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Google is testing appending "learn more" links to the end of the Google search ads text. So the Google Ad will have its normal ad description and at the end, Google is testing adding "Learn more" with an arrow to the right, in blue anchor underlined text.View the full article

GMBapi posted data that looks at tens of thousands of Google Business Profiles across multiple countries and showed that review deletions have increased significantly over the year, compared to previous periods.View the full article

Google quietly updated its AI Overviews ad documentation to say that ads in AI Overviews are supported in Australia, Canada, India, Indonesia, Kenya, Malaysia, New Zealand, Nigeria, Pakistan, Philippines, Singapore, and US. Previously, it just said it was available in the US and "will expand to select English speaking countries soon."View the full article

Anish Kattukaran, CPO at Google Home & Nest announced in the Google Gemini forums that Gemini will not be replacing Google Assistant by the end of 2025. He wrote, "We're adjusting our previously announced timeline to make sure we deliver a seamless transition, and will continue our work to upgrade Assistant users to Gemini on mobile devices into 2026."View the full article

OpenAI has added local knowledge panels to the ChatGPT results. When you ask for local information and then click on a business name, ChatGPT will load a local knowledge panel on the right side.View the full article

AI has been both a blessing and a curse for small businesses. Cheaper technology means that more minor players can level up their competitiveness without having to scale rapidly, but the technology’s reliance on data raises a host of concerns about privacy. This doesn’t come as much of a surprise. The news these days is dominated by stories of data breaches that erode trust and force organizations to take drastic action to prevent further harm. More data is emerging that small businesses are successfully navigating the tightrope between embracing exciting new technology and approaching a mystifying piece of AI with caution. Earlier this year, Zoho partnered with Michael Fauscette and Arion Research to conduct a global privacy and AI survey titled, The AI Privacy Equation — Balancing Innovation with Protection in the Modern Enterprise. The study spoke to 4,782 global business professionals, 47% of which are small or medium sized businesses. Plus, 33% of the companies surveyed have less than 100 employees. The results of this survey, published in September, paint a mixed but ultimately optimistic picture of how small businesses are wading into unknown privacy terrain. Ultimately, they understand the privacy risks presented by AI and have taken steps to get out ahead of them—and as the survey says, those companies who appropriately emphasize privacy are poised to create sustainable competitive advantages. Here are some factoids from the survey and what they mean for small businesses: “When examining organizational privacy concerns, customer data breaches dominate at 40.8% of top-ranked responses.” As the study lays out, “This primary focus reflects the reality that customer data breaches carry the highest potential for reputational damage, regulatory penalties, and business disruption. Organizations understand that customer trust forms the foundation of business relationships, making customer data protection the highest privacy priority.” While larger businesses can try to perform damage control when a data privacy issue arises, small businesses do not share that luxury. Their resources are stretched too thin and the competition for customer attention to begin with is far too fierce. News of an issue can proliferate quickly and ground a small business that would otherwise have launched. Rather than act reactively, it’s up to small business owners to proactively get ahead of privacy concerns before they become even remotely a reality. This process starts by codifying a stance on data privacy to be published on the company’s website and shared far-and-wide. Once this is in place, prospective customers will be able to compare it against those of other companies when they’re conducting exploratory research, meaning that these privacy policies will become competitive differentiators. It’s far easier for a small businesses to stake a claim in data privacy than, say, promising a gargantuan customer service team or the latest flashy pieces of technology. It’s also up to small businesses to address the other two major concerns identified by the privacy survey: employee privacy (18.6%) and regulatory compliance (14.6%). Luckily, the approach doesn’t have to be all that different. By developing data privacy policies for their customers and posting these policies online, small businesses will demonstrate to employees that they take data privacy seriously (perhaps even include employees in the creation of privacy policies) and provide a framework upon which to build mechanisms to maintain compliance. “Rather than weakening privacy protection, 41.3% of organizations report significantly strengthening privacy measures since implementing AI technologies, with an additional 25.5% somewhat strengthening their privacy approaches.” It may seem counterintuitive at first that greater AI adoption would lead to stronger privacy measures. After all, much of the chatter around privacy has to do with how AI has added much complexity to the privacy formula, as understanding of the technology is sparse and regulations or governance is even sparser. But as the survey highlights, the process of implementing AI requires companies to take a deep look at their inner workings best practices. These have to be fully fleshed out so they can be articulated to an AI’s large language model (LLM), thus ensuring new AI technology works within the proper contexts to best serve the business. Often in the hustle-bustle of trying to simply keep the lights on, small businesses will forego formalizing certain processes and continue business as usual, thinking the time will come later when big-picture reflection makes the most sense. AI implementation forces that sort of thinking in the more immediate future. It’s heartening to see that companies are increasing their AI knowledge along with the rise of that technology. According to the study, 37.2% of the companies surveyed strongly agree (5 out of 5) that they clearly understand the privacy implications of their AI systems, while 33.9% said they mostly agree, rating it 4 out of 5. This demonstrates that companies are confident in their ability to venture into unknown territory rather than view AI privacy as an insurmountable challenge.To succeed moving forward, small businesses have to meet this challenge head-on. A wealth of analytics and data help with these endeavors by supplying information about each step of a company’s workflow, particularly when analyzing risk. For example, according to the study, businesses correctly identified recording customer calls, training AI models on customer interactions, and remote work were three facets of a business that carried the highest privacy risks. Analytics focused on those three areas of operations will ensure that privacy efforts remain targeted for maximum effect, shoring up critical points where exposure may occur. “Organizations face three primary barriers to successful AI implementation — privacy and security concerns (37.2%), lack of technical expertise (36.6%), and cost concerns (32.3%).” Not surprisingly, the second and third most prominent blockers of a company’s AI implementation are skills gaps and high costs. But what’s a bit surprising, and heartening, is that the leading cause of pause is related to security and privacy. This indicates that companies are, rightfully, taking these topics seriously. As previously discussed, it’s unlikely that a small business will be able to avoid AI altogether. This means that these companies must begin focusing on upskilling their employees if they haven’t already. These folks need to learn how to get the maximum benefit from AI tools and how to interpret its output to make more informed business decisions. Fittingly, the survey found that companies are prioritizing data analysis and interpretation skills (55.7%), AI literacy and understanding (47.1%), and prompt engineering capabilities (39.6%) within their workforce development initiatives. The emphasis on data analysis skills shows that AI effectiveness requires high-quality data management and interpretation capabilities. Organizations willing to invest in these foundational skills create sustainable competitive advantages in AI implementation. Small businesses would be forgiven if they felt that the above level of technical knowledge far exceeded the demands they place on their employees. But given the rapid reimagining of almost every competitive landscape, it’s always helpful for companies to learn more about what they don’t already know in order to minimize surprise disruptions. Even a survey lesson on interfacing with AI can ease the transition to new technology down the road. In conclusion The AI Privacy Equation global survey offers many more encouraging data points. It demonstrates that all businesses need to focus on privacy, not just enterprise organizations. Companies of all sizes understand that AI is a powerful tool when used ethically and sustainably, and the risks of getting it wrong are simply too high. Ultimately, what small businesses should take away from this survey is that AI privacy is not something that can be solved in one fell swoop. Instead, companies should continue to adapt as the landscape changes around them. The survey suggests that organizations are willing to tackle this challenge head-on and understand the proper investments to make along the way—prioritizing people, processes, and governance structures to ensure AI finds its footing without becoming too invasive. As with most things, patience is also a virtue to AI privacy. This article, "AI Privacy Remains an Ongoing Priority, Even for Small Businesses" was first published on Small Business Trends View the full article

AI has been both a blessing and a curse for small businesses. Cheaper technology means that more minor players can level up their competitiveness without having to scale rapidly, but the technology’s reliance on data raises a host of concerns about privacy. This doesn’t come as much of a surprise. The news these days is dominated by stories of data breaches that erode trust and force organizations to take drastic action to prevent further harm. More data is emerging that small businesses are successfully navigating the tightrope between embracing exciting new technology and approaching a mystifying piece of AI with caution. Earlier this year, Zoho partnered with Michael Fauscette and Arion Research to conduct a global privacy and AI survey titled, The AI Privacy Equation — Balancing Innovation with Protection in the Modern Enterprise. The study spoke to 4,782 global business professionals, 47% of which are small or medium sized businesses. Plus, 33% of the companies surveyed have less than 100 employees. The results of this survey, published in September, paint a mixed but ultimately optimistic picture of how small businesses are wading into unknown privacy terrain. Ultimately, they understand the privacy risks presented by AI and have taken steps to get out ahead of them—and as the survey says, those companies who appropriately emphasize privacy are poised to create sustainable competitive advantages. Here are some factoids from the survey and what they mean for small businesses: “When examining organizational privacy concerns, customer data breaches dominate at 40.8% of top-ranked responses.” As the study lays out, “This primary focus reflects the reality that customer data breaches carry the highest potential for reputational damage, regulatory penalties, and business disruption. Organizations understand that customer trust forms the foundation of business relationships, making customer data protection the highest privacy priority.” While larger businesses can try to perform damage control when a data privacy issue arises, small businesses do not share that luxury. Their resources are stretched too thin and the competition for customer attention to begin with is far too fierce. News of an issue can proliferate quickly and ground a small business that would otherwise have launched. Rather than act reactively, it’s up to small business owners to proactively get ahead of privacy concerns before they become even remotely a reality. This process starts by codifying a stance on data privacy to be published on the company’s website and shared far-and-wide. Once this is in place, prospective customers will be able to compare it against those of other companies when they’re conducting exploratory research, meaning that these privacy policies will become competitive differentiators. It’s far easier for a small businesses to stake a claim in data privacy than, say, promising a gargantuan customer service team or the latest flashy pieces of technology. It’s also up to small businesses to address the other two major concerns identified by the privacy survey: employee privacy (18.6%) and regulatory compliance (14.6%). Luckily, the approach doesn’t have to be all that different. By developing data privacy policies for their customers and posting these policies online, small businesses will demonstrate to employees that they take data privacy seriously (perhaps even include employees in the creation of privacy policies) and provide a framework upon which to build mechanisms to maintain compliance. “Rather than weakening privacy protection, 41.3% of organizations report significantly strengthening privacy measures since implementing AI technologies, with an additional 25.5% somewhat strengthening their privacy approaches.” It may seem counterintuitive at first that greater AI adoption would lead to stronger privacy measures. After all, much of the chatter around privacy has to do with how AI has added much complexity to the privacy formula, as understanding of the technology is sparse and regulations or governance is even sparser. But as the survey highlights, the process of implementing AI requires companies to take a deep look at their inner workings best practices. These have to be fully fleshed out so they can be articulated to an AI’s large language model (LLM), thus ensuring new AI technology works within the proper contexts to best serve the business. Often in the hustle-bustle of trying to simply keep the lights on, small businesses will forego formalizing certain processes and continue business as usual, thinking the time will come later when big-picture reflection makes the most sense. AI implementation forces that sort of thinking in the more immediate future. It’s heartening to see that companies are increasing their AI knowledge along with the rise of that technology. According to the study, 37.2% of the companies surveyed strongly agree (5 out of 5) that they clearly understand the privacy implications of their AI systems, while 33.9% said they mostly agree, rating it 4 out of 5. This demonstrates that companies are confident in their ability to venture into unknown territory rather than view AI privacy as an insurmountable challenge.To succeed moving forward, small businesses have to meet this challenge head-on. A wealth of analytics and data help with these endeavors by supplying information about each step of a company’s workflow, particularly when analyzing risk. For example, according to the study, businesses correctly identified recording customer calls, training AI models on customer interactions, and remote work were three facets of a business that carried the highest privacy risks. Analytics focused on those three areas of operations will ensure that privacy efforts remain targeted for maximum effect, shoring up critical points where exposure may occur. “Organizations face three primary barriers to successful AI implementation — privacy and security concerns (37.2%), lack of technical expertise (36.6%), and cost concerns (32.3%).” Not surprisingly, the second and third most prominent blockers of a company’s AI implementation are skills gaps and high costs. But what’s a bit surprising, and heartening, is that the leading cause of pause is related to security and privacy. This indicates that companies are, rightfully, taking these topics seriously. As previously discussed, it’s unlikely that a small business will be able to avoid AI altogether. This means that these companies must begin focusing on upskilling their employees if they haven’t already. These folks need to learn how to get the maximum benefit from AI tools and how to interpret its output to make more informed business decisions. Fittingly, the survey found that companies are prioritizing data analysis and interpretation skills (55.7%), AI literacy and understanding (47.1%), and prompt engineering capabilities (39.6%) within their workforce development initiatives. The emphasis on data analysis skills shows that AI effectiveness requires high-quality data management and interpretation capabilities. Organizations willing to invest in these foundational skills create sustainable competitive advantages in AI implementation. Small businesses would be forgiven if they felt that the above level of technical knowledge far exceeded the demands they place on their employees. But given the rapid reimagining of almost every competitive landscape, it’s always helpful for companies to learn more about what they don’t already know in order to minimize surprise disruptions. Even a survey lesson on interfacing with AI can ease the transition to new technology down the road. In conclusion The AI Privacy Equation global survey offers many more encouraging data points. It demonstrates that all businesses need to focus on privacy, not just enterprise organizations. Companies of all sizes understand that AI is a powerful tool when used ethically and sustainably, and the risks of getting it wrong are simply too high. Ultimately, what small businesses should take away from this survey is that AI privacy is not something that can be solved in one fell swoop. Instead, companies should continue to adapt as the landscape changes around them. The survey suggests that organizations are willing to tackle this challenge head-on and understand the proper investments to make along the way—prioritizing people, processes, and governance structures to ensure AI finds its footing without becoming too invasive. As with most things, patience is also a virtue to AI privacy. This article, "AI Privacy Remains an Ongoing Priority, Even for Small Businesses" was first published on Small Business Trends View the full article

In 2026, success belongs to marketers who turn strategy into execution, integrating AI, creativity, and community to build authority. The post The Top 10 Digital Marketing Trends For 2026 appeared first on Search Engine Journal. View the full article

Hello and welcome to Modern CEO! Each week this newsletter explores inclusive approaches to leadership drawn from conversations with executives and entrepreneurs, and from the pages of Inc. and Fast Company. If you received this newsletter from a friend, you can sign up to get it yourself every Monday morning. From technological advances and geopolitical changes to workplace culture shifts and market pressures, 2025 has been a year of change, uncertainty, and disruption. I’m Gwen Moran, and for nearly three years as Modern CEO’s editor, I’ve had a front-row seat as Mansueto Ventures CEO and Chief Content Officer Stephanie Mehta talks to business leaders and experts to help CEOs navigate the modern world. Every year, I recap some of the key insights from a year of interviews with the array of leaders featured in the newsletter. Here are four themes that we saw repeatedly in 2025. Uncertainty and change were everywhere Leaders faced nearly constant change—and more than a few curveballs—this year. When E.l.f. Beauty CEO Tarang Amin was named inaugural Modern CEO of the Year near the end of 2024, little did he know that tariffs, blowback over an influencer scandal, and attacks on the diversity efforts that E.l.f. champions were awaiting him in the coming months. When we asked CEOs to share their thoughts on leading during times of great uncertainty, we got responses representing industries from architecture to pharmaceuticals. Some of the changes we saw this year will have lasting ripple effects. Gates Foundation CEO Mark Suzman talked about closing one of the world’s largest and most well-known philanthropies over the next two decades. What had become an annual check-in with former SAIC CEO Toni Townes-Whitley was canceled after she and the company parted ways, leaving TIAA’s Thasunda Brown Duckett as the only Black woman currently leading a Fortune 500 company. AI still dominates the conversation One of the most pressing mandates many CEOs face is figuring out how to realize the potential of artificial intelligence (AI). And they were forthcoming about their opportunities and challenges this year. Weber Shandwick CEO Jim O’Leary discussed how his firm’s multifaceted AI use is giving him back what most leaders value most: time. O’Leary estimates that AI saves him one to two hours per day. This spring, Workday CEO Carl Eschenbach said the quiet part out loud when he discussed how his company made head count cuts to invest in AI. Then, during the summer, seven leading C-level execs gave us a peek at how they are using AI to do their own jobs. Regardless of their path, leaders don’t succeed in a bubble This year’s reporting showed us that there are many paths to the CEO’s office, from intern to chief financial officer—and even a comeback story as former Beautycounter CEO Gregg Renfrew took the reins at her new beauty company, Counter. Despite their different backgrounds, they have one thing in common: They need great people around them to succeed. Leaders shared insights about performance management, the importance of strategic partnerships, the challenges of keeping CEOs safe, and what happens next in diversity, equity, and inclusion initiatives. Additionally, one of our top-performing pieces was about how boards need to focus more on their No. 1 job: succession planning. Creativity and community fuel growth Modern CEO dropped dispatches from Cannes Lions in June. It was clear that this “Festival of Creativity” has grown into an important event for CEOs. As Shelley Zalis, founder and CEO of the Female Quotient, a community of women in business, put it: “Any CEO who wants to grow, innovate, and stay culturally relevant will benefit from being here.” The importance of creativity is a message AKQA Global CEO Baiju Shah discusses with the next-generation business leaders he teaches at Northwestern University. He believes that a fusion of technology and creativity is essential for businesses, especially in the age of AI. Another recurring theme in this year’s coverage was “community.” Cult brand co-CEO AJ Kumaran, who heads chicken chain Raising Cane’s, attributes his company’s success to a rigorous focus on its community. And your community includes your team, too: WorkJam CEO Steven Kramer explained how enlisting the wisdom of frontline workers can help you find market insights and solutions. What lessons did you take away from Modern CEO in 2025? Were there issues of Modern CEO that helped you or gave you something to think about this year? We’d love to hear from you. Please share your thoughts in an email message to stephaniemehta@mansueto.com. Read more: other Modern CEO highlights Conscious capitalism isn’t dead Why your company’s next CEO might be a multi-hyphenate Modern CEO readers share their thoughts on top leaders View the full article

When I talk with business leaders about Gen Z, the same frustration often bubbles up: “They won’t stay.” It’s said with a kind of bewildered shrug, as if the younger generation has suddenly rewritten the rules out of thin air. I heard it again last week during a radio segment I did about generational dynamics at work. The host asked why Gen Z feels so comfortable moving on so quickly. Here’s what I’ve learned after a decade teaching them, coaching them, and watching them navigate the workplace: Gen Z doesn’t think they’re doing anything unusual. And frankly, once you look at the data, it’s hard to argue with them. A new Youngstown State University study of 1,000 full-time U.S. professionals found that nearly half of Gen Z workers are already planning to leave their jobs—not for higher pay, but for better growth. That is the highest rate of all generations surveyed. It’s not impulsiveness. It’s not disloyalty. It’s something far more reasonable. It’s “growth hunting.” What Companies Assume—and What’s Actually Happening There’s a familiar script about young workers: They’re too quick to leave, too impatient, too everything. That narrative has been around for so long that many leaders use it as the default explanation without thinking. But when nearly one out of two early-career workers say they can’t picture a future where they are, that points to something systemic—not personal. Here’s what the data actually shows. Eighty-six percent of Gen Z say they won’t pursue upskilling unless their employer helps pay for it. That’s not a lack of drive. That’s the reality of trying to build a career while carrying historic student debt and paying rent that climbs faster than wages. Forty-three percent say they’re too burnt out to take on education outside of work. That’s not an excuse. That’s a sign that the modern workload has pushed people to their limit long before you ever ask them to add night classes. And seventy-six percent say the main thing blocking their advancement is cost—not interest, not effort, not ambition. Cost. Taken together, the message is straightforward: This generation isn’t avoiding responsibility. They’re asking employers to share it. Why Growth Hunting Makes Sense Right Now Older generations built careers around staying put and climbing step by step. That path made sense when wages matched living costs and companies offered predictable ladders. Gen Z is coming of age in a completely different economy. Careers don’t unfold in neat lines anymore. Skills expire quickly. Entire industries shift in a few years. And the price of staying competitive keeps climbing. So Gen Z does the logical thing: They move toward the places where they can grow. They’re not chasing titles. They’re chasing momentum. Every semester, I watch students who are smart, thoughtful, and deeply motivated figure out how to build a career in a landscape that changes constantly. They’re not waiting for permission. But they will absolutely walk if an employer refuses to invest in them. And honestly, that’s rational. Growth hunting is not about impatience. It’s about survival. The Leadership Miss That Keeps Repeating For years, companies have preached the language of “development” and “continuous learning.” They’ve told young employees to take initiative, expand their skills, stay ahead. Gen Z listened. And now they want to know why the bill for that development keeps landing on their doorstep. You can’t ask workers to level up and then close the door to the support they need to do it. You can’t talk about retention and then offer no path forward. You can’t position upskilling as essential and then make it unaffordable. This is where the generational disconnect becomes obvious. Companies say they want a future-ready workforce. Gen Z is asking them to mean it. A Cultural Standoff That Was Bound to Happen This feels like the moment where the values of Gen Z and the habits of corporate culture finally collide. Not because Gen Z is rebelling, but because they’re taking organizations at their word. If you say you value growth, you have to create it. If you say you care about development, you have to invest in it. Otherwise, Gen Z will simply walk toward someone who does. And here’s the twist: They don’t feel guilty about it. They’re not sneaking out the back door. They’re leaving through the front—head high—because the expectations were never mutual to begin with. What Employers Can Do This doesn’t require an overhaul. It just takes intention. And while every organization is different, here are a few approaches that can make a real difference. Put money behind upskilling. Even partial funding shifts the relationship. Make advancement transparent. When people have to guess, they eventually stop trying. Tackle burnout before talking development. Growth can’t happen when people are running on empty. Promote based on readiness rather than time served. Tenure alone doesn’t tell you who’s capable. Ask employees what growth actually means to them. The answers are often more practical than leaders expect. These aren’t the only steps, but they’re a meaningful start. And they’re far more achievable than most leaders realize. The Future Belongs to the Growth Hunters Gen Z isn’t running from work. They’re running toward growth. They know what it costs to stay still, and they’re not willing to pay that price. Not anymore. They aren’t rejecting the workplace. They’re asking it to evolve with them. When employers offer real development, this generation will show up with incredible commitment. When they don’t, Gen Z moves on with the same honesty and clarity they bring to everything else. That clarity is a gift if leaders choose to use it. Because building a workplace where people can grow isn’t just good for Gen Z. It’s good for everyone. View the full article

If a single type of building could define our present time, it would undoubtedly be the data center. Underpinning the increasingly online way we work, shop, and entertain ourselves, data centers provide the computing power and storage to handle all the Zoom calls, Amazon purchases, and Netflix streams a person can cram into their day. And now as compute-hungry artificial intelligence dominates the future of nearly every sector of the economy—and possibly society as a whole—the data center will become even more ubiquitous. A headlong data center building boom is already underway. One report finds that average monthly spending on data centers has increased 400% in the last two years, adding up to more than $50 billion in 2025 alone. One tally contends that there were more than 1,200 data centers either built or approved for construction in the U.S. by the end of 2024; another suggests the total number of data centers in the U.S. is now more than 4,100. The scale and spread of data center building is staggering, and there seems to be no end in sight. All of this is why it’s so disappointing that the design of data center architecture is, by and large, very, very boring. The typical data center looks something like this: a cluster of large, rectangular warehouses 15 or 20 feet tall, each covering about the area of a professional soccer field. The building’s walls are usually made from tilt-up concrete panels with little adornment. There are few windows, and if there were more they would look out on large outdoor clusters of equipment for cooling equipment, electricity generation, and wastewater treatment. Increasingly, the entire complex is surrounded by security fencing or even opaque walls. For anyone passing by or living in their vicinity, there may be little to see beyond the data center’s unending nighttime glow. For what could be considered the most important buildings of the decade, this is a decidedly dull aesthetic. It is the architecture of value engineering and the minimum viable product. The companies behind these facilities would argue that data centers are more like utilities or infrastructure and therefore don’t need the kind of design a more public-facing building would. But even when these data centers are not located near large communities—though many actually are—how they look can send a powerful message about their owners’ sense of responsibility for their many downsides. A missed opportunity By now, the negative externalities of big data centers are well known. From their excessive energy use to their inflationary impacts on local electricity rates to their deep thirst for water to the sheer size of their sprawling campuses, the costs of the data center building boom can feel excessively high, especially in the face of hallucinating chatbots, disinformation campaigns, and unavoidable AI slop. In this light, the warehouse design approach of most data centers is the architectural equivalent of burying one’s head in the sand, a supermax prison tucked out in the boondocks, far from any discourse over mass incarceration or human rights. The boring design of data centers is a missed opportunity to counter their negative externalities with at least a little upside. There are some data centers that are offering glimpses of what a better design could be. Some data companies and spec builders are turning to large and renowned architecture firms to add an extra layer of design to what can be fairly cookie cutter buildings meant primarily to house computers. Some designs are emphasizing natural light and natural materials in their small but important human-centric office and entry spaces. Others are prioritizing new building materials and server cooling equipment that lowers both the embedded and operational carbon impacts of the facilities. Still others are blending themselves into dense urban locations, bringing smaller scale data centers closer to specific types of users. Some look like modern office complexes. If they weren’t so big, some even look like they could hold a high end restaurant or retailer. But for every data center trying to soften its blow on society, there are dozens, if not hundreds, that are spreading as much computing power over as large an area possible that can draw in the enough resources to get the servers up and whirring as soon as possible. This looks to be the predominant developmental strategy. Design is largely an afterthought. AI companies and other so-called hyperscalers are scrambling for suitable building sites near electricity generation and transmission lines, making it likely that data centers will edge closer and closer to preexisting communities. This proximity will increase the need for more sensitive design approaches. Some better design is happening now. As the building boom carries on, much more will be needed. The companies behind the AI race have been unambiguous about AI’s potential to dramatically reshape society. If that’s true (the jury is still very much out), perhaps those companies could spend a bit more effort signaling AI’s importance by making its vast and growing physical footprint less of a total bore. View the full article

UK company strikes deal as it seeks to expand internationallyView the full article

A few weeks ago, I led a leadership workshop for a group of executive women leaders in Birmingham, Alabama. Before I begin leadership workshops, I ask the participants what they want out of our time together. This year, one answer has emerged consistently on top: connection. This isn’t surprising. As executives rise to higher levels of leadership, they often report increased feelings of loneliness. One Harvard Business Review survey found that 55% of CEOs acknowledge experiencing moderate but significant bouts of loneliness, while 25% report frequent feelings of loneliness. As your expertise becomes more specialized, it can be harder to find other leaders who understand the unique challenges of the corporate environment, with whom you can connect, learn from, and grow alongside. This is especially true for women leaders, as finding them in the senior ranks becomes less frequent the higher they climb. According to McKinsey, only 29% of C-suite leaders are women. As an entrepreneur, I’ve felt this, too. As my business grew, I realized that I didn’t have any coworkers to confide in, lean on, and seek counsel from. I had to create this network on my own. I’ve joined business groups, leadership retreats, and mastermind groups to create this support circle. THE IMPORTANCE OF A LEADERSHIP SUPPORT STRUCTURE As you advance at work, you can find yourself feeling more alone in the decision-making rooms. For example, if you manage the people who were once your peers and your relationship has evolved, this often means you can no longer rely on them for support as you used to. Challenging emotions also arise as your level of decision-making becomes larger and the stakes rise. Neuroscience research shows that when people make decisions under pressure, the brain shifts from thoughtful, deliberate thinking to more automatic, emotion-driven responses. This makes leaders more vulnerable to biased or short-term choices. However, research also shows that strong social support actually dampens the brain’s threat response under pressure, helping leaders think more clearly and make better decisions. In the era of AI, nurturing relationships is even more essential. One large-scale study on 6,000 UK employees found that technologies like AI are associated with a poorer quality of life. A 2023 analysis in Business Insider also warns that AI tools may make us lonelier at work by replacing quick check-ins with colleagues. Many of my clients echo this sentiment, saying things like, “With the rise of AI, I am constantly wondering if things are fake. Because of this, I crave real relationships more than ever.” Relationships are not only essential for combating loneliness, but they are also how deals get done, projects get awarded, and people get promoted. Here are some ways to prioritize them, even in the face of digital distraction. LEVERAGE YOUR SUPPORTERS Your supporters are the people in the organization who would advocate for you when you are not in the room (and you know it). They have your best interests at heart, and you have built solid relationship capital with them. Supporters are also the people who will give you unfiltered feedback that is focused on helping you advance. A good way to leverage your supporters is by asking them to socialize and support initiatives you may be launching. They can also play a critical role in helping you build new relationships in the organization and nurture strained relationships. However, before reaching out, consider what you can offer the relationship in return. CULTIVATE RELATIONSHIPS WITH “NEUTRALS” Neutrals are people in the organization whom you don’t know yet, or don’t know well. Maybe they are new, you are new, or you just haven’t crossed paths yet. Organizational network scholars like Ronald Burt have repeatedly shown that people whose relationships bridge otherwise disconnected groups (what he refers to as “structural holes”) receive higher performance evaluations and compensation, because they sit at key points of information and influence in the network. This is why neutrals in key stakeholder positions are critical to build relationships with. One strategy my clients enjoy using to build relationships with neutrals is called a 30:30 meeting. This is an opportunity to invite someone to a meeting or coffee. Thirty minutes are spent understanding them, their vision, goals, and offering your expertise in a way that might help them. The remaining 30 minutes are spent focused on your needs or area of expertise. The key to success in these meetings is that the focus is always on advancing shared goals and values. REBUILD CONNECTIONS WITH CHALLENGING PARTNERS Nearly every executive client I work with has one or two leaders with whom there exists some tension. It could be because individuals frequently stand in the way of their project implementations, or they consistently deny the resources they need to accomplish the work. Strained relationships are a normal occurrence when you work with people whose personalities differ from yours. However, as you advance in leadership, rebuilding these relationships will be essential to accomplish work and leverage organizational resources. To rebuild relationships, ask yourself: Do my challenging partners have good relationships with any of my supporters? Your supporters can often be bridge builders here. If you don’t have supporters who can act as bridge builders, this can be a good opportunity to cultivate and strengthen your relationship with neutrals. In times of conflict with challenging partners, it can also be helpful to focus on shared business goals and values, rather than defaulting to your fundamental differences. NURTURE YOUR NETWORK BEYOND WORK As an executive coach, the first place I direct clients to is their immediate network of leaders (old colleagues or current colleagues). However, there are also great connection opportunities that you can leverage from your loose network. The next place I encourage them to look is their industry or professional affiliated groups. Because there is a shared common interest of the type of work you do, this is a great place to foster connection through participating in conferences, meet-ups or even online forums. Another example is asking a mutual friend for an introduction to someone whose work you admire. The most effective leaders are not the most self-sufficient, but they often are the most connected. In a world where digital technology and AI are shrinking everyday interactions, relationships become your most valuable and tangible resources. View the full article

The recent announcement by McKinsey & Company that it plans to cut roughly 10% of its workforce has sent ripples through the consulting world, reigniting debate about the future of the industry. This is not about one firm, one round of layoffs, or one business cycle. It signals an irreversible shift in how value is created in consulting. Having spent a significant part of my career at McKinsey, I saw it grow and flourish in an era when information was scarce. Even basic market intelligence required large teams working for months to gather and synthesize data. The digital age brought a data explosion and democratized access, and McKinsey adapted again by expanding its capabilities into advanced analytics and technology-enabled transformation. That advantage is now under pressure in the AI age. The existential threat in the AI age While the digital age reduced information asymmetry, the AI age goes further. It increasingly equalizes analytical and recommendation capabilities. Firms like McKinsey built a powerful competitive moat by hiring the best analytical minds from top universities—excelling at data synthesis, first-principles problem-solving, and translating insight into recommendations. In the AI age, however, that advantage is becoming commoditized. This shift is part of a broader transformation of white-collar work. Contrary to early assumptions, AI is impacting knowledge work more than blue-collar roles. I expect that over the next five years, nearly 300 million white-collar jobs will be impacted globally, with around 100 million at risk of becoming obsolete. Work that is highly cognitive and already digitized is particularly susceptible. Consulting sits squarely within this zone of disruption. As the traditional consulting model faces growing pressure, the premium for future talent will no longer rest on analytical horsepower alone. The center of gravity has shifted: Consulting is being redefined The need for consulting services is not disappearing, but the source of value is shifting decisively. Traditionally, firms like McKinsey, BCG, and Bain (MBB) sat at the top of the consulting value chain through high-value strategy work. Over the years, McKinsey has invested significantly in building technology and execution capabilities, but structural challenges remain. In contrast, execution-centric firms like Deloitte, EY, and Accenture, built with a different DNA, were able to more naturally combine advisory with technology and large-scale execution. The growth numbers speak for themselves. While the MBB firms have reported slower growth, averaging approximately 5% to 6% compound annual growth rate, implementation-led firms such as Accenture, Deloitte, and EY have grown approximately 11% to 12% in recent years (average growth estimated based on revenues from company websites, annual reports, press releases, and analyst reports), reflecting the direction of client spend. Historically, strategy was viewed as the highest-value activity, and execution was treated as a follow-on—largely organizational and operational in nature. In the digital and AI age, execution is deeply technology-driven, and strategy and execution are no longer sequential but iterative and continuous. From being an enabler, technology has become the primary driver of both strategy and execution. Clients increasingly want partners who can bridge strategy, technology, and operations, and execute change at scale. Consulting firms, including the Big Four, have responded by reshaping their talent and operating models around large-scale execution and organizational transformation. The Battle of Relevance in the AI age: Where does McKinsey stand? The key question now is: Who will emerge as winners in this new consulting landscape? As the center of gravity shifts toward execution depth and the ability to drive continuous change, success will depend on how effectively firms rewire their DNA—building the operating model and talent engine required to implement and scale tech-led transformation. While strategy remains critical in the AI age, it demands a higher bar. As AI takes over analysis and recommendations, strategic advantage shifts from problem-solving to sense-making—from humans “in the loop” to humans “above the loop.” My bet is that two types of firms are best positioned to win. First, there are firms like Accenture, Deloitte, and EY, which have built strong execution capabilities and successfully strengthened their technology foundations. Second, there are industry specialists with exceptional domain expertise, where deep contextual understanding becomes the primary source of differentiation. Where does that leave McKinsey? While its brand, client relationships, global reach, and intellectual capital remain as formidable strengths, the transformation challenge it faces may be far greater than what it advises its clients on. Meeting it will require more than just new capabilities. It requires a structural reset, beginning with a mindset shift—from authority rooted in expertise to leadership grounded in learning and adaptability. Whether McKinsey retains its position at the top will depend on how effectively it embraces this shift. In the AI age, even the most storied institutions must continuously reinvent themselves—or risk being outpaced by those that do. View the full article

Our experts expect a mortgage market reset in 2026 with an uptick in originations, but warn lenders not to skimp on compliance even as the reins loosen. View the full article

In 1939, Simon & Schuster revolutionized the American publishing industry with the launch of Pocket Books, a line of diminutive volumes (measuring 4 by 6 inches) that cost only a quarter; a significant discount at a time when a typical hardcover book would ​set you back​ between $2.50 and $3.00. To make the economics of this new model work, Simon & Schuster had to move a huge volume of units. “[They] sold books where they had never been available before–grocery stores, drugstores and airport terminals,” explains Clive Thompson in ​a fascinating 2013 article​ about the Pocket Books phenomenon. “Within two years, [they’d] sold 17 million.” Thompson quotes the historian Kenneth C. Davis, who explains that these new paperbacks had “tapped into a huge reservoir of Americans who nobody realized wanted to read.” This demand, however, created a problem: there weren’t enough books to sell. In 1939, the book market was relatively small. (Thompson estimates that around this time, America had only 500 bookstores, almost exclusively clustered around a dozen major cities.) To make money on paperbacks, the pipeline of new titles released each year would need to increase drastically. This, in turn, required a significant loosening of the standards for what was worthy of publication, leading, among other changes, to the sudden prioritization of genre fiction writers who could churn out serviceable potboilers at a rapid clip. (Interestingly, this new class of writers included a young Michael Crichton, who, during his years as a medical student at Harvard in the 1960s, published preposterous paperback adventure novels under pseudonyms, which he finished by working at “​a furious pace​” on weekends and vacations. I’ve read some of ​these early works​, and they’re mainly mediocre. But that wasn’t a problem, as the goal for many such paperbacks was simply to provide disposable distraction.) Predictably, the new prominence of these lower-quality genres concerned the elite class. Thompson quotes the social critic Harvey Swados, who described the paperback revolution as ushering in a “flood of trash” that would “debase farther the popular taste.” There was a fear that the mass appeal of these cheap books would eventually lead to the elimination of the more serious hardcover titles that had long defined publishing. Here we find a parallel to our current moment. As the platforms of the digital attention economy transition from social network models to providing maximally distracting short-form videos, more of the content available online is devolving toward that paragon of low-quality forgettability, commonly referred to as slop. Who will listen to a podcast or read a long essay, many now fret, when Sora can offer countless videos of historical figures dancing and X can deliver an endless sequence of nudity and bar fights? If we return to the paperback example, however, we might find a small sliver of hope. Ultimately, the explosion of these cheaper, often lower-quality books didn’t lead to the elimination of more serious titles. In fact, the opposite happened. Vastly more hardcover titles are published today than they were before the Pocket Books revolution began. A closer look reveals that by vastly increasing the market for the published word, paperbacks also vastly increased the opportunities to make a living writing serious books (which, for the sake of this discussion, I’ll define as books that require at least a year to write and are published in hardcover). There was, to be sure, a lot of trash put out during the heyday of the paperback, but this reconfigured publishing model also generated a lucrative secondary market for more traditional writers. Stephen King, for example, sold the hardcover rights to his first novel, Carrie, for around $2,500 in 1973 ($18,000 in today’s dollars). This was a nice bonus, but hardly enough to live on. The paperback rights for Carrie, by contrast, sold for $400,000 (almost $3,000,000 in today’s dollars), allowing King to quit his day job and become a full-time writer. King wasn’t alone; other acclaimed authors, from Ursula K. Le Guin to Ray Bradbury, to Agatha Christie, also would have never risen to such prominence without the opportunities provided by the paperback world. As for Crichton, we know what happened next. The nine, mostly cheesy paperbacks, he wrote using pseudonyms, helped him polish his craft. His first hardcover book, The Andromeda Strain, was a massive bestseller and initiated the beginning of a career as one of the most influential writers of his generation. As you know, I strongly dislike much of the current digital attention economy, and I believe that most people should be spending vastly less time engaging with these products. But in the spirit of trying to end 2025 on an optimistic note, I find some solace in the story of paperback books. Just because a certain type of low-quality media becomes immensely popular doesn’t necessarily mean that the deeper alternatives will suffer. Over one billion TikTok videos will be viewed today, and yet, you’re still here, reading a speculative essay about media economics. I don’t take that for granted. The post On Paperbacks and TikTok appeared first on Cal Newport. View the full article

Resilience is a much-needed skill in today’s tough job market. Despite the headlines lambasting young employees as “lazy” and “entitled”, a Big Four consulting firm is taking matters into its own hands and offering training for recent grads. PwC will give its new young hires “resilience” training to toughen them up for careers as management consultants. The firm has introduced the initiative in the UK to help Gen Z brush up on their “human skills,” including communication with clients and handling day-to-day work dynamics, like pressure or criticism. “Quite often we are struck that the graduates that join us… don’t always have the resilience; they don’t always have the human skills that we want to deploy onto the client work we pass them towards,” Phillippa O’Connor, PwC’s chief people officer told The Sunday Times. Resilience requires, among other things, the ability to withstand, adapt or recover quickly from the challenges and inevitable setbacks that come with everyday work and life. A recent study by the McKinsey Health Institute shows that those who report high levels of resilience or adaptability show better holistic health and higher engagement than their peers. But simply telling employees to “be more resilient” and “toughen up” isn’t likely to achieve much. When the path forward is unclear, research shows that teams and employees default to what they already know: regardless of whether it’s the best approach. O’Connor isn’t alone; the notion of Gen Z (and younger millennials) lacking in the resilience department is one that’s popped up across the general discourse. Growing up as digital natives, missing formative in-person experiences during COVID, and now entering hybrid or remote-first workplaces, many young professionals simply didn’t get the chance to build and exercise certain human or “soft” skills. And no amount of resilience training can compensate for a broken workplace. Studies show that resilience may help in low-pressure settings, but in environments with overwhelming workloads and toxicity, it becomes both ineffective and even harmful. As companies gut layers of middle management, Gen Z hires are increasingly left reporting to stretched, exhausted managers with neither the time nor the bandwidth to offer the close, hands-on guidance they need. As companies continue to gut middle management, new hires find themselves reporting to overworked, burnt-out managers who lack the capacity for the hands-on support they need. Now a number of companies, like PwC, are addressing these concerns head on. Last month the accountancy giant Azets revealed it is exploring partnerships with major hotel, pub, and restaurant chains to offer temporary work assignments for trainee accountants and improve their soft skills. In 2023, fellow “Big Four” consulting firm KPMG supplied classes on ‘soft skills’ for its Gen Z recruits who graduated during the pandemic, out of concern they were struggling to adapt to professional life. Surviving a global pandemic during their formative years, thrown into a tumultuous job market, and faced with relentless criticism from those on higher rungs of the corporate ladder, Gen Z have more than demonstrated their resilience. Now? They’re looking for support. View the full article

In 1939, Simon & Schuster revolutionized the American publishing industry with the launch of Pocket Books, a line of diminutive volumes (measuring 4 by 6 inches) that cost only a quarter; a significant discount at a time when a typical hardcover book would ​set you back​ between $2.50 and $3.00. To make the economics of this new model work, Simon & Schuster had to move a huge volume of units. “[They] sold books where they had never been available before–grocery stores, drugstores and airport terminals,” explains Clive Thompson in ​a fascinating 2013 article​ about the Pocket Books phenomenon. “Within two years, [they’d] sold 17 million.” Thompson quotes the historian Kenneth C. Davis, who explains that these new paperbacks had “tapped into a huge reservoir of Americans who nobody realized wanted to read.” This demand, however, created a problem: there weren’t enough books to sell. In 1939, the book market was relatively small. (Thompson estimates that around this time, America had only 500 bookstores, almost exclusively clustered around a dozen major cities.) To make money on paperbacks, the pipeline of new titles released each year would need to increase drastically. This, in turn, required a significant loosening of the standards for what was worthy of publication, leading, among other changes, to the sudden prioritization of genre fiction writers who could churn out serviceable potboilers at a rapid clip. (Interestingly, this new class of writers included a young Michael Crichton, who, during his years as a medical student at Harvard in the 1960s, published preposterous paperback adventure novels under pseudonyms, which he finished by working at “​a furious pace​” on weekends and vacations. I’ve read some of ​these early works​, and they’re mainly mediocre. But that wasn’t a problem, as the goal for many such paperbacks was simply to provide disposable distraction.) Predictably, the new prominence of these lower-quality genres concerned the elite class. Thompson quotes the social critic Harvey Swados, who described the paperback revolution as ushering in a “flood of trash” that would “debase farther the popular taste.” There was a fear that the mass appeal of these cheap books would eventually lead to the elimination of the more serious hardcover titles that had long defined publishing. Here we find a parallel to our current moment. As the platforms of the digital attention economy transition from social network models to providing maximally distracting short-form videos, more of the content available online is devolving toward that paragon of low-quality forgettability, commonly referred to as slop. Who will listen to a podcast or read a long essay, many now fret, when Sora can offer countless videos of historical figures dancing and X can deliver an endless sequence of nudity and bar fights? If we return to the paperback example, however, we might find a small sliver of hope. Ultimately, the explosion of these cheaper, often lower-quality books didn’t lead to the elimination of more serious titles. In fact, the opposite happened. Vastly more hardcover titles are published today than they were before the Pocket Books revolution began. A closer look reveals that by vastly increasing the market for the published word, paperbacks also vastly increased the opportunities to make a living writing serious books (which, for the sake of this discussion, I’ll define as books that require at least a year to write and are published in hardcover). There was, to be sure, a lot of trash put out during the heyday of the paperback, but this reconfigured publishing model also generated a lucrative secondary market for more traditional writers. Stephen King, for example, sold the hardcover rights to his first novel, Carrie, for around $2,500 in 1973 ($18,000 in today’s dollars). This was a nice bonus, but hardly enough to live on. The paperback rights for Carrie, by contrast, sold for $400,000 (almost $3,000,000 in today’s dollars), allowing King to quit his day job and become a full-time writer. King wasn’t alone; other acclaimed authors, from Ursula K. Le Guin to Ray Bradbury, to Agatha Christie, also would have never risen to such prominence without the opportunities provided by the paperback world. As for Crichton, we know what happened next. The nine, mostly cheesy paperbacks, he wrote using pseudonyms, helped him polish his craft. His first hardcover book, The Andromeda Strain, was a massive bestseller and initiated the beginning of a career as one of the most influential writers of his generation. As you know, I strongly dislike much of the current digital attention economy, and I believe that most people should be spending vastly less time engaging with these products. But in the spirit of trying to end 2025 on an optimistic note, I find some solace in the story of paperback books. Just because a certain type of low-quality media becomes immensely popular doesn’t necessarily mean that the deeper alternatives will suffer. Over one billion TikTok videos will be viewed today, and yet, you’re still here, reading a speculative essay about media economics. I don’t take that for granted. The post On Paperbacks and TikTok appeared first on Cal Newport. View the full article

A group of college students braved the frigid New England weather on Dec. 13, 2025, to attend a late afternoon review session at Brown University in Providence, Rhode Island. Eleven of those students were struck by gunfire when a shooter entered the lecture hall. Two didn’t survive. Shortly after, a petition circulated calling for better security for Brown students, including ID-card entry to campus buildings and improved surveillance cameras. As often happens in the aftermath of tragedy, the conversation turned to lessons for the future, especially in terms of school security. There has been rapid growth of the nation’s now US$4 billion school security industry. Schools have many options, from traditional metal detectors and cameras to gunshot detection systems and weaponized drones. There are also purveyors of artificial-intelligence-assisted surveillance systems that promise prevention: The gun will be detected before any shots are fired, and the shooting will never happen. They appeal to institutions struggling to protect their communities, and are marketed aggressively as the future of school shooting prevention. I’m a criminologist who studies mass shootings and school violence. In my research, I’ve found that there’s a lack of evidence to support the effectiveness of these technological interventions. Grasping for a solution Implementation has not lagged. A survey from Campus Safety Magazine found that about 24% of K-12 schools report video-assisted weapons detection systems, and 14% use gunshot detection systems, like ShotSpotter. Gunshot detection uses acoustic sensors placed within an area to detect gunfire and alert police. Research has shown that gunshot detection may help police respond faster to gun crimes, but it has little to no role in preventing gun violence. Still, schools may be warming to the idea of gunshot detection to address the threat of a campus shooter. In 2022, the school board in Manchester, New Hampshire, voted to implement ShotSpotter in the district’s schools after a series of active-shooter threats. Other companies claim their technologies provide real-time visual weapons detection. Evolv is an AI screening system for detecting concealed weapons, which has been implemented in more than 400 school buildings since 2021. ZeroEyes and Omnilert are AI-assisted security camera systems that detect firearms and promise to notify authorities within seconds or minutes of a gun being detected. These systems analyze surveillance video with AI programs trained to recognize a range of visual cues, including different types of guns and behavioral indicators of aggression. Upon recognizing a threat, the system notifies a human verification team, which can then activate a prescribed response plan. But even these highly sophisticated systems can fail to detect a real threat, leading to questions about the utility of security technology. Antioch High School in Nashville, Tennessee, was equipped with Omnilert’s gun detection technology in January 2025 when a student walked inside the school building with a gun and shot several classmates, one fatally, before killing himself. Lack of evidence This demonstrates an enduring problem with the school security technology industry: Most of these technologies are untested, and their effect on safety is unproven. Even gunshot detection systems have not been studied in the context of school and mass shootings outside of simulation studies. School shooting research has very little to offer in terms of assessing the value of these tools, because there are no studies out there. This lack is partly due to the low incidence of mass and school shootings. Even with a broad definition of school shootings—any gunfire on school grounds resulting in injury—the annual rate across America is approximately 24 incidents per year. That’s 24 more than anyone would want, but it’s a small sample size for research. And there are few, if any, ethically and empirically sound ways to test whether a campus fortified with ShotSpotter or the newest AI surveillance cameras is less likely to experience an active shooter incident because the probability of that school being victimized is already so low. Existing research provides a useful overview of the school safety technology landscape, but it offers little evidence of how well this technology actually prevents violence. The National Institute of Justice last published its Comprehensive Report on School Safety Technology in 2016, but its finding that the adoption of biometrics, “smart” cameras, and weapons detection systems was outpacing research on the efficacy of the technology is still true today. The Rand Corporation and the University of Michigan Institute for Firearm Injury Prevention have produced similar findings that demonstrate limited or no evidence that these new technologies improve school safety and reduce risks. While researchers can study some aspects of how the environment and security affect mass shooting outcomes, many of these technologies are too new to be included in studies, or too sparsely implemented to show any meaningful impact on outcomes. My research on active and mass shootings has suggested that the security features with the most lifesaving potential are not part of highly technical systems: They are simple procedures like lockdowns during shootings. The tech keeps coming Nevertheless, technological innovations continue to drive the school safety industry. Campus Guardian Angel, launched out of Texas in 2023, promises a rapid drone response to an active school shooter. Founder Justin Marston compared the drone system to “having a SEAL team in the parking lot.” At $15,000 per box of six drones, and an additional monthly service charge per student, the drones are equipped with non-lethal weaponry, including flash-bangs and pepper spray guns. In late 2025, three Florida school districts announced their participation in Campus Guardian Angel’s pilot programs. Three school districts in Florida are part of a pilot program to test drones that respond to school shootings. There is no shortage of proposed technologies. A presentation from the 2023 International Conference on Computer and Applications described a cutting-edge architectural design system that integrates artificial intelligence and biometrics to bolster school security. And yet, the language used to describe the outcomes of this system leaned away from prevention, instead offering to “mitigate the potential” for a mass shooting to be carried out effectively. While the difference is subtle, prevention and mitigation reflect two different things. Prevention is stopping something avoidable. Mitigation is consequence management: reducing the harm of an unavoidable hazard. Response versus prevention This is another of the enduring limitations of most emerging technologies being advertised as mass shooting prevention: They don’t prevent shootings. They may streamline a response to a crisis and speed up the resolution of the incident. With most active shooter incidents lasting fewer than 10 minutes, time saved could have critical lifesaving implications. But by the time ShotSpotter has detected gunshots on a college campus, or Campus Guardian Angel has been activated in the hallways of a high school, the window for preventing the shooting has long since passed. Emily Greene-Colozzi is an assistant professor of criminology and justice studies at UMass Lowell. This article is republished from The Conversation under a Creative Commons license. Read the original article. View the full article

Vulnerability in Redirection For Contact Form 7 WordPress Plugin affects up to 300,000 installations The post Redirection For Contact Form 7 WordPress Plugin Vulnerability appeared first on Search Engine Journal. View the full article

As the Consumer Electronics Show (CES) returns to Las Vegas from Jan. 6 to 9, the tech industry is gearing up for its annual spectacle of prototypes, silicon benchmarks and AI-branded gadgets. But one of the most consequential shifts in enterprise technology over the coming year will unfold far from the keynote stages and demo floors. HP, the 85-year-old Silicon Valley company long defined by PCs, printers, and enterprise hardware, is repositioning itself as a work-intelligence platform—where devices learn continuously, services anticipate needs, and AI dissolves the traditional boundaries between hardware, software, and the cloud. Under Jim Nottingham, senior vice president and division president of Advanced Compute Solutions, HP is treating AI not as a feature or a marketing layer but as a structural force reshaping how the company builds products, manages its supply chain, and generates revenue. As enterprise spending shifts toward intelligent, autonomous systems, that strategy is becoming central to HP’s future and to whether it can compete with contemporaries, including Dell and Lenovo on devices, while holding its ground against Microsoft and the cloud hyperscalers that control workplace software, data and AI workflows. Nottingham said HP’s transformation began with an uncomfortable realization that “work was not working as well as it should.” Customers had raised these issues for years, but the true scale of the problem became clear only after HP measured it through its 2025 Work Relationship Index. The findings were striking as just 20% of knowledge workers say they have a healthy relationship with work, meaning most feel overwhelmed by fragmented tools, constant interruptions and systems that make work harder rather than more productive. “We heard versions of this from customers across industries and geographies,” Nottingham says. “When you have visibility across millions of devices and organizations of every size, patterns like this become impossible to miss.” Those insights forced HP to confront a deeper truth about AI. “You can’t just add AI to a device and call it transformation.” Instead, HP rethought how devices, software, services and management systems work together across an entire workday. The shift cut across personal systems, print and services at the same time, pushing the company toward a single, platform-led vision of the future of work rather than three separate roadmaps. “At CES, we’ll demonstrate that platform-led view across the portfolio,” Nottingham says. “AI became the organizing principle because it’s the first technology capable of tying those pieces together and enabling work environments that are more adaptive, secure, and intelligent.” From hardware economics to intelligence at scale HP’s reinvention comes at a moment of pressure. Hardware margins are shrinking as devices commoditize, while hyperscalers increasingly control enterprise workflows and set the bar for intelligent work systems. HP’s counter is scale. Few companies span endpoints, managed fleets, printing infrastructure, and workforce software at a global reach. HP is betting that AI layered across that footprint can drive higher-margin services and recurring revenue without forcing customers to replace existing systems. Recent financial results help explain the company’s confidence. In the fourth quarter of fiscal 2025, the company reported revenue growth of 4% year over year, driven largely by strength in Personal Systems. AI PCs accounted for more than 30% of shipments during the quarter, and HP expects that share to approach 50% next year. Subscription and services businesses now generate billions of dollars in annual recurring revenue, reinforcing a shift away from one-time device sales toward a more durable, platform-driven business model. Industry experts argue that this shift reflects where enterprise computing is headed, but execution is what separates leaders from laggards. Pierre Baqué, CEO and founder of Neural Concept, said meaningful AI transformation requires intelligence to be embedded into system design from the outset, accounting for real-world constraints and tradeoffs. “The future of enterprise computing is about leveraging intelligent, AI applications that learn and adapt across the full lifecycle, improving how engineering teams accelerate and validate their operations,” says Baqué. HP’s AI PCs are built around that philosophy. The systems integrate neural processing units that run AI workloads locally, enabling real-time inference without constant reliance on the cloud. The payoff is lower cost, faster performance and stronger privacy—advantages that matter in regulated industries and bandwidth-constrained environments, and that distinguish HP’s approach from cloud-first Copilot PCs and consumer-led AI designs from Apple and Qualcomm. “For specialized workers inside companies—the people responsible for the most complex and demanding workflows—the stakes are much higher,” Nottingham adds. “Whether the work involves generative AI, simulation or data science, our solutions streamline complex workflows, remove friction and help increase productivity.” A different competitive wager HP is embedding AI across categories competitors often treat separately, including AI PCs, workstations, printing and device management. Print AI applies generative models to formatting, security and intent recognition—an area few expected to see meaningful AI impact. In AI PCs, documents, meetings and workflows can be queried instantly, while tasks such as video editing and image processing shrink from minutes to seconds, even offline. “By enabling hybrid compute that combines local responsiveness through AI with cloud scale, we are helping these teams work faster and more effectively without disrupting their flow,” Nottingham says. He added that AI PCs now make up a growing share of HP’s shipments, and adoption is accelerating. “It reflects where enterprise computing already is, not where it might be someday.” HP’s transformation raises a larger question for the industry: If a company with HP’s scale and legacy must become intelligent to stay competitive, what does that mean for every other maker of work devices? Autumn Stanish, a director analyst at Gartner, says the industry’s shift from device-driven revenue to software, services and lifecycle-based models has been inevitable. “This has been inevitable for a long while now, and a very slow transition for the hardware industry,” she said, as longer device lifecycles and price pressure eat into traditional hardware profits. “Device pricing isn’t going rise enough…to make up for that lost revenue,” pushing companies to look beyond selling PCs and other systems. She notes that HP’s expansion into digital employee experience tools such as DXP, along with managed device lifecycle services now offered by HP, Dell and Lenovo, reflects where competition is moving. “Cloud AI processing is expensive for providers and customers alike,” she added, making local, on-device intelligence increasingly essential. The future of work, then, may arrive not through spectacle, but through quiet reinvention—where AI fades into the background and systems adapt to how work actually happens. View the full article

At 10:24 p.m., while brushing his teeth, my husband’s phone pings. It’s not an emergency. No one is bleeding. No building is on fire. It’s an email that begins with the words, “Just circling back.” In France, this would be illegal. Or at least deeply frowned upon. Since 2017, French workers at companies with more than 50 employees have had a legally protected right to disconnect. That means, employers can’t expect workers to answer emails or messages after hours. Similar policies exist across Europe, including Spain, Belgium, and Greece. Meanwhile, in America, we’re circling back at bedtime. The Country That Turned “Always On” Into a Personality Trait In theory, Americans love freedom. In practice, we seem to love productivity even more. Historically, we don’t just work, we identify with our work. We humblebrag about being slammed. We apologize for vacations. We wear burnout like a well-earned Miss America crown. The unspoken rule is clear: If you’re not reachable, you’re not serious. I’ve interviewed hundreds of working parents over the years, and one thing comes up again and again: It’s not just the workload that is crushing them, it’s the anticipation of it. The constant low-grade anxiety that an email could arrive at any moment. That their boss might “just need one thing.” Silence could be interpreted as laziness. Work doesn’t end anymore. It’s like the constant background noise of our personal lives. America’s Love Affair with Hustle Culture (and Why We Can’t Quit It) Here’s the uncomfortable truth: We don’t just tolerate hustle culture, we reward it. We promote the people who respond fastest. We praise the ones who “go above and beyond.” We quietly penalize the ones who protect their time, especially women and parents. Especially mothers. Disconnecting in America isn’t seen as healthy; it’s seen as risky. And that’s the difference between us and Europe. In France, disconnecting is a labor right. In the U.S., it’s a personal boundary you have to negotiate politely without inconveniencing anyone important. Good luck with that. The Myth That Availability Equals Value One of the biggest lies of modern work is that responsiveness equals commitment. But study after study shows the opposite. Constant availability leads to burnout, cognitive fatigue, poorer decision-making, and lower creativity. When your brain never powers down, it doesn’t perform better; it performs worse. And yet, here we are. Answering emails from the sidelines of the soccer field and Slack-ing during bedtime. We’ve turned the ability to be interrupted into a marketable job skill. So, Could a Right to Disconnect Ever Work Here? Legally? Maybe. Culturally? That’s a higher hurdle. Because America’s resistance to disconnecting isn’t just about logistics. It’s about identity. Work isn’t just what we do; it’s who we are. For many of us, especially in an economy as frighteningly precarious as ours, being reachable feels like job protection. Until we change what we reward, no policy will fully save us. A right to disconnect would only work in America if we stopped confusing exhaustion with ambition and availability with worth. What Would Real Progress Actually Look Like? I’m not sure legislation is enough for a cultural shift. We will need leaders who model boundaries instead of martyrdom. With companies that measure output rather than online status. With workplaces that understand rest isn’t the enemy of success; it’s the fuel. And maybe, just maybe, it would start with all of us resisting the urge to “circle back” at 10:24 p.m.. The French have a phrase for this: la vie. It’s the part of life that happens after work. In America, we call it being unreachable, and we are still not sure we are allowed to be. View the full article

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Everybody loves the idea of feedback, defined broadly as information provided to someone about their performance, behavior, or actions. This makes a great deal of sense. Indeed, many studies have consistently shown that feedback from others plays an important role in helping us understand who we are, including how we differ from others. It is vital for improving managers’ and leaders’ performance and for helping people evolve and develop, both professionally and personally. Conversely, being feedback-deprived, or having a tendency to ignore it, increases the gap between how good you think you are, and how good you actually are—at times, to painfully delusional levels. And yet, people often fail to accept and internalize feedback. This is particularly true when the feedback is misaligned with how we view ourselves or at odds with what we think about the situation. Contributing to this failure is often the poor quality of the feedback, due to factors ranging from sender expertise and intention to the politics and bias of subjective character evaluations. Unsurprisingly, meta-analytic evidence suggests that 1/3 of feedback interventions are ineffective, and another 1/3 actually worsen recipients’ performance. Feedback, in short, has a poor track record. And especially poor for more senior leaders. High-quality feedback is thus particularly scarce where it is needed the most—for those whose decisions and actions have the most far-reaching impact: in senior leadership. Why is this the case? The reasons First, when someone is powerful, others will go to great lengths to avoid upsetting or confronting that person, aware (consciously and not) that leaders have some power over their future, which explains why it is far more common for leaders to hear praise and compliments from subordinates than constructive criticism. A darkly comic illustration appears in Armando Ianucci’s movie The Death of Stalin. When Stalin collapses, his inner circle hesitates, panics, and second-guesses itself, terrified of acting without explicit permission. No one dares to take responsibility, question assumptions, or deliver unwelcome truths. The satire works precisely because it exaggerates a real dynamic: when power is concentrated and fear is high, feedback disappears, initiative dies, and silence becomes the safest strategy. Second, hierarchical cultures and traditional leadership archetypes conspire against leaders’ ability to create the necessary psychological safety for candor. Unless effort is put into creating these conditions, team members will perceive a negative cost-benefit analysis when it comes to voicing issues—especially with their leader’s decisions or behaviors—versus holding back and staying silent. While this may boost leaders’ egos, fostering self-enhancing and delusional estimates of their own talents—it will severely limit their ability to improve and get better. How can anyone, including a manager or leader, get better if they are unaware of a gap between their self-views and their actual performance? Why would anyone, including a manager or leader, seek to change and evolve if their perception is that everything is fine? Third, when someone seems devoid of self-awareness, to the point of being not just immune to feedback, but almost un-coachable, people will see no point in providing them with feedback, as it would be wasted on them. Unfortunately, when others are of the opinion that leaders are incompetent, and that, on top of that, they are totally unaware of this fact, they lose respect for that leader and approach their interactions with them as they would with a delusional narcissist or mad person. What to do Fortunately, there is a booming industry (at times comprising science-based instruments like evidence-based 360-degree feedback surveys and personality assessments) to tell leaders what they need to hear, especially when that’s not what they want to hear. Even in the absence of such instruments, here are five simple ways leaders can get better at receiving—and ingesting—constructive feedback. Ask for disconfirming data, not general impressions Instead of “Any feedback for me?”, ask narrowly framed questions that invite contradiction, such as “What is one decision I made recently that slowed the team down?” or “Where did my involvement add least value this quarter?” Research on feedback seeking shows that specific, behavior-linked requests increase both the honesty and usefulness of responses, while vague requests elicit politeness and noise rather than signal. Separate ingestion from reaction, deliberately and visibly High-status leaders often kill feedback not by rejecting it, but by reacting too fast. A defensive facial expression, explanation, or “contextual clarification” is usually enough to shut people down. Evidence from self-regulation and feedback intervention research shows that feedback is more likely to improve performance when recipients force themselves to pause evaluation and treat feedback as data, not judgment. One practical move is to explicitly say, “Thank you. I won’t respond now, so I can think about what you’ve said, and I’ll come back to you,” and then actually do so. Triangulate patterns, ignore anecdotes Single pieces of feedback are typically biased, idiosyncratic, or situational. Leaders should resist reacting to one voice and instead look for recurring themes across sources, time, and contexts. Meta-analytic work on 360-degree feedback consistently shows that behavior change is most likely when leaders focus on convergent signals rather than isolated comments. Treat feedback like data analysis, not testimony. Outsource truth-telling when power gets in the way At senior levels, the social cost of honesty becomes prohibitive. This is precisely why structured mechanisms such as anonymous upward feedback, external coaching, or validated personality and derailment assessments outperform informal conversations. Research on power and voice shows that hierarchy systematically suppresses upward dissent unless safeguards are in place. Leaders who believe their “open-door policies” are adequate are usually the least informed. Publicly act on one small piece of feedback, fast The strongest signal that feedback is welcome is not just saying “thank you,” but visibly changing something. Even a modest adjustment, communicated explicitly (“Based on your feedback, I’ll stop doing X and start doing Y”), recalibrates the perceived cost-benefit of speaking up. Evidence from psychological safety research shows that follow-through, not receptiveness rhetoric, predicts future voice behavior. Feedback cultures are built behavior by behavior, not intention by intention. Taken together, these practices treat feedback less as a moral virtue and more as an imperfect but essential data stream. Leaders who learn to filter, metabolize, and act on that data gain something far rarer than praise: a realistic picture of their impact. View the full article

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