Free of These Beliefs

  The designers I’ve watched break free of these stories don’t do it by deciding they were wrong to believe them. The stories made sense at the time because they were survival logic . . . and survival logic deserves some compassion too.

  What shifts is something closer to discernment: a practiced ability to tell the difference between what you actually believe now and what you absorbed a long time ago and kept repeating.

  And unfortunately, that kind of honesty is something most organizations aren’t built to support. It takes people around you who can reflect your capacity back when the stories are loudest, and it takes treating your own career with at least the rigor you’ve been giving everyone else’s.

  So I’m not sure who needs to hear this today, but corporate loyalty is not self-respect and staying in a role that no longer fits your values or your vision is not discipline. However, leaving (with intention, with your full skill set, with a real plan) is not a gamble, it’s the same process you’d apply to any design problem worth solving.

  The only thing left to decide is whether you’re willing to stop letting an old story make the decision for you.

• AI is changing who you should hire. Here’s how to get it right

  “We need someone who’s done this before.”

  Translation: we need someone who can absorb a strategic pivot, upskill personally for AI, manage a workforce whose skills and expectations are shifting, maintain execution velocity, and make faster and better decisions—with the same budget, the same headcount, and no additional runway.

  That’s not a job description. That’s a superhero spec.

  And the person most organizations reach for to fill it—the candidate with deep sector experience, the safe hire, the one who’s “done this before”—is often exactly wrong for what the role now requires.

  The logic behind the experience filter is not irrational. Sector knowledge compresses ramp time. It signals credibility with peers. It reduces the number of things that can go wrong in the first ninety days. When the environment was stable and execution was the output, it was a reasonable proxy for readiness.

  That environment is gone.

  AI has compressed execution timelines and put judgment at the center of competitive advantage. The work that once required a team now requires one person with the right capabilities. And the capabilities that matter most—operating without a playbook, making decisions under uncertainty, building alignment across functions—are not what the sector-experience filter selects for. It selects for pattern reproduction. In roles that now require pattern disruption, that’s not risk reduction. It’s risk amplification.

  New criteria

  A recent Strategy Science study, summarized by HEC Paris, found that within-industry breadth combined with cross-functional experience predicts stronger strategic foresight than narrow same-sector depth—particularly under conditions of uncertainty. The implication is uncomfortable: the profile most organizations default to in hiring may be the profile least suited to the moment they’re hiring for.

  The middle management layer is where this mismatch is most expensive.

  These are the people being asked to do something genuinely unprecedented: translate executive vision into execution reality, interpret and validate AI outputs, manage a workforce in transition, and make judgment calls faster—simultaneously, at the same level of quality, with no increase in resources. Every one of those demands has escalated in the last two years. None of them has been removed.

  According to Gartner research cited by HRDive, 75% of business managers are overwhelmed by growing responsibilities, and 82% of HR leaders say managers are not currently equipped to lead change. AI is not relieving this pressure. It is adding a new layer: managers must now decipher AI initiatives, test tools, validate outputs, and explain limitations upward—while managing fewer junior staff to absorb the work.

  This is the job that exists. It was built incrementally, requirement by requirement, until it became something no single person was designed to do. And the response—find someone who has done this before in our industry—does not solve the problem. It fills the role with someone selected for the conditions that no longer apply.

  The cost of the wrong hire

  The economics make this harder to ignore than most leadership teams have allowed themselves to.

  The visible cost of bringing in a judgment-first hire without deep sector background is real: structured onboarding, longer ramp time, investment in building context deliberately. Organizations weigh that cost and reach for the familiar.

  What they are not weighing with the same rigor is the cost of the wrong hire. Research from the Recruitment and Employment Confederation, cited by Gatenby Sanderson, estimates that a mid-level manager earning around £42,000 can cost a business more than £132,000 once recruitment, training, wasted salary, and lost productivity are included. That figure does not capture decision drag—the slower decisions, the missed pivots, the team that stalled waiting for direction that never came with sufficient clarity.

  Organizations are making some of their most consequential talent decisions without serious cost data on either side of the equation. The familiar choice feels cheaper. It often isn’t.

  The supply side

  The math is also running out on the supply side.

  According to ATD, middle manager hiring has fallen 43% since 2022—more than three times the drop in entry-level hiring. The experienced cohort that has historically filled these roles is aging toward retirement. The replacement cohort is smaller and carries less of the accumulated sector depth that organizations currently require as a baseline. At the same time, Deloitte’s 2025 human capital research finds that the work itself is shifting—AI is automating administrative and coordination tasks, increasing the need for managers who can coach, interpret ambiguity, and build alignment across boundaries.

  Organizations are trying to solve a new management problem with a labor-market assumption that is breaking down. The experienced sector hire will become harder to find, more expensive to attract, and less suited to the actual job—in that order, and faster than most hiring plans currently reflect.

  None of this is an argument for discarding experience. There are roles where deep sector knowledge is genuinely non-negotiable—where regulatory context, technical domain, or client relationships make it irreplaceable. The problem is that organizations apply the sector-experience filter uniformly, across roles where it matters and roles where it has simply become the default. Most have never made that distinction explicitly.

  The organizations making progress on this are not overhauling their entire talent strategy. They are running contained experiments: small teams, high-performing, curious, change-ready. They are measuring what happens when the hiring criteria shift. They are designing for learning before they design for scale.

  That is how you find out whether the model works before the hiring math forces the issue.

  The question worth sitting with: in your organization, which management roles genuinely require sector depth—and which are using it as a shortcut?

  Have you ever asked?