Extractive summaries and key takeaways from the articles carefully curated from TOP TEN BUSINESS MAGAZINES to promote informed business decision-making | Since 2017 | Week 430, covering December 5-11, 2025 | Archive
Shaping Section
India’s Digital Dream, Hacked
By Natalie Obiko Pearson and Suparna Sharma | Bloomberg Businessweek | December 5, 2025
3 key takeaways from the article
- Aadhaar—a new biometric identification system spearheaded by Nandan Nilekani, co-founder of tech giant Infosys. Until 2010, India had no equivalent to the US Social Security number. Many people—mostly poor, often rural—couldn’t prove their identity and were thereby shut out of the formal economy. They couldn’t buy a SIM card, open a bank account or access government benefits. Aadhaar, meaning “foundation,” changed that, issuing a unique 12-digit number linked to a person’s fingerprints and iris scan.
- Registering 1.3 billion people in Aadhaar proved fiendishly complex. The fingerprints and iris scans of each new registrant had to be compared against those of all previous registrants. To speed the process, the government turned to private operators like Baharat.
- The Aadhaar program was lauded by experts for its scalability and security. But it had a fundamental flaw: India had created a lockbox, yet kept giving a peek inside—to telecom companies, banks, courier companies, airlines, you name it. For about $3.50, private operators like Bharat had bought access to a database containing the private details of a billion-plus people, one of the biggest data breaches of all time, and no one cared.
(Copyright lies with the publisher)
Topics: Aadhaar, India’s Digital ID System, Huamns & Technology
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Over the previous two decades, India had shifted from landlines to mobile phones, but cellular services remained too costly to bring India fully online. Then came Mukesh Ambani—Asia’s richest man, famed for spotting opportunities—who upended the market in late 2016 with Reliance Jio. His nationwide 4G network slashed data costs to the world’s lowest, putting high-speed internet within reach of anyone with a cheap smartphone. Prime Minister Modi, too, pledged to knit the country together with high-speed networks under an initiative called Digital India.
The bedrock for that transition was Aadhaar—a new biometric identification system spearheaded by Nandan Nilekani, co-founder of tech giant Infosys. Until 2010, India had no equivalent to the US Social Security number. Many people—mostly poor, often rural—couldn’t prove their identity and were thereby shut out of the formal economy. They couldn’t buy a SIM card, open a bank account or access government benefits. Aadhaar, meaning “foundation,” changed that, issuing a unique 12-digit number linked to a person’s fingerprints and iris scan.
Registering 1.3 billion people in Aadhaar proved fiendishly complex. The fingerprints and iris scans of each new registrant had to be compared against those of all previous registrants. To speed the process, the government turned to private operators like Baharat.
Business was brisk. Aadhaar was supposed to be voluntary, but its expediency soon made it a de facto requirement for everything: buying a car, tracking a lost Amazon package, registering on a matchmaking website, getting treated at a hospital. People across the country lined up for an Aadhaar number.
At first, Bharat’s was the only kiosk in the neighborhood. Before long others caught on. Within months, Aadhaar kiosks mushroomed across the country. In Bihar, near the border with Nepal, one entrepreneurial 16-year-old named Rishikesh Kumar opened one, gaining a toehold into a world coursing with the private details of hundreds of millions of citizens.
Operators received little vetting: Inspectors came maybe twice to Bharat’s kiosk, and only to check if there was a water cooler, enough chairs and adequate waiting space. For technical support, Bharat and some fellow operators had an informal WhatsApp group where they shared information on software updates and the like.
By late 2016, India had issued more than a billion Aadhaar numbers, opened 260 million bank accounts, and brought 410 million people online in less than a decade. By making it easy to verify identities and link bank accounts, Aadhaar also enabled the rise of a homegrown instant-payment system that began transforming the country’s cash-based economy into a digital one. Street sellers and rickshaw drivers started flashing QR codes to customers, who at a stroke could transfer payment from their phones. Modi accelerated this shift in November 2016 by withdrawing India’s highest-value banknotes, accounting for 86% of the currency in circulation, to combat corruption and tax evasion.
India proved Gates right, undergoing the fastest, most ambitious digital transformation in history. It became the world’s top consumer of mobile data per user. Its Internet users are set to surpass 900 million. Its instant payment system processes half of all global real-time transactions.
The Aadhaar program was lauded by experts for its scalability and security. But it had a fundamental flaw: India had created a lockbox, yet kept giving a peek inside—to telecom companies, banks, courier companies, airlines, you name it.
By mid-2017 the government began restricting access for private operators like Bharat. Along with thousands of other small-time entrepreneurs, he was about to lose his livelihood.
Around that time, Bharat noticed new participants in the WhatsApp group, hawking a software they promised would maintain access to the Aadhaar system for a nominal fee of 200 to 300 rupees. “I wanted to try and understand the software, what it was,” Bharat recalls. He purchased it, got a new ID and password, and entered the system. He typed in an Aadhaar number, and the system spat back all the registrant’s details—name, address, phone number, photo. This was odd. Previously, he couldn’t retrieve such details, he could only input them. He tried another Aadhaar number, and another, and another—all with the same result. “I felt something was very, very wrong.”
Over the next few months, he tried to alert authorities. He called and sent hundreds of emails to the Unique Identification Authority of India, which oversees Aadhaar. He went in person to several regional government officers to show them the software firsthand. He even emailed Modi.
For about $3.50, Bharat had bought access to a database containing the private details of a billion-plus people, one of the biggest data breaches of all time, and no one cared. Eventually, Bharat got the attention of a local newspaper reporter, who replicated Bharat’s steps, verified the breach and published an account. Modi’s ruling Bharatiya Janata Party responded by tweeting from its official account, “FAKE NEWS.”
It’s unknown how many unauthorized people had access or how much data was downloaded. In 2023 an American cybersecurity firm discovered hundreds of millions of Aadhaar records for sale on the dark web. Unlike leaked passwords or credit card numbers, biometrics can’t be changed—once they’re stolen, they pose a lifelong risk.
The day after the newspaper story was published, Bharat was rewarded for whistleblowing by having his access to government services cut off. He folded his service center and opened a business repairing kitchen appliances. Unauthorized groups are still out there offering access to Aadhaar, evidence that the government’s ID system remains vulnerable, he said in June at his new shop. “They know what’s happening, but they can’t stop it.”
The era of AI persuasion in elections is about to begin
By Tal Feldman and Aneesh Pappu | MIT Technology Review | December 5, 2025
3 key takeaways from the article
1. AI can be used to fabricate messages from politicians and celebrities—even entire news clips—in minutes. The fear that elections could be overwhelmed by realistic fake media has gone mainstream—and for good reason. But that’s only half the story. The deeper threat isn’t that AI can just imitate people—it’s that it can actively persuade people.
2. In the coming years, we will see the rise of AI that can personalize arguments, test what works, and quietly reshape political views at scale. That shift—from imitation to active persuasion—should worry us deeply.
3. The challenge is that modern AI doesn’t just copy voices or faces; it holds conversations, reads emotions, and tailors its tone to persuade. And it can now command other AIs—directing image, video, and voice models to generate the most convincing content for each target. Putting these pieces together, it’s not hard to imagine how one could build a coordinated persuasion machine. One AI might write the message, another could create the visuals, another could distribute it across platforms and watch what works. No humans required.
(Copyright lies with the publisher)
Topics: AI and Elections
Extractive Summary of the Article | Read | Listen
In January 2024, the phone rang in homes all around New Hampshire. On the other end was Joe Biden’s voice, urging Democrats to “save your vote” by skipping the primary. It sounded authentic, but it wasn’t. The call was a fake, generated by artificial intelligence.
Today, the technology behind that hoax looks quaint. Tools like OpenAI’s Sora now make it possible to create convincing synthetic videos with astonishing ease. AI can be used to fabricate messages from politicians and celebrities—even entire news clips—in minutes. The fear that elections could be overwhelmed by realistic fake media has gone mainstream—and for good reason.
But that’s only half the story. The deeper threat isn’t that AI can just imitate people—it’s that it can actively persuade people. And new research published this week shows just how powerful that persuasion can be. In two large peer-reviewed studies, AI chatbots shifted voters’ views by a substantial margin, far more than traditional political advertising tends to do.
In the coming years, we will see the rise of AI that can personalize arguments, test what works, and quietly reshape political views at scale. That shift—from imitation to active persuasion—should worry us deeply.
The challenge is that modern AI doesn’t just copy voices or faces; it holds conversations, reads emotions, and tailors its tone to persuade. And it can now command other AIs—directing image, video, and voice models to generate the most convincing content for each target. Putting these pieces together, it’s not hard to imagine how one could build a coordinated persuasion machine. One AI might write the message, another could create the visuals, another could distribute it across platforms and watch what works. No humans required.
The same technology that powers customer service bots and tutoring apps can be repurposed to nudge political opinions or amplify a government’s preferred narrative. And the persuasion doesn’t have to be confined to ads or robocalls. It can be woven into the tools people already use every day—social media feeds, language learning apps, dating platforms, or even voice assistants built and sold by parties trying to influence the American public. That kind of influence could come from malicious actors using the APIs of popular AI tools people already rely on, or from entirely new apps built with the persuasion baked in from the start.
And it’s affordable. For less than a million dollars, anyone can generate personalized, conversational messages for every registered voter in America.
Although this is a challenge in elections across the world, the stakes for the United States are especially high, given the scale of its elections and the attention they attract from foreign actors. If the US doesn’t move fast, the next presidential election in 2028, or even the midterms in 2026, could be won by whoever automates persuasion first.
Strategy & Business Model Section
Past forward: The modern rethinking of marketing’s core
By Aurélia Bettati et al., | McKinsey & Company | November 20, 2025
3 key takeaways from the article
- Europe’s marketing organizations are going back to basics, rediscovering the power of prioritizing proven growth levers such as branding and budget rigor. But McKinsey’s State of Marketing Europe 2026 report finds almost all are failing to embrace the transformative potential of AI and other technologies—and that could leave many European companies on the cusp of an AI reckoning.
- McKinsey’s report reveals 94 percent of European marketing organizations are yet to advance their gen AI maturity, often hampered by cautious leadership, limited know-how, and scattered initiatives. But the 6 percent of marketing executives who describe their company’s use of gen AI as mature are reaping serious rewards: they have already seen 22 percent efficiency gains, which they often reinvest in growth, and expect gains to hit 28 percent within two years.
- From the 20 priority topics, the following three themes emerged: Be Trusted. Be Effective. And Be Bold.
(Copyright lies with the publisher)
Topics: European Firms’ Marketing Strategy
Extractive Summary of the Article | Read | Listen
Europe’s marketing organizations are going back to basics, rediscovering the power of prioritizing proven growth levers such as branding and budget rigor. But McKinsey’s State of Marketing Europe 2026 report finds almost all are failing to embrace the transformative potential of AI and other technologies—and that could leave many European companies on the cusp of an AI reckoning.
McKinsey’s report reveals 94 percent of European marketing organizations are yet to advance their gen AI maturity, often hampered by cautious leadership, limited know-how, and scattered initiatives. But the 6 percent of marketing executives who describe their company’s use of gen AI as mature are reaping serious rewards: they have already seen 22 percent efficiency gains, which they often reinvest in growth, and expect gains to hit 28 percent within two years.
While 50 percent of CMOs rank gen AI-enabled marketing as a top three fastest growing investment area, in terms of priority for 2026, it was ranked 17th out of 20.
More widespread gen AI adoption and execution could accelerate the impact of branding efforts, which have reasserted their power. Branding was cited as the number one priority for 2026 by marketing leaders, who view its ability to drive distinctiveness, embody a clear value proposition, and showcase creativity as critical to building competitive differentiation. While financial rigor was also a priority, 72 percent of CMOs plan to increase their budgets relative to sales in 2026—although they are under pressure to better explain marketing’s ROI.
Europe’s marketing executives are focusing on basics within their control as they navigate renewed trade uncertainty, stagnating economies in major European markets, and declining economic and consumer sentiment indices across the European Union. That makes sense: volatility and uncertainty affect not only companies but also consumers, whose desire for stability and belonging draws them to strong, reliable brands that drive trust and affiliation. From the 20 priority topics, the following three themes emerged: Be Trusted. Be Effective. And Be Bold.
Be Trusted. CMOs are rediscovering that brand is not a relic but the bedrock of resilience and long-term growth. As tools get faster, the fundamentals matter more: trust and emotional connection become the anchor that gives customers clarity, consistency, and a sense of security. Four of the top five priorities—branding (ranked #1), data privacy (#3), authenticity (#4), and employer branding (#5)—point to a shift from short-term activation toward long-term brand and trust building.
Be Effective. Despite concerns that marketing budgets could come under pressure due to company-wide cost-cutting programs, Europe’s marketing decision-makers are signaling optimism. A significant 72 percent plan to increase their budgets (compared to 49 percent who actually did so last year, relative to sales), while 27 percent intend to keep budgets constant (versus 49 percent last year). This reflects a belief in the potential for future growth in Europe. However, this optimism comes with increased pressure from the board, as CMOs are increasingly challenged to demonstrate the value of marketing spend and operate more efficiently. Notably, five of the ten topics cited in our survey as most important by Europe’s marketing executives center around proving and enhancing marketing’s contribution to business outcomes.
B Bold. While Europe’s marketing decision-makers don’t place gen AI and agentic AI among their top priorities (#17 out of 20), the need for action suggests a very different outcome. We believe this ranking underestimates both the urgency and the opportunity. Gen AI is already reshaping marketing economics: Gen AI leaders in our survey place it in their top five priorities and report efficiency improvements averaging 22 percent, which they bank or reinvest in growth. Laggards, by contrast, leave it near the bottom of their agendas. If this gap continues, European brands risk ceding ground to global leaders. The critical challenge is moving beyond isolated pilots toward marketing-wide adoption that consistently creates value.
As gen AI increasingly shapes consumer decision-making, the role of brands is shifting from providing functional benefits to fostering emotional relevance and trust. McKinsey’s research finds Europe’s marketing leaders are seeking to generate deep connections with consumers by positioning brands as authentic and creative. They are confident in the resilience of their budgets but remain aware of the challenging environment, putting efficiency and effectiveness first. And they are embracing the transformative opportunities presented by gen AI, with an eye to the emerging potential of agentic AI. In short, they’re seeking to get the basics right and position themselves as leaders in the next phase of marketing innovation.
Assess What Is Certain in a Sea of Unknowns
By Cynthia Selin | MIT Sloan Management Review | December 09, 2025
3 key takeaways from the article
- Scenario planning as a discipline is often associated with exploring uncertainty, but at its heart, its deeper purpose is re-perception. Re-perception is the practice of shifting how we see — not just confronting what is unknown but challenging what is familiar, expected, or taken for granted. It invites a reframing of assumptions, revealing blind spots and surfacing new possibilities. The following five lenses of certainty offer a way to re-perceive change. These are: Material and physical, Knowledge- and expert-driven, Temporal and path-dependent, Political and economic, and normative and cultural.
- Some certainties are helpfully stabilizing and protective of values, ecosystems, and social order. Others are maladaptive, reinforcing injustice, inefficiency, or outdated legacies. Some certainties deserve to be defended. Others need to be dismantled. But we can’t do either unless we name them.
- Good strategy involves balancing your attention between both certainties and uncertainties. Certainties and uncertainties must be put into dialogue with one another. It’s the tension and interplay between what we know and what we can’t know that shapes good strategic thinking.
(Copyright lies with the publisher)
Topics: Strategy, Strategic Planning, Stratgic Thinking, Scenario Planning
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In a world gripped by turmoil, leaders are fixated on the big unknowns. Political volatility, technological acceleration, ecological disruption, and economic instability have converged to make even short-term planning feel precarious. Uncertainty is no longer an exception — it’s the baseline.
Scenario planning practices are meant to help in times like these. They offer a structured way to navigate chaotic times, not by aiming to predict the future but by constructing portraits of plausible alternative futures to surface hidden assumptions, question what’s known and unknown, and tune leaders’ attention to factors that strategists may have overlooked.
However, while scenario planning has earned its place as a valuable tool for examining uncertainties, the author believes that its untapped strength lies in exposing and clarifying certainties. The pursuit of as-yet-unseen disrupters has overshadowed something equally vital: what is knowable about the future.
Strategic acumen lies not only in anticipating what will change but in recognizing what won’t. Certain constraints — whether physical, temporal, institutional, or cultural — shape the terrain of the future, delimiting what is possible and where meaningful shifts can occur. By surfacing these layers of certainty, leaders can shift from a vision of limitless potential to one grounded in the specific boundaries that shape change — offering a clearer basis for planning and vital scaffolding for building and stress-testing strategy.
Envisioning the future as a blank canvas of infinite possibilities frees us from a fixed mindset that simply overlays today’s issues and trends on tomorrow. It stimulates imagination and creativity. Yet the future is not a blank slate; there are grooves from the past that persist into the future.
The landscape of the future is already being shaped by entrenched infrastructures, institutional legacies, durable social forces, and deep-seated, ongoing trends.1 Some forces exhibit obduracy — resisting change despite efforts to disrupt them — while others evolve steadily and predictably along slower, long-wave trajectories. Some certainties, like carbon accumulating in the atmosphere, are latent but inevitable, lying in wait with consequences that are bound to unfold.
Leaders need to pay better attention to these stickier, slower, and more silent factors in their planning. In these volatile times of radical uncertainty, people tend to overfocus on uncertainties and gloss over certainties. When they perceive that everything is up for grabs, they don’t notice that many paths have already been laid or are locked in.
To facilitate identifying and investigating certainties so that they can be incorporated into scenario work and strategic planning, the author suggests applying a framework that considers the following five types of certainties:
- Material and physical. These certainties are rooted in environmental ecosystems, physical conditions, and hardened infrastructures that shape what is possible.
- Knowledge- and expert-driven. Some certainties persist because they are upheld by dominant knowledge regimes, expertise networks, and institutional ways of knowing that shape what counts as “true.”
- Temporal and path-dependent. Some certainties are structured by time, such as the inertia of past decisions, long planning cycles, or intergenerational commitments.
- Political and economic. Certainties are often upheld not because they are righteous or natural but because they serve some people’s interests and align with power. Some certainties are firmed up through policy lock-in, interdependent market structures, or entrenched financial commitments.
- Normative and cultural. Some certainties are not material or institutional but exist in the collective imagination, defining what is seen as natural or inevitable. These are enduring societal values or organizational principles that shape decision-making and persist over time.
Some certainties are helpfully stabilizing and protective of values, ecosystems, and social order. Others are maladaptive, reinforcing injustice, inefficiency, or outdated legacies. Some certainties deserve to be defended. Others need to be dismantled. But we can’t do either unless we name them.
Good strategy involves balancing your attention between both certainties and uncertainties. While certainties give us anchors, anchors don’t set direction or steer the way through radical uncertainty. Certainties and uncertainties must be put into dialogue with one another. It’s the tension and interplay between what we know and what we can’t know that shapes good strategic thinking.
Scenario planning as a discipline is often associated with exploring uncertainty, but at its heart, its deeper purpose is re-perception. Re-perception is the practice of shifting how we see — not just confronting what is unknown but challenging what is familiar, expected, or taken for granted. It invites a reframing of assumptions, revealing blind spots and surfacing new possibilities.
Anthropic is all in on ‘AI safety’—and that’s helping the $183 billion startup win over big business
By Jeremy Kahn | Fortune | December 2, 2025
3 key takeaways from the article
- Dario Amodei is, in his telling, the accidental CEO of an accidental business—one that just happens to be among the fastest-growing on the planet. “When we first started Anthropic, we didn’t have any idea about how we would make money, or when, or under what conditions,” he says.
- Anthropic is the San Francisco–based AI company that Amodei cofounded and leads. And it hasn’t taken long for it to start pulling in lots of money, under lots of conditions. The startup has emerged as one of the leading rivals to OpenAI and Google in the race to build ever-more-capable artificial intelligence. And over the past year its Claude family of AI models have quietly emerged as the model that businesses seem to like best.
- Anthropic’s commercial traction is in some ways profoundly ironic. The company was founded in 2020 by Amodei, his sister Daniela, and five other former OpenAI employees who broke away from that company, in part, because they were concerned it was putting too much emphasis on commercial products over “AI safety,” the effort to ensure AI doesn’t pose significant risks to humanity. At Anthropic, safety was going to be the sine qua non. In another twist, the emphasis on trust and caution that has helped Anthropic gain traction with big business has entangled the company in conflicts with influential figures in politics and business.
(Copyright lies with the publisher)
Topics: Anthropic, AI Market, Competition, Business Strategy, Claude
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Dario Amodei is, in his telling, the accidental CEO of an accidental business—one that just happens to be among the fastest-growing on the planet. “When we first started Anthropic, we didn’t have any idea about how we would make money, or when, or under what conditions,” he says.
Anthropic is the San Francisco–based AI company that Amodei cofounded and leads. And it hasn’t taken long for it to start pulling in lots of money, under lots of conditions. The startup has emerged as one of the leading rivals to OpenAI and Google in the race to build ever-more-capable artificial intelligence. And while Anthropic and its Claude family of AI models don’t have quite the same brand recognition as crosstown rival OpenAI and its ChatGPT products, over the past year Claude has quietly emerged as the model that businesses seem to like best.
Anthropic, currently valued at $183 billion, has by some metrics pulled ahead of its larger rivals, OpenAI and Google, in enterprise usage. The company is on track to hit an annualized run rate of close to $10 billion by year-end—more than 10 times what it generated in 2024. It also told investors in August that it could bring in as much as $26 billion in 2026, and a staggering $70 billion in 2028.
Even more remarkably, Anthropic is generating such growth without spending nearly as much as some rivals—at a time when massive capital expenditures across the industry are stoking anxiety about an AI bubble. (OpenAI alone has signed AI infrastructure deals worth more than $1 trillion.) That’s in part because Anthropic says it has found ways to train and run its AI models more efficiently. To be sure, Anthropic is nowhere near profitable today: It was pacing to end 2025 having consumed $2.8 billion more cash than it took in, according to recent news accounts citing forecasts provided to investors. But the company is also on track to break even in 2028, according to those projections—two years ahead of OpenAI.
Anthropic’s commercial traction is in some ways profoundly ironic. The company was founded in 2020 by Amodei, his sister Daniela, and five other former OpenAI employees who broke away from that company, in part, because they were concerned it was putting too much emphasis on commercial products over “AI safety,” the effort to ensure AI doesn’t pose significant risks to humanity. At Anthropic, safety was going to be the sine qua non.
In another twist, the emphasis on trust and caution that has helped Anthropic gain traction with big business has entangled the company in conflicts with influential figures in politics and business. Key Trump administration officials range from skeptical to downright hostile to Anthropic’s positions on AI safety and its advocacy for regulation. The company has clashed with Nvidia CEO Jensen Huang—over Anthropic’s support for limiting exports of AI chips to China—and with Salesforce CEO Marc Benioff over Amodei’s warnings about AI-induced job losses.
The opprobrium of these influential figures is just one obstacle Anthropic is navigating. It has also faced lawsuits over its use of copyrighted books and music to train Claude. It agreed to settle one class action lawsuit with authors over its use of pirated libraries of books for $1.5 billion in September. That’s cash the company would rather spend on growth, but had it lost in court, Anthropic might have been bankrupted.
It’s a lot for a young company to manage, especially one undergoing hypergrowth. Anthropic had fewer than 200 employees in late 2023. Today it has approximately 2,300. It’s hiring an army of salespeople, customer support engineers, and marketing professionals, even as it staffs up on researchers to push the frontier of AI development. It’s also expanding internationally at a rapid clip. Just since September, it has opened Paris and Tokyo offices, and announced ones in Munich, Seoul, and Bengaluru, adding to its existing global footprint of Dublin, Zurich, and London.
Having established itself as “the AI company for business,” Anthropic’s challenge is to keep that title in an industry where performance leaderboards can shift overnight and market gains can quickly disappear. As its rocket ship burns through the stratosphere, the question is, Can Anthropic achieve escape velocity? Or will powerful forces—the gravitational pull of the immense costs associated with cutting-edge AI models, the buffeting winds from political turbulence and intense competition, and the internal pressures inherent in managing an organization growing at supersonic rates—send it spinning back down to earth?
Personal Development, Leading & Managing Section
The Hidden Beliefs That Hold Leaders Back
By Muriel M. Wilkins | Harvard Business Review Magazine | Nov-Dece 2025 Issue
2 key takeaways from the article
1. Every leader hits a wall from time to time. Perhaps you’re struggling to lead at scale, motivate your team, or persuade higher-ups to give you the resources you need. In such situations it can be tempting to focus on external blockers, such as organizational bureaucracy, employee attitudes, and managerial decision-making. However, the biggest limiting factors for most of us lie within our own unproductive hidden (beliefs) blockers. Based on her research seven most common: I need to be involved. I need it done now. I know I’m right. I can’t make a mistake. If I can do it, so can you. I can’t say no. And I don’t belong here.
2. If you’re having trouble advancing in your career or having the impact you want at work, chances are, one of these beliefs is holding you back. The author developed and suggested a three-step framework—rooted in established behavioral-change principles—that can be used to get unblocked and unstuck. These steps are: uncover the blocker, unpack the belief, re-frame the belief into something more productive and embedding that new perspective into behavioral changes and tangible action.
(Copyright lies with the publisher)
Topics: Leadership, Beliefs
Extractive Summary of the Article | Read | Listen
Every leader hits a wall from time to time. Perhaps you’re struggling to lead at scale, motivate your team, or persuade higher-ups to give you the resources you need. In such situations it can be tempting to focus on external blockers, such as organizational bureaucracy, employee attitudes, and managerial decision-making. However, in the two decades the author has spent coaching hundreds of executives across multiple industries, she has found that the biggest limiting factors for most of them lie within: their own unproductive beliefs, which I call hidden blockers.
Why hidden? Because these blockers are so ingrained and habitual that most of us aren’t even aware that they exist. But they are there, quietly shaping every aspect of how we think, feel, and act. As the psychologist Carol Dweck’s groundbreaking work on mindsets has shown, the sets of beliefs we hold about ourselves are key to our ability to learn, adapt, and grow and to our performance and results. Bottom line: Whether we’re aware of them or not, our beliefs affect our outcomes. Based on her research seven most common: I need to be involved. I need it done now. I know I’m right. I can’t make a mistake. If I can do it, so can you. I can’t say no. And I don’t belong here.
If you’re having trouble advancing in your career or having the impact you want at work, chances are, one of these beliefs is holding you back. The author developed and suggested a three-step framework—rooted in established behavioral-change principles—that can be used to get unblocked and unstuck. Step one is to uncover the blocker: recognizing the problem and naming the belief that’s creating it. In step two, you unpack the belief, reflecting on where it came from, how it might have once served you, and how it is limiting you now. Step three is to unblock yourself by reframing the belief into something more productive and embedding that new perspective into behavioral changes and tangible action.
Try to focus on: I can do anything, but I can’t do everything. I need to focus on what truly matters. My role is to help others find solutions, not to always give them the answers. My focus is excellence, not avoiding failure. What worked for me might not work for everyone. I can say no to some thing. I belong wherever I am.
The Art Of Disagreeing Without Damaging Trust: 5 Leadership Practices
By Tony Gambill | Forbes | December 10, 2025
3 key takeaways from the article
- In today’s workplace, disagreements often escalate into defensiveness, which damages trust, psychological safety and team performance. Yet great leaders know how to do something increasingly rare: disagree respectfully without negatively impacting trust and relationships.
- The most effective leaders embrace a simple truth: It’s more important to get it right than to be right. Being right is about having the correct answer or perspective. Getting it right is about creating an environment of trust and collaboration that leads to the right answer.
- So how do the best leaders challenge ideas without damaging trust or psychological safety? It comes down to five practices that consistently strengthen trust and relationships instead of eroding them. Decide When to Speak Up (and When to Stay Silent). Your Perceptions Are Not Reality. Clarify Whether Your Role is Advising or Deciding. You Can Be Right and Still Get It Wrong. And Challenge Ideas Without Triggering Defensiveness.
(Copyright lies with the publisher)
Topics: Leadership, Disagreement, Turst
Extractive Summary of the Article | Read | Listen
In today’s workplace, disagreements often escalate into defensiveness, which damages trust, psychological safety and team performance. Yet great leaders know how to do something increasingly rare: disagree respectfully without negatively impacting trust and relationships.
The most effective leaders embrace a simple truth: It’s more important to get it right than to be right. Being right is about having the correct answer or perspective. Getting it right is about creating an environment of trust and collaboration that leads to the right answer.
A leader’s success is tied to their ability to build relationships, influence others, coach, delegate, engage employees, establish trust and develop talent. None of these skills depend on always having the right perspective, but a leader’s success does depend on how effectively they engage with others toward finding the best solution.
So how do the best leaders challenge ideas without damaging trust or psychological safety? It comes down to five practices that consistently strengthen trust and relationships instead of eroding them.
- Decide When to Speak Up (and When to Stay Silent). You need to learn to be more selective about when to speak up by asking himself questions like: Does this serve the greater good? Have I already shared my perspective? Are the people involved open to being influenced? Is there a better time, place, or person to voice this? Should someone else take the lead on raising this concern?
- Your Perceptions Are Not Reality. Disagreements can easily escalate into larger conflicts when leaders assume their interpretation of a situation is accurate and complete. This mindset is harmful because it leaves no room for others’ perspectives or for dialogue that leads to learning, alignment and mutual trust. Decades of research on cognitive biases show that our perceptions are shaped, and often distorted, by past experiences, preferences, stress and emotions. Understanding that we all experience perceptual bias gives us the humility and patience to ask questions and listen. When leaders forget this, they often misjudge others’ intentions, react defensively or push too hard for their own viewpoint. Before challenging someone, pause and ask yourself: What assumptions am I making? What else could be true? How might their perspective make sense from where they sit? Leaders who treat their perspective as one view, not the only view, create space for healthier dialogue, reduce defensiveness and preserve the trust needed for productive disagreement.
- Clarify Whether Your Role is Advising or Deciding. Before entering a conversation that challenges others’ positions, clarify whether your role is to advise or decide on this issue. When you’re giving counsel, your goal is to influence thoughtfully and support decision-makers. When you have authority, your responsibility is to make the final call while still creating space for others’ voices. Confusion around these roles can easily escalate tension, misunderstanding and conflict.
- You Can Be Right and Still Get It Wrong. You can be right about your perspective and wrong about your delivery. Many leaders fall into the trap of believing the urgency or importance of their message excuses harsh communication. Very few situations are so critical that they justify sacrificing dignity, emotional safety or respect. Before challenging someone, take a brief pause and ask: What are my best long-term goals for this relationship and outcome? Based on that, what are my best “in-the-moment” intentions?
- Challenge Ideas Without Triggering Defensiveness. When you need to challenge someone’s perspective, start by signaling a desire to understand their perspectives, challenges, needs, and goals. You might say: “I think we may see this differently. I’d like to hear your thoughts and share mine.” Listening doesn’t mean agreeing; it means you respect the person enough to take the time to listen and understand their feelings. This approach communicates respect and curiosity, while reducing defensiveness and setting a collaborative tone.
Entrepreneurship Section
5 Ways to Introduce AI Into Your Business—and What Mistakes to Avoid
By Chloe Aiello | Inc | December 9, 2025
3 key takeaways from the article
- There’s almost no way to describe the AI hype that’s sweeping the business world that won’t read like an understatement—and companies are rushing to jump in. But as with any new technology, AI comes with certain risks.
- With all this buzz, companies that have only begun to test the waters of the technology likely have some questions about how to introduce AI in a safe and effective way. And who better to answer than chief technology officers?
- Inc. spoke to three Best in Business CTOs from Blackbird.AI, Copyleaks, and DataDome for their advice on how to implement AI—and when it may be best not to. Start with a problem, not a tool. Automate replicable processes—and update them. Know the technology’s limits. Ignite enthusiasm. And assume your team is already using AI.
(Copyright lies with the publisher)
Topics: Entrepreneurship, Technology Adoption
Extractive Summary of the Article | Read | Listen
There’s almost no way to describe the AI hype that’s sweeping the business world that won’t read like an understatement—and companies are rushing to jump in. But as with any new technology, AI comes with certain risks.
With all this buzz, companies that have only begun to test the waters of the technology likely have some questions about how to introduce AI in a safe and effective way. And who better to answer than chief technology officers? Inc. spoke to three Best in Business CTOs from Blackbird.AI, Copyleaks, and DataDome for their advice on how to implement AI—and when it may be best not to.
- Start with a problem, not a tool. AI can be a powerful tool, but it is hardly a magic bullet. And when wielded incorrectly, it can compound chaos. AI can be a powerful tool, but it is hardly a magic bullet. And when wielded incorrectly, it can compound chaos, warns Blackbird.AI co-founder and CTO Naushad UzZaman. Blackbird.AI offers a suite of AI-powered tools that helps executives, major companies, and governmental organizations anticipate and protect against narrative attacks like misinformation that can cause reputational and financial harm. “The real edge is not using AI everywhere—it’s knowing where AI can genuinely help,” he says. Much like founding a startup, the key to implementing AI, UzZaman says, is to first identify a real problem and then find the optimal AI solution for it.
- Automate replicable processes—and update them. Automation is a relatively easy entry point for AI. And thanks to low- and no-code platforms, as well as vibe coding (which leverages generative AI to convert natural language prompts into code), it’s more accessible than ever. “Automation is available to everyone now,” says DataDome CTO Gilles Walbrou. “You don’t need to code to automate things.” Walbrou says tasks ripe for automation are things that teams do repeatedly, day in and day out. Automation then frees up workers, engineers in particular, to “focus on the high value you can provide within your job,” he says. That said, automation isn’t for everyone. Before jumping into automation, Walbrou urges companies to first adopt a performance culture—one built around quantifiable performance metrics, high-quality data, speed and adaptability.
- Know the technology’s limits. Speaking of vibe coding, Walbrou says it is a powerful and potentially transformative tool—but it has a very specific place. He says researchers in particular found it “life changing,” because it reduced their dependence on developers during testing and ideation and sped up the delivery timeline for new features. But Walbrou emphasizes that companies should never produce features built only with vibe coding. UzZaman agrees, calling vibe-coded apps “very, very risky.” “Vibe coding I would recommend strongly for internal prototyping. But after that, someone can do the coding properly,” he says.
- Ignite enthusiasm. Although it’s unlikely every employee will be interested in AI, there’s a good chance there’s at least one enthusiast lurking in every enterprise. DataDome’s Walbrou recommends companies identify enthusiasts and early adapters and leverage them as AI ambassadors. “My advice would be to find an internal sponsor—passionate people that can act as ambassadors of the technology internally,” he says. “They will show the value to the rest of the team, and then you’ll have a positive loop.”
- Assume your team is already using AI. Your team is likely already using AI—so set your policies accordingly. “This is something the team is going to use whether you like it or not,” Blackbird.AI’s UzZaman says. “So embrace it and provide proper guidance.” What that means in practice will vary depending on the nature of a company and its risk appetite, UzZaman says. At an absolute minimum, he recommends that leaders set policies around which tools are safe or appropriate to use, based on the data use, storage and training policies of the companies that created them.
Why Startups Fail to Break Through and the Strategic Moves That Separate the Winners
By Bidhan Baruah | edited by Micah Zimmerman | Entrepreneur | December 11, 2025
2 key takeaways from the article
- If you’ve ever built a startup from scratch, you know the story. You start with a clear pain point, build a product that solves it, and fight to get valuable clients. In that moment, it feels like you’ve cracked it, and momentum will never stop. Yet 42% startups collapse due to misreading market demand. And when growth stalls, everything comes crashing down. Sales slow, your pipeline dries up and your product gets more complex, but revenue doesn’t follow.
- 5 major drawbacks that stop startups from scaling and their solutions are: A) Founders obsess over features and perfection — but traction matters most. So, before you scale, simplify, test your assumptions, build lean and validate fast. B) Unbalanced teams. You can’t scale on code alone. Scaling comes from balance — a team that can build, sell and support in sync. C) Founder-led sales that never end. Instead make this shift early by operationalizing the founder’s insights. Turn his/her instinct into playbooks, relationships into processes and ad-hoc selling into structured enablement. D) Instead of allowing building fiefdoms, build a culture of shared ownership. Cross-functional pods work better than rigid hierarchies in early-stage startups. And E) Neglecting support and customer success. Invest early in customer success. Establish onboarding processes that coach users, initiate feedback loops informing your roadmap and track retention with the same rigor as acquisition.
(Copyright lies with the publisher)
Topics: Entrepreneurship, Technology Startups
Extractive Summary of the Article | Read | Listen
Startups that don’t learn how to scale viable ideas often fail. If you’ve ever built a startup from scratch, you know the story. You start with a clear pain point, build a product that solves it, and fight to get valuable clients. In that moment, it feels like you’ve cracked it, and momentum will never stop. Yet 42% startups collapse due to misreading market demand. And when growth stalls, everything comes crashing down. Sales slow, your pipeline dries up and your product gets more complex, but revenue doesn’t follow.
There’s only a hairline difference between building a product and knowing how to scale one. Let’s discuss the major drawbacks that stop startups from scaling, and the strategic approaches that help you stay resilient.
- A broken go-to-market process. When founders treat “launching” as success, their learning curve becomes a straight line. They obsess over features and perfection — but traction matters most. An unassailable go-to-market validates that your product solves a problem people will pay for. Most startups spend months on dashboards, integrations and AI add-ons even before acknowledging customers’ views about the core feature. This isn’t progress; it’s expensive guesswork. Your MVP is a test, not a product. It can be a simple wireframe, prototype or flowchart. In startups, the primary principle is to prove value quickly or risk losing customers before they experience your differentiation. So, before you scale, simplify, test your assumptions, build lean and validate fast.
- Unbalanced teams Many startups focus on developers and designers but overlook those who sell the product, resulting in a powerful platform with unpredictable revenue. It’s typical to see founders drive the first handful of deals, only for growth to plateau later because no repeatable sales motion exists beyond their own effort. You can’t scale on code alone. Scaling comes from balance — a team that can build, sell and support in sync. When those pieces don’t move together, growth stalls and customer insight gets lost in the noise. Your tech might give you a great product, but it’s your sales and customer success teams that turn that product into a business.
- Founder-led sales that never end. Founder-led sales are often one of the biggest barriers to early-stage companies. Initially, it’s understandable — the founder knows the market, the problem and the product narrative better than anyone else. However, as the company scales, this pattern becomes a hindrance rather than an edge. Now, when every sale still depends on the founder, scalability crashes. This prevents the organization from creating a predictable and repeatable sales motion, and strategic growth takes a backseat. High-growth, visionary startups make this shift early by operationalizing the founder’s insights. They turn instinct into playbooks, relationships into processes and ad-hoc selling into structured enablement.
- Building fiefdoms, not flexibility. As startups grow, it’s common for teams to form silos. Engineering guards the product, sales guards the customer and operations guards the process. But this is where innovation slows down. Now, instead of collaborating, teams start protecting territory. Product decisions take longer. Priorities drift. Suddenly, the agility that once defined you early on disappears under layers of internal friction. As the market needs shift, your team needs to evolve with them. Build a culture of shared ownership. Cross-functional pods work better than rigid hierarchies in early-stage startups.
- Neglecting support and customer success. Without consistent sales support, growth becomes a revolving door. In every sector, clients aren’t just buying software; they’re betting their operations, outcomes and often investors on your reliability. When onboarding is weak or support is slow, even the best technology loses credibility. Customer success is the backbone of retention and referral growth. Invest early in customer success. Establish onboarding processes that coach users, initiate feedback loops informing your roadmap and track retention with the same rigor as acquisition. A loyal customer base can be the most cost-effective growth strategy, and a powerful proof that your product works.
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