Google’s Head of Search Shares 3 Rules Every Business Needs to Win in the AI Era

Google Search has undergone some serious changes that will likely have big implications for how businesses present themselves online—and how people find them. Google VP of Search Liz Reid says there are no quick tips to hack the system, but she does explain there are techniques that entrepreneurs and business-owners can use to optimize their digital footprint for AI search. Hint: it’s all about quality. When Reid took stage at the tech company’s annual developer’s conference in May, she spelled out her vision for a brand new world of Google Search. She touted the biggest change to Google’s iconic search bar in 25 years. That included baking AI into the search experience through conversational language search interface, contextual search history, and even search with video and images. She also teased agentic features that are still only slowly rolling out to select users. Given the fact that AI Mode rolled out in 2025, these changes are hardly the first to rock Google search in recent years. Entrepreneurs may be understandably confused about how best to optimize their online presence, as AI changes the game for keywords and SEO. Despite all these changes and perhaps a bit of confusion, there are still some best practices to keep in mind. Reid sat down with Inc. to share her advice for getting the best results out of Google search for your company. Go deep and niche Reid says the recent changes to Google Search have resulted in a higher overall volume of queries and a change in their nature. The incorporation of generative AI into Google Search means people are ditching keywords in favor of questions that are phrased the way they might actually ask them. They are getting specific, providing context, and asking follow-up questions. Because users are able to get more detailed about their questions and preferences, Reid says this new behavior offers a real opportunity for companies to seize upon what makes their product or expertise unique. She gives the example of searching for shoes, which in the era of keyword search may have weighted many shoes equally. Now users can specify that they want “eco and sustainable shoes,” made by a founder with certain specifications, Reid notes. “Now this opportunity for people to differentiate themselves and shine becomes much more possible than if you could have done it before with keywords,” she says. Of course, that means business owners have to work that individuality into content on their own websites, online storefronts, and social media. Make content with value Reid encourages entrepreneurs not only to identify what makes them unique, but create value around that. In e-commerce, that might mean uploading more detailed product information to Google’s Merchant Center, and including nuanced descriptions of products on a company’s website. For a service-based business, that can mean focusing on thought leadership through mediums like podcasts, articles, and blogs that dig deeper than surface level information people may already be able to find in a Google AI overview. “Sometimes you’ll have a bunch of sites in which they’re basically saying the same thing as 500 other sites. That’s not going to go,” she says. “People would rather go and see a site that doesn’t say this exact same thing as AI overviews, but now takes it down to a much deeper level.” And, of course, Reid says, content has to be interesting: “It’s not going to rank well if when people click on it, they hate it, and they leave right away. So the first thing you should figure out is, would anyone want to read it?” Be wary of GEO claims SEO, or search engine optimization, has quickly given way to what’s being called GEO, or generative engine optimization. And a number of businesses have already been built on the claim that they’ve unlocked the secret to GEO. Reid says entrepreneurs should be skeptical of such claims and check out Google’s own resource with best practices to help people optimize for generative AI. The site notes that SEO rules still apply, and offers more detail on what high quality content actually means. It also includes “myths” about AI search, including that websites must have machine readable .txt files, content written especially for AI, or specially structured data. “I would definitely encourage people to use the tips and to express some skepticism in what they’re reading from some folks, especially if there’s business incentives for them to claim they can solve all your problems,” she says. BY CHLOE AIELLO @CHLOBO_ILO

The Best Leaders Aren’t Replacing Employees With AI, They’re Empowering Them

For years, you’ve been told that artificial intelligence is coming for your job. Silicon Valley insisted automation would replace millions of workers. Now, the people who pushed that narrative are changing their message, and that shift could reshape how you think about technology at work. OpenAI chief executive Sam Altman and other prominent tech leaders are completely abandoning the doomsday narrative. They have realized that terrifying your workforce is a terrible way to scale an enterprise. When your employees constantly fear for their livelihoods, operational momentum stalls, engagement drops, and your best talent starts looking for the exit. To protect your company and accelerate your growth, you must completely flip your internal messaging. You need to frame these new tools as massive productivity multipliers that make your people indispensable instead of replaceable. Here are three critical leadership lessons to help guide your team through this technological transition. 1. Stop selling fear and start selling execution power. If you tell your staff that an algorithm can do their jobs faster and cheaper, you immediately destroy all psychological safety in your organization. Workers who feel threatened will actively resist adopting the expensive new tools you just purchased. Instead of framing automated software as a replacement for human talent, you must position it as an upgrade for human potential. Show your team exactly how automation eliminates their most tedious administrative tasks so they can focus on high level strategy and creative problem solving. According to recent Gallup workplace data, broader technology adoption among employees is strongly associated with having active managerial support that focuses on strategic integration. 2. Ditch top-down decrees for internal champions. You cannot force true innovation through an executive mandate. Many white collar workers remain deeply skeptical of the automated tools their employers roll out. If you send a company-wide email demanding immediate compliance with a new system, your team will only use the tool when you are actively watching them. People inherently resist mandates that are forced upon them. To build a truly innovative culture, your adoption strategy must rely on organic influence rather than executive pressure. Look closely at your team and identify the employees who are already experimenting with these tools on their own time. You must empower these enthusiastic early adopters to train and encourage their peers. When a highly skeptical employee sees a trusted colleague using new software to finish a project early and leave the office on time, they will eagerly ask for a tutorial. Peer influence will always be your most effective strategy for managing corporate change. 3. Protect human ownership of the final output. The goal of implementing automation is never to turn your employees into passive observers. If your team members become completely dependent on algorithms to think for them, the quality of your business output will rapidly decline. As a leader, you must remind your workforce that human judgment remains your ultimate competitive advantage. Encourage your team to question automated summaries, challenge algorithmic data, and inject their own unique perspectives into every project. True productivity happens when human creativity directs the technology, not the other way around. The ultimate leadership takeaway The companies that thrive in this new era will not be the ones with the most advanced algorithms. They will be the ones with the most empowered humans. Your primary job as an entrepreneur is to build a culture where technology serves your people. Stop predicting the end of human labor and start building a workplace where your team feels truly irreplaceable. EXPERT OPINION BY ASH KUMRA

AI Was Supposed to Save Companies Money. Instead, It’s Blowing Up Budgets in a Big Way

The refrain from executives amid the seemingly-continuous job cuts over the past few months has been a common one: AI can do the job at a lower cost than human workers. But a new report has issued a stark warning: That school of thought is wrong. Very wrong. A survey from KPMG finds business owners are aghast at their bills for AI, now that many AI companies have shifted to a usage-based model. The accounting firm spoke with 2,145 executives around the world, and one-third said they had a limited understanding of usage costs. AI companies used to charge corporate clients a flat rate, but as compute costs have increased, many major operators are switching to a different model to help control costs. That wasn’t factored into some executives’ decisions to go all-in on the technology. “AI is now as much a financial management priority as it is a technology one,” Rob Fisher, global head of advisory at KPMG, said in a statement. “The real risk isn’t investing in AI but doing so without cost visibility and an understanding of the economics of AI. Organizations that have visibility into their costs and maintain strong oversight are the ones translating AI investment into real, measurable value.” Making matters worse, the higher pricing model comes as many businesses are still figuring out how to use AI efficiently. Many did not realize, for instance, the need to build the capabilities required to forecast, monitor, and manage AI spending, the report says. There have been several examples of this in the past year. Uber blew through its entire 2026 AI budget in just four months. (The company has since set usage caps on various AI-powered tools used by its staff.) Another company, which remains unnamed, spent $500 million on AI in just one month, since its employees apparently had no limit on how many licenses they could use. AI companies acknowledge the rising prices but aren’t signaling things will change anytime soon. Last month, OpenAI CEO Sam Altman said in an interview: “People are really saying, ‘My company spent my entire 2026 budget in Q1. Can you make this more efficient?’” And since the start of the year, Altman continued, it went from being “an issue that never came up (people were totally happy with the amount they were spending) to, all of a sudden, a huge issue.” Part of the reason for that new urgency is the escalating cost of new models as AI companies battle for supremacy. Each new top-level release is “roughly twice as expensive per token as the one it replaced,” Arvind Jain, CEO of AI company Glean, told CNBC. Prioritizing people While there has been no slowdown in tech layoffs so far (though Gartner says half of those will be reversed by 2027), a growing number of executives say they’re focusing more on human-AI collaboration, utilizing the advantages of both, and choosing to upskill their remaining workforce. “By putting AI directly into the hands of their people, organizations are better positioned to translate adoption into real business value,” KPMG’s report says. Value is key, as just 7 percent of the executives surveyed said they were seeing a return on investment in AI. Nearly one-quarter of those executives, however, said they were facing pressure to prove the technology’s value to investors. Step one of that is getting a better handle on spending. Some 23 percent said they struggle with usage-based costs, and 42 percent said they only have partial visibility into AI spending. That’s making tools like monitoring dashboards, which track the cost of each employee’s AI usage, more common. And roughly half of the executives say cost reviews have become part of the AI approval process. Companies that take those steps, says KPMG, are five times more likely to report an established ROI. “We’re seeing a clear divide between organizations with leadership accountability at the top and those without,” said Steve Chase, KPMG’s global head of AI and digital innovation. BY CHRIS MORRIS @MORRISATLARGE

Research Says Leaders Are Overlooking 1 Simple Way to Accelerate AI Adoption

Almost every company is doing something with AI right now. Some are testing chatbots. Others are automating workflows, redesigning roles, or asking employees to “use AI more” without much direction. But embracing AI and scaling it well are two very different things. According to the 2025 McKinsey Global Survey on AI, only 38% have successfully begun scaling AI across their businesses. Enter the workforce readiness recession. Employees aren’t falling behind because they’re resistant to AI, but because they lack the confidence, clarity, and reinforcement to embrace it. As AI reshapes the workplace, leaders must become both advocates for change and trusted guides through it. According to Achievers Workforce Institute’s (AWI), leaders under pressure to demonstrate AI ROI may be overlooking one of the simplest ways to accelerate adoption: employee recognition. Recognition isn’t separate from an AI strategy—it’s a practical leadership tool for accelerating adoption. Stop readiness from falling behind AWI’s seventh annual State of Recognition Report finds that just 19% of workers feel confident using AI tools, and only 18% feel supported in adapting to AI. How can companies expect results when over 80% of employees haven’t been given the confidence or support to see where AI fits into their day-to-day work? “Those who create the conditions for employee change readiness will separate the winners from the losers, both in the race to realize AI’s potential and in building a great workplace culture,” said David Bator, Managing Director of AWI. “Employees aren’t going to wake up one day ready to do their best work with AI. Change on that scale is never automatic. Confidence is built brick by brick through everyday leadership behaviors. Leaders who embrace recognition will be the ones who create the confidence, trust, and advocacy needed for AI to scale across their businesses.” AWI’s research shows recognition is most effective when it reinforces learning, adaptability, and progress rather than perfection. Closing the recognition gap closes the readiness gap Leaders have long fallen short on recognition. The first thing AWI advises is to get right is frequency. Every employee should receive meaningful recognition at least monthly to feel supported through change, yet just 19% of workers say they are regularly recognized by their manager. Leaders need to make regular recognition a management requirement, not an afterthought. Then focus on one keyword: meaningful. In the AI era, meaningful recognition isn’t about celebrating AI for AI’s sake. It’s about recognizing the human capabilities behind successful AI adoption. If an employee uses AI to uncover new sales opportunities, don’t recognize the technology, but the creativity, initiative, and business impact behind its use. “A common misconception is that recognition does nothing beyond making people feel good,” added Bator. “While celebrating your people early and often is important, leaders should see appreciation as a change catalyst. When managers reinforce learning, adaptability, and responsible AI use, they recognize good work and help drive organizational progress as AI integrates into daily work.” AI raises the value of humane leadership There’s no denying it: AI is a force of disruption at work. But every major technology transformation has ultimately been about people. A great leader understands this and ensures employees experience change as something they can grow through, not something being done to them. Right now, there is a lot of ground to make up: just 18% of workers feel informed when changes affect their job, and only 23% say communication is clear during uncertainty. Employees are asking for clarity, coaching, and confidence, and leaders can’t delegate that responsibility to AI. Recognition is most powerful when it comes from another human being. In my book, Humane Leadership: Lead with Radical Love, Be a Kick-Ass Boss, I argue that humane leaders exhibit two essential qualities —trustworthiness and advocacy —that matter even more in the AI era. Leaders bring clarity to AI by using recognition to reinforce what good work and responsible behavior look like during rapid change. Done well, recognition helps employees trust themselves, trust their company, and understand what great work looks like in a workplace being reshaped by a technology we have never seen before. EXPERT OPINION BY MARCEL SCHWANTES, EXECUTIVE COACH, SPEAKER, AND AUTHOR @MARCELSCHWANTES

IBM’s CEO Has a Message for Founders: Treat AI as ‘Day Zero’

We’re fast approaching the fourth anniversary of the launch of ChatGPT, meaning artificial intelligence has been a part of the business conversation for quite some time now. Many companies have experimented with it or attempted slow roll-outs in select areas of their operations. But IBM CEO Arvind Krishna says the days of sticking your toes in the water are over. It’s time to jump in. The rollout of the technology, he says, should be treated as a “Day Zero” event, a chance to reset the competitive race among businesses. But to do that, your business needs to start implementing AI at scale. “It’s time to sit down and take it seriously,” Krishna said on the Masters of Scale podcast. “You’re not in the experimentation phase. Day Zero, the race is about to start. Put yourself in the blocks and start sprinting.” Krishna says he isn’t talking about incorporating AI in every aspect of your company or automating a large percentage of the workforce. Instead, he recommends fully embracing AI in some aspects of your business as a case study of sorts to help you better understand what it can do for you. From there, you can expand your use of AI. “Take three, four, five things—not 100—and learn how to do them at scale, because that’ll teach you how to get all your change management done,” he said. “How do you get your data organized? How do you really get people motivated to change a process? Do a few things at scale. Learn how to do that really well. Then do 10—and then give yourself the confidence to do the next 20.” Despite all the talk of AI, Krishna estimates that just 20 percent of businesses are utilizing it correctly. The rest, he says, are not getting a return on their investment or don’t quite know what to do with it. Incorporating AI might mean bringing on new staff in some cases. And while the instinct of some founders will be to search for an AI expert, Krishna says the smarter move is to find someone who understands the difference AI can make for your company. “Find that 20 or 30 percent who are motivated to say, ‘I want to learn a new way to do things,’” he said. “I think curiosity and willingness to adapt are more important.” When it comes to measuring the returns of AI on your business, that too is going to require a shift in mindset for business owners, Krishna said. Efficiencies and savings aren’t going to be immediate, he warned. In fact, there could be additional expenses. For the first six months to a year, he said, businesses will likely spend more than they save, as they dedicate engineers to implementation and pay for tokens. But as companies operate AI at scale for a use case, they learn how to implement the technology, making subsequent rollouts cheaper. IBM played its part in introducing the world to AI with Watson, which made headlines when it won on the TV show Jeopardy! But that awareness was also a wake-up call to other companies, which began to invest in AI very heavily while IBM did not, said Krishna. “As opposed to creating building blocks, we wanted to create solutions in verticals. That, I think, is a mistake, as technology shows,” he said. Today, the company isn’t trying to be OpenAI or Anthropic. Instead, it’s betting on AI orchestration—the coordination of multiple AI models into a single workflow. It’s also focused on Enterprise AI, providing businesses with tools to build, scale, and govern artificial intelligence. Lately, there has been growing consumer pushback to AI. One recent report from AI platform Parloa found that during automated customer-service calls 61 percent of respondents have screamed at automation to get routed to a human faster. A separate survey from WordPress VIP, which offers an enterprise version of the publishing platform, found that 60 percent of the people it polled found AI in a brand’s messaging to be a turnoff, not a feature. Meanwhile, some companies that went all-in on AI are starting to realize the real cost of the technology. Uber, for instance, exhausted its 2026 AI budget in just four months and was forced to cap employee use. And several companies that fired workers in favor of AI are bringing those employees back. Krishna argued that companies that don’t incorporate AI ultimately face even more potential problems. “The riskiest route is taking zero risk,” he said. “What happens in any business that takes no risk? It means you’re trying to extract profit—or what an economist would call rent—from what you already have. But that means you’re giving everybody else the opportunity to clone you or copy you, to innovate from the bottom, and pick off the most profitable parts of your business.” BY CHRIS MORRIS @MORRISATLARGE

Microsoft and LinkedIn Just Analyzed the Future of Work and AI. It All Points to 1 Key Skill Set

Algorithms can now write code, draft legal contracts, and generate entire marketing campaigns in seconds. As artificial intelligence automates increasingly complex work, it’s easy to assume technical expertise will become the defining trait of great leadership. The evidence points in the opposite direction. Recent data from Microsoft and LinkedIn reveals a fascinating reality. While AI is automating execution, leaders are aggressively prioritizing soft skills like emotional intelligence. As tools become more artificial, humans crave the authentic. The ultimate competitive moat is no longer technical execution. It is the ability to forge genuine human connection. If you are a founder or an executive, community building fueled by high emotional intelligence is the single most important leadership skill you must master. The isolation crisis A massive psychological shift is happening in the workplace. Gallup research confirms that employee stress remains at record highs, and loneliness is a massive factor. When you introduce generative models into your daily operations, your team members spend more time prompting machines and less time talking to each other. This creates a vacuum of trust. Humans are biologically wired for social connection. When people feel isolated, their brains enter a state of chronic stress. You can deploy the most advanced foundational models in the world, but if your team feels disconnected, your output will plummet. The smartest leaders recognize that their job is not to manage workflows. Their job is to manage energy and connection. The empathy premium When technical output becomes a commodity, what becomes scarce? The answer is human resonance. The American Psychological Association recently found that workers who are worried about artificial intelligence are significantly more likely to feel tense, stressed, and isolated. A machine can generate a flawless and sterile piece of text. A human brings vulnerability, shared struggle, and nuanced understanding. In a market flooded with synthetic perfection, people will pay a premium for authentic imperfection. The same principle applies to your internal culture. Your team doesn’t want a flawless manager who acts like an algorithm. They want a leader who understands their anxieties about the future of work. They want someone who can build a safe environment where it is acceptable to experiment, fail, and learn together. Empathy is the engine of psychological safety, and psychological safety is the engine of true innovation. Your blueprint for human connection How do you operationalize emotional intelligence and community building inside your company? It requires a deliberate approach to how you structure your daily operations. Optimize for unstructured connection. Don’t just schedule meetings for status updates—a machine can read a status update. Instead, create intentional spaces where your team can connect over shared interests, challenges, and ideas without a rigid agenda. Reward vulnerability over perfection. If you want your team to trust you, you must go first. Share your own challenges and uncertainties about navigating the new tech landscape. When leaders admit they don’t have all the answers, it gives the team permission to be honest and collaborative. Elevate human milestones. Algorithms don’t care about birthdays, work anniversaries, or personal triumphs. You must. Celebrate the unique human moments that machines cannot replicate. The future of leadership isn’t about competing with algorithms. It’s about doubling down on the things algorithms can’t do. Step away from the dashboard, look your team in the eye, and start building a culture rooted in genuine connection. EXPERT OPINION BY ASH KUMRA

AI is powering an economy in which many Americans are falling behind

At the Richmond Neighborhood Center in San Francisco, more than 200 people are on the waitlist for the food pantry. The center is just a couple of miles west of “AI Alley,” where a cluster of major AI companies take in billions of dollars in investments and pay out high salaries to employees — in turn making home prices and rent payments soar. San Francisco serves as a prime example of how the roaring AI industry is helping drive economic growth more broadly, but masking the economic inequality of lower-and-middle-income families. And San Francisco reflects the same patterns happening on a national scale: In the first three months of the year, the US economy overall grew at a solid 2.1% annualized rate, largely due to businesses ramping up AI-related investments, according to Commerce Department data. Yet consumer sentiment is languishing near record lows over wartime price spikes, and the bottom quarter of Americans on the income spectrum have seen the weakest wage growth of any other cohort this year, according to the Federal Reserve Bank of Atlanta. “The inequalities in the neighborhood have just grown and grown and grown,” Yves Xavier, community programs director at the Richmond Neighborhood Center, told CNN. “We can’t draw a direct line to AI’s impact and say ‘That’s exactly it’ because it’s been happening for a while, but it doesn’t exactly take a rocket scientist to see how that’s widening the inequalities in a city already dealing with those issues.” He added that demand for the nonprofit’s food pantry is up about 10% this year. ‘An economy of winners and losers’ The diverging fortunes of the poorest and wealthiest Americans has emerged as a key theme in the US economy, and experts say AI is playing a significant role. The billions poured into the AI industry have minted a cadre of handsomely paid workers in tech hubs across the country, including San Francisco, New York, Seattle, Los Angeles, San Jose and Washington, DC, according to a report by Oxford Economics. Those workers are part of the wealthiest 10% of Americans who are increasingly powering US economic growth with their spending, or as much as 62% of growth, according to Moody’s. “You’re seeing incredible concentrations of wealth as a result of AI for these new companies, their founders and their first employees,” said Manuel Pastor, director of the Equity Research Institute at the University of Southern California. “It’s exacerbating an economy of winners and losers.” The winners in today’s economy are clearly involved in the development and funding of AI, including early investors, experts told CNN. SpaceX debuted on Wall Street last month as the largest initial public offering on record. The AI and space exploration company is now worth more than $2.1 trillion, and investors widely expect it to be a windfall for Americans’ retirement accounts. AI stalwarts OpenAI and Anthropic, both headquartered in San Francisco, are also gearing up for their own IPOs, which would add trillions in new market value. And San Francisco companies comprise nearly two-thirds of worldwide AI funding, according to data firm Crunchbase. Those losing out are vast swaths of Americans, particularly recent college graduates who are struggling to find a job; low-income Americans who continue to rack up debt as they feel the sting of higher inflation; and even workers in creative industries, according to Pastor. “What people put on the internet or put into books is being privatized by these AI companies, making it more difficult for those same people to make money,” he said. “That’s happening to people who are authors, to people who are musicians, anyone who is a creative.” The AI hype is also skewing the health of Main Street businesses. “If you exclude AI, business investment would be actually falling, which is quite unprecedented outside of recessions,” said Maxime Darmet, senior economist at Allianz Trade. “The technology is powerful in propping up the economy, but at the same time, there’s a lot of spending being cut in more traditional areas.” Meanwhile, the gap between the broader AI-fueled economic growth and the lived reality for millions of Americans continues to widen. “The inequalities here are very, very stark,” Xavier said of San Francisco. “It’s been an issue for a long time, and I think it’s just continuing to be an issue.” By Bryan Mena

The AI Era Is Creating a New Trust Crisis at Work. Great Leaders Respond With 3 Simple Behaviors

Layoffs are back in the headlines. Across industries, companies are restructuring, reducing headcount, and redirecting resources toward AI initiatives and operational efficiency. For many leaders, the focus naturally turns to cutting costs, productivity targets, and reassuring investors. But in my experience coaching executives for more than two decades, that’s not where the biggest damage occurs. The real casualty after layoffs isn’t productivity or efficiency. It’s trust. And once trust is broken, the costs can linger long after employees are gone. What leaders often miss When layoffs occur, leaders tend to focus on the people leaving. But there’s another group leaders often overlook: the employees who stay. These employees are asking questions that rarely appear in engagement surveys. Am I next? Can I trust leadership? Does this company still care about people? Does any of this matter anymore? When those questions go unanswered, something dangerous happens. Employees stop giving their full discretionary effort. They become cautious, withhold ideas, and protect themselves. The organization may still function, but trust starts to break down. One of the biggest myths in leadership is that people lose trust because of difficult decisions. That’s rarely what I see. Employees can handle bad news. They can handle uncertainty. They can even handle layoffs. What they struggle to handle is silence. What employees want to see and hear from their leaders When leaders disappear after difficult decisions, employees fill in the blanks themselves. And human beings are remarkably good at creating worst-case scenarios. A few years ago, I worked with the CEO of a mid-sized company that had just completed a painful round of layoffs. The reductions were necessary, and to his credit, he handled the departures with empathy and respect. But once the layoffs were over, he assumed everyone wanted to move on. So the leadership team stopped talking about it. For months, employees heard almost nothing beyond routine business updates. No acknowledgment of what people had experienced. No discussion of the company’s direction. No opportunities to ask difficult questions. Within six months, the company lost several of its highest-performing employees—not because they feared another layoff, but because they no longer trusted leadership to be transparent. In exit interviews, one theme kept surfacing: “I felt like I was left to figure things out on my own.” The CEO later admitted something that stuck with me: “I thought silence would help people heal. Instead, it made them wonder what else we weren’t telling them.” That’s the thing about trust. If leaders don’t fill the communication vacuum, employees will. So, let’s say you’re a leader who wants to regain trust. That’s great. Your starting point? It’s to aways remember that trust isn’t built by protecting your people from reality; it’s built by helping your people understand reality. That’s why communication becomes even more important after layoffs than before them. Three behaviors that rebuild trust The best leaders I’ve worked with and coached consistently do three things after workforce reductions. 1. They communicate early and often Not every answer will be available. That’s okay. Employees don’t expect perfection. But they do expect honesty. Leaders who provide regular updates—even when those updates include uncertainty—create stability during unstable times. A simple message such as, “Here’s what we know, here’s what we don’t know, and here’s what we’re doing next,” can go a long way toward rebuilding confidence. 2. They acknowledge the human impact Too many leaders move immediately to business metrics after people’s livelihoods are destroyed by layoffs. Their colleagues and coworkers notice. So, before discussing strategy, be human and acknowledge loss. Recognize the contributions of those who left. Give employees permission to feel disappointment, concern, or grief. Human-centered leadership doesn’t avoid emotions in something as traumatic as a layoff. It recognizes them. 3. They create opportunities for dialogue As we have determined, the remaining employees will look to their leaders for answers. But not through company-wide announcements alone. That doesn’t build trust. Trust grows through conversations. Managers should be encouraged to ask questions like: “What concerns are you carrying right now?” “What do you need from me to be successful?” “How can I support you?” These conversations demonstrate something employees desperately need after disruption: evidence that leadership is listening. The leadership lesson Layoffs may be a business decision. But trust is, and always will be, a leadership decision. The organizations that emerge strongest from difficult periods are not necessarily the ones that cut costs most effectively. They’re the ones whose leaders understand that people are watching how decisions are made, how communication happens, and how employees are treated when things get hard. At the end of the day, employees don’t expect leaders to eliminate uncertainty. They expect leaders to help them navigate it. And that’s where trust begins. EXPERT OPINION BY MARCEL SCHWANTES, EXECUTIVE COACH, SPEAKER, AND AUTHOR @MARCELSCHWANTES

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