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Three horizons of quantum: A business road map to the future computing economy
By Arvind Govindarajan et al., | McKinsey & Company | October 20, 2026
Extractive Summary of the Article | Read/Listen
Many business leaders now accept that quantum technology is coming sooner than they first expected, and they’re taking steps today to capture a competitive advantage. In their study, the authors have found that over 300 organizations worldwide are already working with quantum technology providers, with many more experimenting. What many leaders lack is a sense of how much to invest in which technologies, and over which timeline.
Faced with quantum technology’s rapid pace of development and the scale of its implications, leaders are now forced to reconsider their action plans. Across all three of its pillars—quantum computing, quantum communication, and quantum sensing—quantum technology is advancing rapidly. Quantum technology companies are hitting milestones more quickly than they initially predicted, and many have ambitious road maps that put the expected arrival of fault-tolerant quantum computing (FTQC) within the next few years. FTQC will enable reliable quantum computing at scale, opening new possibilities in everything from drug discovery to materials design to financial modeling. But FTQC is a double-edged sword; when fully scaled, it will also bring about Q-Day, the moment when quantum computers can break today’s public-key cryptography. As a result, even companies that don’t directly deploy quantum computing will need to update their security platforms to contend with it.
To help business leaders understand the road ahead, the authors mapped three horizons of quantum technology development, the roadblocks that could slow the quantum timeline—and the emerging developments that could speed it up.
The financial stakes justify immediate action. McKinsey’s latest Quantum Technology Monitor finds that quantum computing alone could create $1.3 trillion to $2.7 trillion of economic value worldwide by 2035. To capture as much of this value as possible, business leaders need to understand how quantum technology is developing across the three horizons and map their companies’ pathways through them. Waiting to invest is risky. Those that do could soon find that the partnerships, talent, and intellectual property needed to succeed with quantum technology were claimed years earlier by faster-moving competitors. They could also face severe security issues when Q-Day arrives.
- Horizon 1: Early commercialization. The clearest signal that quantum technology has crossed from research into commercial deployment is that the sector now has an exit market. In 2026, companies such as Horizon Quantum, Infleqtion, Pasqal, Quantinuum, and Xanadu went public. Meanwhile, IonQ acquired SkyWater Technology in a deal that pairs SkyWater’s chip manufacturing with IonQ’s quantum hardware and software. Governments are also supplying a stream of development capital, including, for example, recent commitments of $2 billion in the United States and more than €1 billion in France. Many of these investments are aimed at increasing manufacturing capacity rather than just research output, and they show that governments see economic opportunity in quantum technology.
- Horizon 2: Establishing a competitive position. Hardware road maps from leading quantum computing companies are converging on the possibility of delivering a fault-tolerant quantum computer within five years. IBM has published a potential path to large-scale fault tolerance by 2029, while IonQ is targeting two million physical qubits by 2030—enough to yield up to 80,000 logical qubits, the error-corrected units of computation that fault tolerance depends on. Fault tolerance will bring a step change for quantum computing: machines that can sustain long computations reliably enough to be embedded into production workflows.
- Horizon 3: Leading the quantum-enabled economy. In Horizon 3, entire economic arenas could reorganize around the future capabilities that quantum technology will make possible. The McKinsey Global Institute (MGI) has identified 18 future arenas of competition that will shape the global economy over the next 15 years, collectively generating $29 trillion to $48 trillion in revenues by 2040. Quantum technology intersects with several of these arenas. This means that some of the most competitive companies in Horizon 3 will be those that redesign their operating models around quantum technology. Horizon 3 is not just about adopting quantum technology for its own sake. If quantum becomes as foundational as AI is today, the question facing business leaders will not be whether to use quantum technology at all, but how to do so in ways that materially change their operating models. Every leader also needs to consider how quantum technology and AI will intersect—and the value that intersection could create for their businesses, the economy, and society.
Over the next 15 years, quantum computing will drive deep structural shifts in how companies do business. As fault-tolerant systems scale, first movers could gain access to computational capabilities that deliver hundreds of billions of dollars in value. Preparing for this future requires action today. To do so, leaders need to understand how quantum will develop across the three horizons.
To ensure their organizations take leading positions during each horizon, leaders can focus on four strategic priorities: secure ecosystem partnerships and access to frontier systems; pilot applications ahead of commercial readiness; build organizational familiarity through talent and IP; and explore how quantum technology could ultimately alleviate compute and energy bottlenecks in AI scaling. Quantum technology will not wait for organizations to feel ready—and the window to build a leading position will narrow with each horizon that passes.
3 key takeaways from the article
- Many business leaders now accept that quantum technology is coming sooner than they first expected, and they’re taking steps today to capture a competitive advantage. Across all three of its pillars—quantum computing, quantum communication, and quantum sensing—quantum technology is advancing rapidly. What many leaders lack is a sense of how much to invest in which technologies, and over which timeline.
- Quantum technology companies are hitting milestones more quickly than they initially predicted, and many have ambitious road maps that put the expected arrival of fault-tolerant quantum computing (FTQC) within the next few years. FTQC will enable reliable quantum computing at scale, opening new possibilities in everything from drug discovery to materials design to financial modeling. But FTQC is a double-edged sword; when fully scaled, it will also bring about Q-Day, the moment when quantum computers can break today’s public-key cryptography. As a result, even companies that don’t directly deploy quantum computing will need to update their security platforms to contend with it.
- To help business leaders understand the road ahead, the authors mapped three horizons of quantum technology development: Early commercialization, Establishing a competitive position, and Leading the quantum-enabled economy. To ensure their organizations take leading positions during each horizon, leaders can focus on four strategic priorities: secure ecosystem partnerships and access to frontier systems; pilot applications ahead of commercial readiness; build organizational familiarity through talent and IP; and explore how quantum technology could ultimately alleviate compute and energy bottlenecks in AI scaling.
(Copyright lies with the publisher)
Topics: Computing Economy, Quantum Computers
The focus on AI safety disasters ignores everyday harms
By Sam Hiner and Emma Leiken | MIT Technology Review | October 26, 2026
Extractive Summary of the Article | Read/Listen
Consider what passes for success in technology policy. An AI company promises that its chatbot will not encourage suicide. A social media platform makes it more difficult for children to buy fentanyl. These are important protections, and they should have existed all along. But companies can clear these low bars while continuing to make products that leave young people dependent on simulated friendships or trapped in feeds built to keep them scrolling.
We have historically allowed the debate over technology to be defined by the worst thing a product might do, with remarkably little discussion of the insidious damage it does every day. As we transition into an era defined by powerful AI products, we should demand that the tech industry do more than merely address catastrophic harms. We should take measures to ensure that its products don’t erode how we think, learn, and interact with one another.
A narrow definition of success defined around safety is politically convenient for the technology industry, and companies actively promote such definitions. Taking steps to prevent spectacular disasters is good for business: It can mean fewer lawsuits and less pressure for serious regulation. Confronting the everyday consequences of dependence would require something considerably more threatening to their bottom line. It might mean asking companies to add more friction to their products or actively limit engagement or features that lead to negative outcomes, such as addictive attention-hacking algorithms.
We have been through a version of this with social media. Globally, people who use the internet now spend an average of more than two hours a day on social media platforms—time that has been quietly taken from ordinary life and handed over to companies whose profits depend on keeping us there. No one, outside perhaps a few tech CEOs, wanted these algorithms to occupy such a large portion of our waking hours, and their cultural engineering can actually contribute to violence on a devastating scale. Meta’s platforms have been cited for contributing to the Rohingya genocide in Myanmar, anti-Muslim riots in Sri Lanka, and alleged calls for violence during Ethiopia’s Tigray war. The same incentives operate in the feeds that shape young Americans’ understanding of politics, their peers, and the wider world.
AI is extending this logic into parts of life that social media could influence only from a distance. It offers to write our thoughts for us and stand in for the people we might otherwise turn to. A third of teens now choose to discuss serious matters with AI companions instead of other people. MIT researchers found that young people using ChatGPT to write essays showed weaker brain connectivity during the task, and their evidence indicated that “cognitive debt” persisted even after the task was complete. There is plenty we still need to learn about the long-term effects. We already have reason to ask whether technology marketed as making us more capable is eroding the habits and relationships that help us develop capabilities in the first place.
Follow this way of thinking to its logical endpoint and you get a world of perfectly sanitized entertainment, with chatbots ready to spare us the difficulty of thinking or of dealing with another person’s feelings (or even our own). But anyone who has struggled to write something worth reading, or repair a damaged friendship, knows how much gets lost in that bargain. We build judgment through effort and friction, and we learn to live with other people by confronting the fact that they have needs and opinions of their own.
We should demand safety as a minimum, yes—and then demand considerably more. Technology companies and school districts should have to show beyond a reasonable doubt that AI improves learning and critical thinking before making it a fixture in classrooms. Companies should be prohibited from designing companions that pretend to be conscious or profess love to users, and they should face independent scrutiny of how their systems affect relationships and people’s ability to think for themselves. The companies that have inserted their products into nearly every part of modern life have earned obligations far greater than avoiding the next terrible headline.
3 key takeaways from the article
- Consider what passes for success in technology policy. An AI company promises that its chatbot will not encourage suicide. A social media platform makes it more difficult for children to buy fentanyl. These are important protections, and they should have existed all along. But companies can clear these low bars while continuing to make products that leave young people dependent on simulated friendships or trapped in feeds built to keep them scrolling.
- We have historically allowed the debate over technology to be defined by the worst thing a product might do, with remarkably little discussion of the insidious damage it does every day. As we transition into an era defined by powerful AI products, we should demand that the tech industry do more than merely address catastrophic harms. We should take measures to ensure that its products don’t erode how we think, learn, and interact with one another.
- We should demand safety as a minimum, yes—and then demand considerably more. Technology companies and school districts should have to show beyond a reasonable doubt that AI improves learning and critical thinking before making it a fixture in classrooms. Companies should be prohibited from designing companions that pretend to be conscious or profess love to users, and they should face independent scrutiny of how their systems affect relationships and people’s ability to think for themselves. The companies that have inserted their products into nearly every part of modern life have earned obligations far greater than avoiding the next terrible headline.
(Copyright lies with the publisher)
Topics: Technology & Society, AI safety
China is now supporting more people over 65 than children under 15
By Jay Ganglani | Fortune | October 29, 2026
Extractive Summary of the Article | Read/Listen
China now has more elderly dependents than children for the first time, a demographic milestone that adds to the mounting pressure facing the world’s second-largest economy.
The country’s old-age dependency ratio, which measures the number of people 65 and older as a share of the working-age population, rose to 23.1% last year, overtaking the child dependency ratio of 22%, according to data released last week by the National Bureau of Statistics (NBS) and reported by Yicai.
More than 223 million people in China are 65 or older, compared with roughly 213 million children aged 14 and under, according to government data.
“The costs of an ageing population fall more heavily on pensions, healthcare and long-term care,” Stuart Gietel-Basten, a professor of social science and public policy at the Hong Kong University of Science and Technology, says. China’s state pension fund risks running out of money by 2035, the Chinese Academy of Social Sciences warned in 2019.
The country’s population fell for a fourth consecutive year in 2025, dropping by 3.4 million people to 1.405 billion. The birth rate slid to 5.63 births per 1,000 people, its lowest level since the People’s Republic of China was founded in 1949.
“What matters most for China’s economy is not the ratio itself but how many people work, how productive they are, and how long they stay healthy,” Gietel-Basten says.
China’s demographic decline could affect the country’s long-term economic health. A smaller workforce must fund pensions and care for a population that is aging faster than those of most developed economies.
The birth rate has declined for decades amid rapid urbanization and the one-child policy, which Beijing enforced from 1980 to 2015 to curb population growth. The government provided financial incentives to families that complied, while those that broke the rules faced fines. China allowed families to have two children from 2016, then allowed families up to three children in 2021 and removed the penalties. Yet many Chinese couples are choosing not to have children, often citing the high cost of housing, education, and childcare.
To encourage couples to have children, China announced last year that it would offer parents a subsidy of 3,600 yuan ($540) a year for each child under three. The government is also gradually raising the retirement age to 63 for men, to 58 for women in white-collar jobs, and to 55 for women in blue-collar jobs
China’s aging population is creating a market for the “silver economy” or goods and services designed to meet the needs of older consumers. Beijing expects the sector to grow to 30 trillion yuan ($4.5 trillion) by 2035.
“Looking ahead, as China’s workforce continues to shrink and its population ages, investing more in education and training, along with using new technologies such as artificial intelligence and automation, will become increasingly important to help workers produce more and keep China’s economy growing,” Xiujian Peng, a senior research fellow at Victoria University’s Center of Policy Studies, says.
3 key takeaways from the article
- China now has more elderly dependents than children for the first time, a demographic milestone that adds to the mounting pressure facing the world’s second-largest economy.
- The country’s old-age dependency ratio, which measures the number of people 65 and older as a share of the working-age population, rose to 23.1% last year, overtaking the child dependency ratio of 22%. More than 223 million people in China are 65 or older, compared with roughly 213 million children aged 14 and under, according to government data.
- China’s demographic decline could affect the country’s long-term economic health. A smaller workforce must fund pensions and care for a population that is aging faster than those of most developed economies. China’s aging population is creating a market for the “silver economy” or goods and services designed to meet the needs of older consumers. Beijing expects the sector to grow to 30 trillion yuan ($4.5 trillion) by 2035.
(Copyright lies with the publisher)
Topics: China’s Shifting Demographics, Silver Economy
Strategy & Business Model Section
Your Chatbot Will Define Your Brand
By Julian De Freitas | Harvard Business Review Magazine | November–December 2026 Issue
Extractive Summary of the Article | Read/Listen
For decades companies have chased the promise of relationship marketing: Make customers feel known, cared for, and understood, and loyalty will follow. Companies have spent heavily on customer relationship management (CRM) systems to make that promise real. But relationship marketing has remained mostly a slogan. The problem isn’t effort; it’s execution at scale. Customer activity is fragmented across channels, service quality varies from one touchpoint to the next, and personalization often lands as clumsy or creepy. As a result the experience of having a relationship with a brand rarely resembles what people mean by “a relationship” in real life.
That’s starting to change, especially among AI-native companies. I call that shift “chatbot as relationship.” Instead of asking an entire organization to maintain one unified customer relationship, companies can increasingly offer a single conversational interface, an AI-powered chatbot, that becomes the primary way customers experience the brand. These systems don’t just answer questions. They can be designed to embody a distinct role, such as the attentive assistant, the trusted adviser, the encouraging coach, the empathetic companion, or the vigilant guardian. Each role shapes what customers expect, what they share, and how they interpret the brand’s intentions. Generative AI makes these relationships scalable, consistent, and adaptable in ways earlier personalization tools never could.
The shift removes many of the classic obstacles to managing customer-brand relationships. It makes personalization feel interactive rather than extractive. And it allows brands to deliver a uniformly positive experience without relying on perfect coordination among employees, vendors, and systems. But it also creates new challenges: Customers may disclose far more personal information than they ordinarily would to a company, begin to treat the chatbot as the brand itself, or react strongly when the relationship changes or the chatbot’s personality is altered.
Companies should ask four questions: What relationship should our chatbot have with customers? How should our chatbot change over time? How do we build trust? And what happens when that trust is broken? Many companies will need to manage multiple AI relationships under one brand. The winners will build bots with explicit roles that are complementary to the companies’ economic goals, devising technology that relentlessly sticks to the communication styles consumers expect from specific relationships.
The deeper shift, especially for AI-native companies, is not efficiency but relational intelligence: Once AI that is naturally conversational becomes the primary way customers experience an organization, they won’t separate the chatbot from the brand. Every conversation will shape what they believe the company stands for, what promises it intends to keep, and whose interests it ultimately serves. That means decisions that once felt purely technical, such as how much a chatbot remembers, when it hands customers to a human, or how it responds in difficult moments, will increasingly be part of a relational strategy—ideally from the inception of the brand—that shapes trust and loyalty.
Over time that will change what leadership looks like. Managing customer relationships won’t fall only to marketing or customer service. Product managers, engineers, designers, lawyers, compliance teams, and executives will all influence the relationship customers have with the company, because every update will potentially change how that relationship feels. The organizations that get this right won’t just build better chatbots. They’ll redefine what it means to build a trusted brand.
3 key takeaways from the article
- That’s starting to change, especially among AI-native companies. I call that shift “chatbot as relationship.” Instead of asking an entire organization to maintain one unified customer relationship, companies can increasingly offer a single conversational interface, an AI-powered chatbot, that becomes the primary way customers experience the brand. These systems don’t just answer questions. They can be designed to embody a distinct role, such as the attentive assistant, the trusted adviser, the encouraging coach, the empathetic companion, or the vigilant guardian. Each role shapes what customers expect, what they share, and how they interpret the brand’s intentions. Generative AI makes these relationships scalable, consistent, and adaptable in ways earlier personalization tools never could.
- The shift removes many of the classic obstacles to managing customer-brand relationships. It makes personalization feel interactive rather than extractive. And it allows brands to deliver a uniformly positive experience without relying on perfect coordination among employees, vendors, and systems. But it also creates new challenges: Customers may disclose far more personal information than they ordinarily would to a company, begin to treat the chatbot as the brand itself, or react strongly when the relationship changes or the chatbot’s personality is altered.
- Companies should ask four questions: What relationship should our chatbot have with customers? How should our chatbot change over time? How do we build trust? And what happens when that trust is broken? Many companies will need to manage multiple AI relationships under one brand. The winners will build bots with explicit roles that are complementary to the companies’ economic goals, devising technology that relentlessly sticks to the communication styles consumers expect from specific relationships.
(Copyright lies with the publisher)
Topics: Chatbots and Customer Relationship Marketing, Strategy, Business Model
Is HR Tech Undermining Your Strategy?
By Sharna Wiblen and Alexis Fink | MIT Sloan Management Review | October 26, 2026
Extractive Summary of the Article | Read/Listen
HR technology is no longer peripheral to how organizations operate. A fast-growing assortment of platforms is touching the employee life cycle and capturing workforce data. Each platform promises an alluring array of benefits, the most compelling of which is the ability to improve evidence-based decisions by establishing a single source of truth: current, centrally accessible workforce data. But despite this wealth of options, industry and consulting reports frequently attest that these proclaimed advancements in systems and decision-making remain largely unrealized; notably, SHRM found that fewer than half of both HR professionals and employees regard their company’s HR technology as effective.
How HR Tech Can Create Waste. The accumulation of HR technology systems often results in functional, financial, and decision waste for organizations. A fundamental and nearly universal business problem is data fragmentation. When data privacy and security are managed within each tool, as is often the case, competing models can create risks, such as inappropriately blocking data needed for essential functions in other tools — or inadvertently releasing data from one tool that is protected in another. Entire roles are now emerging for employees to bridge these gaps as organizations rely on “human glue” to manually extract, translate, reconcile, and transfer data across multiple systems.
Mapping Your Intent: Strategy First. When adopting vendor technology for talent management, organizations that don’t first consider whether a system supports desired outcomes can unintentionally cede command of their own strategy to vendors.
The Strategy-First Check-In. Based on their extensive work with organizations, the authors have learned that examining an organization’s talent management decision infrastructure is essential to ensuring that it advances the company’s strategy. To assist in this investigation, they offer the Strategy-First Check-In, a practical diagnostic we can use to help determine whether your HR tech stack supports strategic precision. These four steps aim to surface precisely where your systems may diverge from your priorities.
- The Blank-Page Exercise. Defining what an ideal system would look like in the absence of “close enough” constraints helps clarify what are you tolerating that you would never actively choose. Take a holistic view of your existing HR technology stack to identify which elements add value and which have merely become accepted ways of doing things.
- The Ecosystem Inventory. The next step is to inventory the active systems and tools running in your HR technology ecosystem. In large or complex organizations, that alone can be a significant amount of work. Building a list of the user-facing and back-end tools that are currently in place to run all of the various operations across HR, never mind determining the owner accountable for each system, can be daunting.
- The Accumulation Audit. The biggest benefit comes from understanding how each tool’s embedded criteria, processes, and decision logic shape talent decisions. Consider the following aspects of your HR technology stack. System purpose and history, Ownership and users, Data and decision logic, Ecosystem fit and value
- The Strategy Test. Raise and answer deeper questions about how your talent tech stack enables or limits your goals and priorities and whether the system fits your current strategic needs. Of course, doing this effectively requires clarity on your organization’s existing talent strategy; for many organizations, getting a clear, coherent and consistent talent strategy may be the first, most critical step in this process.
2 key takeaways from the article
- HR technology is no longer peripheral to how organizations operate. A fast-growing assortment of platforms is touching the employee life cycle and capturing workforce data. Each platform promises an alluring array of benefits, the most compelling of which is the ability to improve evidence-based decisions by establishing a single source of truth: current, centrally accessible workforce data. But despite this wealth of options, industry and consulting reports frequently attest that these proclaimed advancements in systems and decision-making remain largely unrealized.
- The accumulation of HR technology systems often results in functional, financial, and decision waste for organizations. When adopting vendor technology for talent management, organizations that don’t first consider whether a system supports desired outcomes can unintentionally cede command of their own strategy to vendors. Based on their extensive work with organizations, the authors suggest four steps aimed to surface precisely where your systems may diverge from your priorities. A) Defining what an ideal system would look like in the absence of “close enough” constraints. B) Inventory the active systems and tools running in your HR technology ecosystem. C) Understanding how each tool’s embedded criteria, processes, and decision logic shape talent decisions. And D) the strategy test is to raise and answer deeper questions about how your talent tech stack enables or limits your goals and priorities and whether the system fits your current strategic needs.
(Copyright lies with the publisher)
Topics: HR Technology, Strategy, Business Model
Personal Development, Leading & Managing Section
18 Leadership Behaviors That Undermine Trust (And How To Fix Them)
By Forbes Expert Panel | Forbes | October 29, 2026
Extractive Summary of the Article | Read/Listen
Building trust with a team takes time and care, and losing it doesn’t always take a major mistake. Sometimes, everyday habits leaders barely notice can cause employees to question their intentions, hesitate to speak up or disengage entirely.
Recognizing these tendencies is the first step toward changing them. Here, members of Forbes Coaches Council highlight leadership behaviors that can silently and invisibly erode trust, along with practical ways to adjust before it affects team confidence and performance.
- Acting Out Of Alignment With Professed Values. Failing to embody leadership behaviors that support shared principles can undermine trust. People are watching. When we don’t walk the talk, they notice. Leaders develop trust when acting in harmony with the values and aims they profess. If you desire transparency, practice vulnerability. If you preach risk-taking, support experimentation. If you advocate for accountability, engage team members in decision-making. Coherence in action builds trust.
- Neglecting Regular One-On-One Conversations. One leadership behavior that quietly undermines trust is letting regular one-to-one conversations slip. It’s easy to cancel or postpone them when things get busy, but those sessions are where leaders build trust. People can start to feel less valued, and leaders can lose touch with what’s really happening in their team. As AI rapidly reshapes the workplace, those conversations matter more than ever.
- Holding Employees To Different Standards. Selective accountability quietly destroys trust. When leaders tolerate behavior from high performers, senior employees or personal favorites that they wouldn’t accept from others, the team notices. Every exception teaches people what is actually acceptable. Ask yourself: “Would I tolerate this from someone else?” Accountability must apply regardless of title, tenure or relationship.
- Allowing Your Enthusiasm To Silence Others. Passion can quietly become intensity and undermine trust. Leaders jump in, cut people off or suck the oxygen out of the room. They often don’t do this out of bad intent. It’s usually unchecked enthusiasm. Notice when people contribute less, defer quietly or stop challenging you. Intensity makes people feel unsafe, and you can’t have trust without safety. Slow down. Your passion should create more voices in the room, not fewer.
- Withholding Important Information From Your Team. Hoarding information can quietly undermine trust. When leaders selectively share what they know, teams may fill in the gaps with their own assumptions, duplicate work or make avoidable mistakes. If you catch yourself holding back, ask what your team needs to move forward. Even when you can’t share everything, explain what you can and tell them when you expect to know more. Doing so helps you be more transparent and build the trust your team needs.
The others leadership behavior those undermine trust are:
Not Repairing Small Breaches Of Trust, Making Changes Without Input From Those Affected, Hiding Stress Instead Of Acknowledging It, Gossiping Instead Of Addressing Issues Directly, Failing To Acknowledge Employees’ Contributions, Reacting Defensively To Honest Feedback, Rewarding Behaviors That Contradict Your Values, Taking A One-Size-Fits-All Approach To Leadership, Listening To Respond Rather Than Understand, Sharing Too Much Without Considering The Impact, Avoiding Difficult Conversations, Ignoring How Others Experience Your Leadership, and Refusing To Admit What You Don’t Know.
2 key takeaways from the article
- Building trust with a team takes time and care, and losing it doesn’t always take a major mistake. Sometimes, everyday habits leaders barely notice can cause employees to question their intentions, hesitate to speak up or disengage entirely.
- Recognizing these tendencies is the first step toward changing them. Members of Forbes Coaches Council highlight leadership behaviors that can silently and invisibly erode trust, along with practical ways to adjust before it affects team confidence and performance. According to thes following are which erod trust: Acting Out Of Alignment With Professed Values, Neglecting Regular One-On-One Conversations, Holding Employees To Different Standards, Allowing Your Enthusiasm To Silence Others, Withholding Important Information From Your Team, Not Repairing Small Breaches Of Trust, Making Changes Without Input From Those Affected, Hiding Stress Instead Of Acknowledging It, Gossiping Instead Of Addressing Issues Directly, Failing To Acknowledge Employees’ Contributions, Reacting Defensively To Honest Feedback, Rewarding Behaviors That Contradict Your Values, Taking A One-Size-Fits-All Approach To Leadership, Listening To Respond Rather Than Understand, Sharing Too Much Without Considering The Impact, Avoiding Difficult Conversations, Ignoring How Others Experience Your Leadership, and Refusing To Admit What You Don’t Know.
(Copyright lies with the publisher)
Topics: Leadership, Erosion of Trust
Entrepreneurship Section
3 Reasons Why You Struggle With Difficult Conversations—and What You Can Do About It
By Justin Bariso | Inc | October 29, 2026
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According to the author over his career he has had to learn how to have difficult conversations. Telling someone their performance needs to improve, or pushing back to a client who you think has it wrong. He has gotten better at these types of conversations, but they haven’t really become easier. According to him he feels stress and anxiety and gets a pit in his stomach before he meets for such conversations. Is this normal?
Personality (and people!) are complex, so this experience will be different for everyone. But here are three factors that make a big difference:
- Your level of agreeableness. On one end of the spectrum, there’s highly agreeable, where you value social harmony much more than being right. On the other end of the spectrum is low agreeableness, where you care more about your own beliefs and opinion than how others feel about it. (And of course, there’s the full continuum in between.) In most cases, the higher you rank on agreeableness, the harder these conversations are. A personality assessment can give you a directionally accurate concept of how agreeable you are, but you probably already have a good idea. Most important, remember that there’s no “right” or “wrong” level of agreeableness. Being highly agreeable will give you advantages in some situations, and disadvantages in others. So will being less agreeable, and everything in between. The key is to recognize how your agreeableness is affecting you. Doing so helps you recognize that what you’re feeling is completely normal, and to develop strategies to manage that stress and to make the most of your conversation.
- Your level of empathy. The more natural empathy you feel for others, the more you “feel what they feel.” This causes friction, between the “you” that knows what needs to be said and done and the “you” that is empathizing with the other person. Similar to agreeableness, empathy exists on a continuum. Your empathy level will help you in many situations, but it can also hurt you if you don’t keep it in check. Still, you’re at your best when you lean into your empathy, leveraging to connect with the person you’re trying to have the difficult conversation with.
- Your previous experiences. Even if you rank low on agreeableness and empathy, all it takes is one really bad experience to cause you to get those butterflies churning. The thing is, would you change any of this, even if you could? High agreeableness, high empathy, your previous experiences…they all make you who you are. Like two sides of a coin, you can’t have the good without the bad. So, take both and make the most of it.
2 key takeaways from the article
- According to the author over his career he has had to learn how to have difficult conversations. Telling someone their performance needs to improve, or pushing back to a client who you think has it wrong. He has gotten better at these types of conversations, but they haven’t really become easier. According to him he feels stress and anxiety and gets a pit in his stomach before he meets for such conversations. Is this normal?
- Personality (and people!) are complex, so this experience will be different for everyone. But here are three factors that make a big difference: recognize how your agreeableness is affecting you. Doing so helps you recognize that what you’re feeling is completely normal, and to develop strategies to manage that stress and to make the most of your conversation. B) You will be at your best when you lean into your empathy, leveraging to connect with the person you’re trying to have the difficult conversation with. And C) Even if you rank low on agreeableness and empathy, all it takes is one really bad experience to cause you to get those butterflies churning. The thing is, would you change any of this, even if you could?
(Copyright lies with the publisher)
Topics: Personal Development, Leadership, Entrepreneur
9 Hidden Technology Challenges That Can Slow Down Business Growth
By Arpit Jain | Entrepreneur | October 30, 2026
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For most entrepreneurs, growth is the ultimate measure of success. Expanding into new markets, acquiring customers, increasing revenue and building stronger teams are often the priorities that dominate strategic discussions.
However, one critical factor frequently receives less attention: the technology infrastructure supporting everyday business operations. A company might have an excellent product, a growing customer base and an ambitious expansion strategy, yet still struggle to scale because its internal systems cannot keep up with increasing demand.
Technology challenges rarely appear overnight. They develop gradually through outdated software, disconnected applications, inefficient databases, inadequate security measures and technology investments made without a long-term strategy. These issues may seem manageable during the early stages of business development. But as organizations grow, even minor inefficiencies can become expensive obstacles.
Understanding these hidden challenges is essential for entrepreneurs who want to build businesses capable of sustaining long-term growth.
Outdated technology can create unexpected operational costs
Disconnected business systems reduce productivity
Poor database decisions can limit business scalability
Technology investments without clear business goals can waste resources
Weak cybersecurity can threaten business continuity
Lack of reliable data can lead to poor business decisions
Scaling too quickly can expose technology weaknesses
Overlooking employee training reduces the value of technology
The absence of a long-term technology roadmap creates unnecessary risk
Technology problems often remain hidden until they begin affecting revenue, productivity or customer satisfaction. By that stage, addressing them may require urgent investments and operational changes that could have been avoided through earlier planning.
Entrepreneurs can take a more proactive approach by reviewing their technology environment regularly and identifying potential weaknesses before they become significant obstacles. This includes evaluating outdated systems, improving application integration, monitoring database performance, strengthening cybersecurity and investing in employee training.
Equally important is connecting every major technology decision to a measurable business objective. Not every company needs the newest software, the most sophisticated infrastructure or an immediate migration to emerging technologies. In many cases, improving existing systems and simplifying workflows can produce meaningful results without unnecessary spending.
3 key takeaways from the article
- For most entrepreneurs, growth is the ultimate measure of success, however, one critical factor frequently receives less attention: the technology infrastructure supporting everyday business operations. A company might have an excellent product, a growing customer base and an ambitious expansion strategy, yet still struggle to scale because its internal systems cannot keep up with increasing demand.
- Technology challenges rarely appear overnight. Understanding these hidden challenges is essential for entrepreneurs who want to build businesses capable of sustaining long-term growth. 9 of these challenges are: Outdated technology can create unexpected operational costs. Disconnected business systems reduce productivity. Poor database decisions can limit business scalability. Technology investments without clear business goals can waste resources. Weak cybersecurity can threaten business continuity. Lack of reliable data can lead to poor business decisions. Scaling too quickly can expose technology weaknesses. Overlooking employee training reduces the value of technology. And the absence of a long-term technology roadmap creates unnecessary risk.
- Technology problems often remain hidden until they begin affecting revenue, productivity or customer satisfaction. By that stage, addressing them may require urgent investments and operational changes that could have been avoided through earlier planning.
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Topics: Technology & Growth, Technology Challenges