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Abby, a 13-year-old from Poulsbo, Washington, went to a Seattle Mariners baseball game expecting nothing more than a fun night. She left with a trading card worth $20,100, the Seattle Times reports.

The card featured Jimothy, a raccoon with an unusually short, round shape who went viral this summer after videos of him wandering a Seattle neighborhood spread online. In his honor, the team gave out Jimothy cards to the first 20,000 fans through the gate.

Abby, a 13-year-old from Poulsbo, Washington, went to a Seattle Mariners baseball game expecting nothing more than a fun night. She left with a trading card worth $20,100, the Seattle Times reports.

The card featured Jimothy, a raccoon with an unusually short, round shape who went viral this summer after videos of him wandering a Seattle neighborhood spread online. In his honor, the team gave out Jimothy cards to the first 20,000 fans through the gate.

Like much of the rest of the country, I just finished devouring HBO’s gritty medical drama, The Pitt. As much as I love Dr. Robby and the rest of the show’s day crew, around whom the series revolves, it always thrills me when their grueling, 15-hour shifts start to wind down and the night shift shows up. 

It takes a specific kind of person to become an emergency room doctor, and an even more specific kind to become one who particularly loves working overnights. As the night shift’s attending, Dr. Abbot, tells his staff in a pre-shift pep talk, “We are the night crawlers. We deal with the weirdest and the wildest because — ” and here the group says in unison — “we are the weirdest and wildest of them all.” 

This delightful scene got me thinking, and not just about how grateful I am that there are men and women out there who are staffing our hospitals in the wee hours of the night. It also reminded me that everyone has their own circadian rhythm, the internal clock that governs when they feel their sharpest. 

As a founder, I used to assume that productivity was mostly a matter of discipline — that if someone wasn’t doing their highest level of thinking during core business hours, they simply needed better habits. I was wrong. What I’ve learned, both from building Jotform and from watching how our team actually operates, is that peak performance times are something you have to discover and build around.

The science behind circadian rhythms

Contrary to the perception that people are either early birds or night owls, it turns out there’s a whole range of hours when one may be predisposed to do their best thinking. For me, I’m sharpest in the morning; by 3 p.m., I have to fight to stay focused. That’s hardly the case for everyone — in fact, recent research from the Journal of Sleep Research found four discrete circadian profiles, including but not limited to those who hit their stride in the afternoon. 

What determines which profile you fall into? Largely genetics, though age plays a role too — teenagers and young adults tend to skew later, while older adults are often at their best earlier. Light exposure, exercise and even meal timing can nudge your rhythms, but nothing you do will fundamentally rewire them. You are, to a significant degree, born with your clock.

Why should leaders care? Because understanding how your employees operate best has a direct impact on their effectiveness. When we schedule our most demanding work without any regard for when our people are at their cognitive peak, their performance is going to suffer, and your bottom line is, too.

Building around your teams’ best hours

Presumably, you already know when you, personally, work best. If not, I suggest keeping an energy journal to note the times of day you feel alert and motivated, and when you start to flag. 

But leaders tend to have more flexibility than their teams — as a CEO, no one is raising any eyebrows about my comings and goings from the office. I can head out for a midday walk or have a long lunch with a colleague, and not worry about what my supervisor will think of my absence. It’s one of the perks of being the boss. 

Your employees don’t have that luxury. And many won’t volunteer information about their peak hours unless you make it explicitly safe to do so. Writing for Harvard Business Review, management professor Stefan Volk suggests using a free tool, like Munich ChronoType Questionnaire, to learn more about your team members’ most productive hours. “Used thoughtfully, those assessments reveal where energy levels align and where they diverge, helping leaders decide when to schedule demanding discussions, assign complex tasks and hand off less demanding work,” he writes. 

Obviously, it’s not possible to completely redesign the standard workday. But it is possible to be more conscious about what tasks are completed when. If you know your lead engineer is most focused in the late morning, for example, that may not be the best time to schedule your weekly check-in call. For collaborative projects, an awareness of everyone’s chronotype can help determine how to determine when the bulk of work gets done. 

At Jotform, I find it’s helpful to lead by example. Aside from having some necessary overlap during the day, I am agnostic as to when employees do their work. For me, mornings are my deep work time, and I don’t schedule anything superfluous during the hours when my mind is at its sharpest. When leaders model this kind of self-awareness, it gives employees permission to do the same.

Dr. Abbot’s night crawlers thrive in the wee hours, and that’s great for them (and anyone with a 3 a.m. emergency). It’s highly likely that some of your team members do, too. By building around when your people think their best, you’re encouraging them to perform at their highest level. And who doesn’t want that?

Like much of the rest of the country, I just finished devouring HBO’s gritty medical drama, The Pitt. As much as I love Dr. Robby and the rest of the show’s day crew, around whom the series revolves, it always thrills me when their grueling, 15-hour shifts start to wind down and the night shift shows up. 

It takes a specific kind of person to become an emergency room doctor, and an even more specific kind to become one who particularly loves working overnights. As the night shift’s attending, Dr. Abbot, tells his staff in a pre-shift pep talk, “We are the night crawlers. We deal with the weirdest and the wildest because — ” and here the group says in unison — “we are the weirdest and wildest of them all.” 

This delightful scene got me thinking, and not just about how grateful I am that there are men and women out there who are staffing our hospitals in the wee hours of the night. It also reminded me that everyone has their own circadian rhythm, the internal clock that governs when they feel their sharpest. 

Most executives believe they’ve done their part on artificial intelligence. They’ve approved the tools, announced the initiative and moved on. But the adoption numbers tell a different story.

According to Slingshot‘s Digital Work Trends Report, 86% of C-suite executives believe AI usage is required in their company operations. Yet fewer than half (49%) of middle managers are reinforcing that expectation with their teams. This gap between what leaders announce and what employees actually do isn’t a technology problem. It’s a leadership one.

I’ve spent more than 35 years leading Infragistics, and one lesson which has remained true through every major technology shift is that the success of any new initiative depends less on the technology itself and more  on how leaders introduce it. The organizations that see lasting change are the ones whose leaders create an environment where people can adopt new tools with confidence.

AI is no different. If leaders want employees to embrace it, they need to do more than roll out a platform or issue a mandate. They need to create a safe space where people feel comfortable learning, experimenting and building new habits. Here are three ways leaders can do so. 

1. Coaching creates the confidence to experiment

Real AI adoption requires employees to experiment with the tools. But people won’t take those risks unless they feel safe doing so.

That’s where coaching becomes far more effective than command-and-control leadership. Rather than simply telling employees to use AI, coaching-oriented leaders work alongside their teams and ask what’s working, what isn’t and where people are getting stuck. 

Anyone who has spent time with an AI tool knows that getting genuinely useful results takes practice. The first prompt rarely gives you what you need. Over time, though, you learn to ask more specific questions, provide the right context and test different approaches until the output actually fits your workflow. 

That kind of learning is personal and iterative, and it looks different for every role. A marketer figuring out how to use AI to track KPIs is going to take a completely different path than a salesperson using it for outreach. Employees need room to go through that process, and that only happens when leaders create an environment where figuring it out is part of that job and not a sign that someone isn’t ready.

2. Model the behavior you want to see

One of the fastest ways to encourage AI adoption is for leaders to use it themselves. 

Employees pay far more attention to what leaders do than what they say. So, when leaders openly incorporate AI into meetings, planning sessions, decision-making or content creation — and are honest about both the successes and limitations — they normalize learning. And that transparency gives employees permission to experiment without feeling like they need to be experts from day one.

One simple habit leaders can implement is to open team check-ins by sharing how they used AI that week, what they tried, what worked and what didn’t, then inviting employees to do the same. Conversations like those are an opportunity to exchange ideas, uncover successful use cases, encourage collaboration and help employees learn from one another instead of experimenting in isolation.

3. Position AI as growth, not compliance

How leaders talk about AI matters just as much as how they implement it. When AI is framed as another mandatory technology rollout, employees often see it as another box to check or, worse, as a threat to their jobs. 

Slingshot’s Digital Work Trends report found that nearly 1 in 5 Gen Z employees (19%) and 17% of millennials worry AI could eventually replace them. A company mandate does nothing to address that fear. But when leaders position AI as a way to remove repetitive work, improve decision-making and give employees more time for higher-value thinking, that conversation starts to look very different.

Employees don’t want to hear that AI will replace what makes them valuable. They want to understand how it helps them become even better at the work they already do well. That means being clear about where AI adds value and where human judgment remains essential. AI can analyze data, summarize information and automate repetitive processes, but people still provide strategy, creativity, relationship-building and accountability. When those roles are clearly defined, AI becomes less intimidating and much more useful.

Ultimately, the organizations making the most progress with AI are the ones whose leaders make it safe to learn, model the behaviors they expect from others and consistently reinforce that AI is an investment in their people, not a replacement for them.

Most executives believe they’ve done their part on artificial intelligence. They’ve approved the tools, announced the initiative and moved on. But the adoption numbers tell a different story.

According to Slingshot‘s Digital Work Trends Report, 86% of C-suite executives believe AI usage is required in their company operations. Yet fewer than half (49%) of middle managers are reinforcing that expectation with their teams. This gap between what leaders announce and what employees actually do isn’t a technology problem. It’s a leadership one.

I’ve spent more than 35 years leading Infragistics, and one lesson which has remained true through every major technology shift is that the success of any new initiative depends less on the technology itself and more  on how leaders introduce it. The organizations that see lasting change are the ones whose leaders create an environment where people can adopt new tools with confidence.

Does saving $1,000 in a month seem impossible? Personal finance expert Jade Warshaw, who co-hosts The Ramsey Show, a popular financial talk radio program and podcast, says it’s not as difficult as it seems. 

Warshaw recently said in an interview with Fox Business that most Americans can put aside $1,000 if they are willing to sacrifice the little things and view their finances with a “scorched earth” mentality. “It’s more realistic than people think,” she said. “Most people are able to do it in 30 days.”

Warshaw said to start with building a budget. “If you don’t have a budget, it’s not going to work,” she said. That means calculating net monthly income, tracking expenses and making sure expenses are less than income. 

From that point, Warshaw suggests addressing the problem from two angles by both spending less and bringing in more. That may involve picking up extra shifts at work, starting a side hustle such as driving for Lyft or Uber or selling items online. 

At the same time, cutting back on routine spending, from streaming service subscriptions to dining out, can free up additional cash. 

Warshaw, who claims to have paid off $460,000 in debt, said groceries and dining are often among the fastest areas where households can reduce spending. Frequent restaurant visits and delivery fees can add hundreds of dollars to a monthly budget. Packing lunch at home instead of buying it during the workday can make a meaningful difference, she said.

“For the average person, they could spend anywhere between $12 to $15 going out for lunch, but making that same lunch at home, you could save half and only spend $5 or $6,” Warshaw said.

Baby steps

Ramsey Solutions, the financial education company founded by Dave Ramsey in 1992, recommends seven baby steps to help people take control of their finances. The first step is what Warshaw described: Saving $1,000 for a starter emergency fund. After that comes paying off all debt, saving three to six months of expenses and investing 15% of household income in retirement. 

Warshaw said that people trying to get out of debt could consider temporarily pausing their retirement contributions until they pay everything off. She also recommended being realistic about expenses, especially during the holidays.

“If a family says, ‘I’d like to save $1,000 in the month of December,’ well, it’s going to be tough because you’ve got Christmas going on,” she said.

These baby steps are difficult for most Americans to follow. According to a Bankrate survey released in February, only 47% of Americans said that they had enough money to cover a $1,000 emergency expense. Around 30% indicated that building an emergency fund and decreasing their credit card debt were equally important to them. 

“Most American households want to grow their savings, but few are making meaningful progress right now,” Stephen Kates, Bankrate financial analyst, said in the report. “Rather than trying to tackle everything at once, I recommend focusing on the single most important financial priority in 2026 and making consistent progress there first.”

Does saving $1,000 in a month seem impossible? Personal finance expert Jade Warshaw, who co-hosts The Ramsey Show, a popular financial talk radio program and podcast, says it’s not as difficult as it seems. 

Warshaw recently said in an interview with Fox Business that most Americans can put aside $1,000 if they are willing to sacrifice the little things and view their finances with a “scorched earth” mentality. “It’s more realistic than people think,” she said. “Most people are able to do it in 30 days.”

Warshaw said to start with building a budget. “If you don’t have a budget, it’s not going to work,” she said. That means calculating net monthly income, tracking expenses and making sure expenses are less than income. 

A few years ago, a candidate who had a poor experience during recruitment might tell a few friends. Today, they post about it. They leave a Glassdoor review and share screenshots. Hiring has become public in a way most organizations weren’t built to handle.

What I’ve seen, both through building a company and through analyzing how people find and evaluate jobs, is that trust has become the deciding factor in hiring. Job seekers evaluate employers by how clearly and consistently an organization communicates before anyone has been offered a role.

The cost of getting that wrong is measurable: Companies with a poor employer reputation pay at least 10% more per hire, and that’s before accounting for the offers declined, the referrals lost and the reviews that don’t stop.

The hiring process is part of your reputation

Those signals start earlier than most organizations realize. By the time someone applies, they’ve already formed an impression — shaped as much by what a company hasn’t said as by what’s written in the job description.

The data supports this — 66% of candidates say a positive hiring experience influenced their decision to accept an offer. Poor communication or unclear expectations led 26% of job seekers to decline offers, and up to 72% say they’ll share a bad hiring experience publicly. The numbers reflect a pattern, and patterns compound.

The specific ways unstructured hiring damages trust

Ghost jobs are one of the most visible symptoms of broken hiring communication. When organizations post roles that aren’t actively being filled, or allow listings to sit long after hiring has paused, they erode the credibility of everything else. People apply, hear nothing and draw conclusions about the company, its honesty and its regard for people’s time.

Ghost jobs are only one piece. Vague timelines, repeated interview rounds without explanation and inconsistent updates between stages all create the same corrosive effect: uncertainty. And uncertainty, for most candidates, reads as disrespect.

A 2023 survey found that 40% of applicants were ghosted after multiple interview rounds. Another 35% didn’t receive any acknowledgment of their application. The frustration this generates becomes the story people tell about your brand.

What transparency looks like before the first interview

The recruiters who consistently close strong candidates tend to operate from the same principle: Clarity before the interview is more valuable than a polished pitch during it. What applicants want to understand early is how the process works and what the company genuinely expects. Vague or overly optimistic job descriptions tend to omit all that.

This has practical dimensions, too. Nearly half of job seekers expect to learn about salary before applying. Organizations that include compensation ranges, realistic role descriptions and defined hiring stages self-select for hires who already understand what they’re walking into. The rest of the process gets faster and more honest as a result.

Keeping candidates engaged when decisions take time

Here’s a dynamic recruiters understand but rarely say out loud: Someone can be strong enough to stay in consideration without being strong enough for an immediate decision. Business priorities shift, or budgets change. A role that was well-defined three months ago may have evolved significantly by the time a finalist is being evaluated.

This creates a genuine tension because candidates expect clarity, while recruiters are often working against a moving target internally. The organizations that handle it best are the ones that communicate openly when priorities shift, rather than allowing candidates to sit in silence. A brief update that says the timeline has changed does more for candidate trust than a polished message delivered three weeks late.

Where automation helps and where it doesn’t

Fifty-five percent of candidates hold a negative view of AI in recruitment, citing bias risk and the dehumanizing effect on the process. The concern is the loss of human judgment at moments that feel significant.

Automated systems that handle scheduling or send status updates are useful, but the ones that replace human contact at moments candidates consider meaningful tend to damage trust faster than no communication at all. 

First contact, feedback after interviews, rejection — these are often the moments that define how someone remembers a company.

The long-term business case for getting this right

Candidate experience doesn’t end at the offer — it shapes what comes after. Employees who had an exceptional candidate experience are 3.2 times as likely to feel connected to their organization’s culture long-term, according to Gallup. That process isn’t separate from the employee experience. It’s where it begins.

Those who say they’re unlikely to apply again after a negative experience represent a shrinking future talent pool. The reviews they leave, the conversations they have and the referrals they don’t make are real costs. They accumulate slowly enough that they’re easy to ignore until they aren’t.

Only 14% of organizations have fully implemented their pay transparency approach, according to Mercer’s global survey of over 1,600 companies. For most, transparency is still an aspiration.

Organizations that close that gap build a reputation for being worth working for. That reputation is gained one hiring process at a time. And right now, most companies are leaving it to chance.

A few years ago, a candidate who had a poor experience during recruitment might tell a few friends. Today, they post about it. They leave a Glassdoor review and share screenshots. Hiring has become public in a way most organizations weren’t built to handle.

What I’ve seen, both through building a company and through analyzing how people find and evaluate jobs, is that trust has become the deciding factor in hiring. Job seekers evaluate employers by how clearly and consistently an organization communicates before anyone has been offered a role.

The cost of getting that wrong is measurable: Companies with a poor employer reputation pay at least 10% more per hire, and that’s before accounting for the offers declined, the referrals lost and the reviews that don’t stop.

I try to maintain a growth mindset. That means taking constructive criticism seriously, because I want to properly consider every opportunity to learn how I can improve my business.

But not all criticism is constructive. Sometimes, unsolicited opinions are intentionally shared to disrupt or distract you. And sometimes, advice is simply bad — no matter how good the intentions behind it may be.

The question is: How do you tell the difference between the feedback that helps you grow and the noise that will throw you off track if you pay it too much attention?

My company, Roof Maxx, exists in a highly competitive industry, so we’re used to hearing other people’s opinions. We sell a roof maintenance solution for asphalt shingles that can extend their usable lifespan for years by restoring the flexibility they naturally lose over time. Most of the feedback we receive from customers is overwhelmingly positive; we have over 20,000 online customer reviews with an average rating of 4.9/5 stars. But every so often, we come across misinformation or a divergent opinion about our service and the restoration product it uses.

Here’s how we decide whether these cases are worth addressing, and how you can do the same if you ever find your company receiving confusing or counterproductive feedback.

Any feedback that comes from customers is worth paying attention to

First, let me clarify the above by saying that whenever one of your customers — or potential customers — has questions or concerns, it’s always in your best interest to address them. You never blow off the people you serve. That should be rule number one for pretty much every business.

That’s why we have always remained committed to ensuring dealers respond to customer inquiries quickly. If a homeowner wants to know whether Roof Maxx is right for their roof, a dealer goes to perform a thorough assessment and provide their honest opinion. They only recommend Roof Maxx when the roof is a good candidate, with shingles that are aging or brittle but still in decent structural condition.

Our warranty also guarantees that the asphalt shingles our dealers treat will stay flexible and serviceable for five years from the treatment date. So if a customer ever informs us that their treated shingles are losing flexibility within that window, our dealers are trained to investigate right away and re-treat the area in question if necessary. This doesn’t happen often, but the fact that we demonstrate this kind of accountability to customers is still part of why our reviews are so positive.

Not all feedback comes from customers — or even real people

Like many other businesses, we’ve learned that it’s important to consistently monitor AI platforms for brand mentions. Most of the time, platforms like ChatGPT or Gemini seem to present accurate information about Roof Maxx’s approach to maintaining asphalt shingles. But every so often, I can tell that the data it’s collecting for its responses isn’t entirely accurate.

Here’s one recent example that stuck out to me: that “most consumers love it, while some contractors question it.” This was hugely telling to me, because it speaks to both our stellar reputation among homeowners and the resistance that we’ve occasionally faced from other professionals in an industry we’ve successfully disrupted.

When you think about it, it actually makes sense that some contractors would have a vested interest in criticizing maintenance solutions that make roof replacements less necessary. After all, roof replacements are the highest-margin service a typical roofing contractor can sell, so it’s common for contractors to recommend them — even in cases where a homeowner’s current roof can still be saved.

That means the more homeowners who learn that Roof Maxx is a viable alternative, the fewer unnecessary replacements these contractors are likely to sell. Of course, some of them are going to question it.

What to do when your brand is misrepresented online

It’s always disappointing for me when I see these kinds of results show up in our AI brand mentions, but I also understand that it’s not because we’re doing anything wrong. In fact, it’s the opposite: We’re facing a degree of resistance within our industry precisely because we offer an innovative solution to a common problem, and that’s inconvenient for contractors whose business model depends on customers not having a better option.

Chances are that your AI brand mentions won’t always be perfectly accurate. But they can still be valuable, because studying the discrepancies can reveal a lot about how your competitors perceive you and the messages they’re putting out about your brand. This can set you up to control the narrative.

I use any inaccurate information about Roof Maxx that I find online to update our marketing strategy accordingly. We address false claims head-on in our blog and on our website. Our dealers make speaking to those points a priority when educating potential or existing customers.

What we’ve found is that the best strategy is not to fight misinformation at the source when the source has a clear ulterior motive. We just make sure we’re being as clear and direct as possible when putting the truth out there.

Telling the truth always gives you an advantage because reality will eventually back it up. In our case, that means more glowing reviews and referrals from people who have actually seen the results of our solution firsthand. Eventually, that information outweighs the noise — improving brand awareness among both AI and potential customers everywhere.

I try to maintain a growth mindset. That means taking constructive criticism seriously, because I want to properly consider every opportunity to learn how I can improve my business.

But not all criticism is constructive. Sometimes, unsolicited opinions are intentionally shared to disrupt or distract you. And sometimes, advice is simply bad — no matter how good the intentions behind it may be.

The question is: How do you tell the difference between the feedback that helps you grow and the noise that will throw you off track if you pay it too much attention?

What would you study if you were in college today?

For many college students, majoring in computer science is no longer a job guarantee. According to the Federal Reserve Bank of New York’s labor market data, recent computer science graduates have an unemployment rate of about 6.1%, slightly higher than the 5.7% overall rate for recent graduates. 

Not all hope is lost. The U.S. Bureau of Labor Statistics predicted that software developer jobs will grow 15% from 2024 to 2034, about five times the average for all jobs. So long-term demand for computer science is strong, even as recent graduates face an uphill climb trying to enter the field. 

According to a new report from The Wall Street Journal, experts recommend three alternative majors instead of computer science for students who want to thrive in an AI-dominated workplace: anthropology, mathematics and philosophy. The commonality between these different areas of study is that they thrive where AI falls short. 

For example, anthropology is “the study of what makes us human,” according to the American Anthropological Association. That inquiry feels newly urgent as AI reshapes work and forces people to consider which skills and qualities remain uniquely human. 

Alec Litowitz studied mathematics and anthropology at MIT before adding both a law degree and an MBA to the mix. Throughout his career, including as an early partner in global hedge fund Citadel, Litowitz has repeatedly relied on the insights into human behavior that he gained from anthropology.  

“The beauty of anthropology for me is that I can telescope out and try to understand what’s happening to society right now,” he said in an interview with the Journal. 

Math and philosophy are also strong contenders

Bert Bean, chief executive of Insight Global, a staffing and consulting firm, told the Journal that he brings candidates for AI jobs in for an interview and puts them in front of a whiteboard. Then, the interviewers “throw crazy technical problems” at the candidates to see how they think. 

Math majors excel at this type of assessment. They usually have experience with manual problem-solving, having grappled with hard questions and practiced working them out by hand. 

However, Litowitz, the math-anthropology double major, said that if he were to do it all over again, he would pick philosophy. Ana Prestamo, a recent graduate from the University of Notre Dame, agrees that philosophy is a useful major.

“Studying philosophy, or any of the humanities for that matter, has given me something that artificial intelligence cannot replace: a closer understanding of what makes us human,” she wrote in March in The Observer. “And in a time when AI can solve almost any technical problem, understanding what makes us uniquely human becomes all the more valuable.”

Notably absent from the list of recommended majors is AI. Peter Miscovich, executive managing director at real-estate giant JLL, told the Journal that majoring in AI is “too narrow.” Eventually, saying you majored in AI will “sort of [be] like saying you majored in Excel,” he added.

What would you study if you were in college today?

For many college students, majoring in computer science is no longer a job guarantee. According to the Federal Reserve Bank of New York’s labor market data, recent computer science graduates have an unemployment rate of about 6.1%, slightly higher than the 5.7% overall rate for recent graduates. 

Not all hope is lost. The U.S. Bureau of Labor Statistics predicted that software developer jobs will grow 15% from 2024 to 2034, about five times the average for all jobs. So long-term demand for computer science is strong, even as recent graduates face an uphill climb trying to enter the field. 

The skills that help you build a company are not always the same skills you need to lead it at scale.

When a company is small, the CEO knows almost everything that is happening. You know the people, the clients and where the biggest opportunities are. You are close to the details, and when something goes wrong, you can usually get involved and help fix it yourself.

I remember that stage of my career clearly. There was a certain comfort in being close to everything. Decisions could be made quickly because the distance between a question and the person making the decision was very short.

Then the company grows, markets expand, teams multiply, new offices open, customers come from different parts of the world. Decisions become larger, the consequences become harder to see immediately, and there are simply more things happening than one person can follow.

That is when I learned one of the harder lessons of leadership: The way you lead a company at one stage of its growth can become a limitation at the next. For a CEO, growth requires a change in role.

You stop being the center of every decision

In a growing company, there is a natural temptation to stay involved in everything.

It comes from a good place. You care about the business. You know its history. You have developed instincts that have served you well. You may even believe that your involvement protects the quality of decisions.

Eventually, though, the volume makes that impossible. The more important question becomes whether you have built a team that can make good decisions without you. That question has changed the way I see leadership.

At BGN, we operate across more than 120 countries, with people working across different markets, cultures and areas of expertise. I cannot be in every room where a decision is being made. Nor should I be.

My responsibility is to make sure the people in those rooms understand the direction of the company, the standards we expect and the judgment required to act in its best interests.

That takes time. It also requires trust.

The hardest thing to delegate is judgment

Delegating a task is relatively easy; however, delegating a decision is much harder.

The real test comes when you give someone responsibility for something important and resist the urge to step back in when they approach it differently from the way you would have. That is where leadership gets uncomfortable.

People need room to develop their own judgment. They need to make decisions, learn from the consequences and gradually take on more responsibility.

If a CEO corrects every decision before a person has had the opportunity to own it, that person learns something very quickly: Wait for the CEO. And that is exactly what a growing company cannot afford. The goal is to develop leaders who can think independently while remaining aligned with the company’s values and objectives.

I have found that this takes more than hiring talented people. It requires giving them meaningful responsibility and allowing them to grow into it.

Show me your calendar, and I’ll tell you what kind of CEO you are

One of the clearest signs that a company has changed is the CEO’s calendar.

Early in a company’s life, the calendar can be filled with operational questions: Which customer needs attention? Which deal needs to be closed? Which problem needs solving today?

As the company grows, the most valuable use of a CEO’s time changes. You need to spend more time thinking about where the company should be in three, five or 10 years. Which markets deserve investment? Where should we build? Which capabilities will we need? Who are the leaders who can take the company forward? What should the organization stand for as it grows?

Those questions rarely produce an immediate result: There is no satisfying feeling of crossing something off a list, and yet they may be among the most consequential decisions a CEO makes.

I have become increasingly protective of time for that kind of thinking. A full calendar can create the feeling of productivity while leaving little room for perspective. The larger the company becomes, the more valuable perspective becomes.

You have to let the company become bigger than you

There is a personal side to this transition that people do not talk about enough.

When you have spent years building a business, your identity can become closely connected to it. You know the history. You remember it all: the difficult years, the people who took a chance on the company when it was smaller, the decisions that changed its direction. That history is never truly behind us; it shapes where we go.

But the company also has to develop an identity of its own. If every important relationship, decision or opportunity depends on the CEO personally, the organization remains smaller than its size suggests.

A strong company should be able to carry its values through many people. That means developing leaders who can represent the business with customers and partners as well as giving people enough context to understand why decisions are made. It also means creating a culture where standards remain consistent even when the CEO is not present.

For me, that is one of the most rewarding parts of leadership.

Seeing someone you have developed walk into a room and handle a situation exceptionally well gives you a different kind of satisfaction from solving the problem yourself. You realize the organization is growing its own strength.

The CEO has to keep learning too

There is another trap that comes with seniority: People begin to assume that because you are the CEO, you should already know the answer.

Sometimes you do, but let’s face it — often you do not.

The larger and more international a company becomes, the more important it is to remain curious. Someone who works close to a customer may understand something the executive team has missed. A colleague in another market may see an opportunity that looks invisible from headquarters. A younger member of the team may question an assumption that has been accepted for years.

I want people around me who are willing to challenge my thinking. That requires humility, but it also requires confidence. A leader who feels threatened every time someone disagrees will eventually surround herself with people who agree too easily. That is dangerous for any company.

The CEO has to keep listening, especially when the company becomes large enough for the leader to hear mostly what other people think she wants to hear.

Growth changes the questions

I think about the evolution of leadership through the questions we ask.

When you are building a company, you ask, “How do we make this work?” As the company grows, the question becomes, “Who can make this work without me?” Then it becomes, “How do we build an organization that can keep growing?” And eventually, “What kind of company are we building for the people who will lead it after us?”

That last question changes the perspective completely.

It moves leadership beyond the next deal, the next quarter or even the next stage of growth. It makes you think about culture, talent, reputation and institutional knowledge. It makes you think about whether the company can continue to evolve when the people who built it eventually step aside.

That is a responsibility I take seriously.

Growth should change the CEO too

A company can only grow as far as its leadership is willing to grow with it.

For me, that has meant becoming more comfortable with distance from the details and more deliberate about where my attention belongs. It has meant trusting people with decisions that I once would have wanted to make myself. It has meant accepting that someone else may approach a problem differently and still reach an excellent outcome.

Most importantly, it has meant understanding that leadership at scale is a different job.

The instinct to get involved is still there. So is the satisfaction of solving a difficult problem yourself. But there is a greater satisfaction now in seeing a team solve something that once would have landed on my desk.

That is how you know the company is becoming bigger than its founder, its CEO or any single individual.

And perhaps that is one of the clearest signs that you have built something that can last.

The skills that help you build a company are not always the same skills you need to lead it at scale.

When a company is small, the CEO knows almost everything that is happening. You know the people, the clients and where the biggest opportunities are. You are close to the details, and when something goes wrong, you can usually get involved and help fix it yourself.

I remember that stage of my career clearly. There was a certain comfort in being close to everything. Decisions could be made quickly because the distance between a question and the person making the decision was very short.

Many brands use the U.S. Open to entertain clients or put up flashy signage. IBM does both, but its involvement goes much deeper. Behind the scenes, the century-old tech titan is the invisible hand shaping the fan experience, powering the U.S. Open app, and engaging 14 million fans worldwide. In the process, IBM is making the case that sports might be the perfect playground for AI integration.

The servers behind each serve 

From a fan’s perspective, it seems simple. You open the app, check the score and maybe watch a highlight or two. But making that experience work requires IBM and the USTA to process a mountain of data in real time, using AI alongside human review to balance speed and accuracy. One new metric, Serve Quality, analyzes 21 data points across a player’s body and racquet 50 times per second, generating roughly 4.6 million data points per match and more than 1.2 billion throughout the tournament. And then there’s the match chat, an AI bot that lets users ask conversational questions about the sport, like “what is the record for x?” 

Users appear to be embracing these features, if the numbers are any indication: More than 14 million unique devices engaged with U.S. Open digital platforms in 2025, generating nearly 47 million visits, up 19% year over year.

So why does the USTA need IBM to help run a tennis tournament? To understand that, you have to recognize that the U.S. Open isn’t simply a sporting event. It’s a massive, temporary business operation with millions of customers, enormous amounts of data, and a three-week deadline. That comes with a litany of challenges, from security and bandwidth to content production and infrastructure, that require the scale and experience of a company like IBM.

The USTA is a few-hundred-person team that’s expected to scale monumentally during those three weeks each year. With IBM’s help, however, it can deploy AI-powered tools to streamline infrastructure management, optimize costs, enhance content production workflows, and improve operational resilience. For example, the USTA’s small editorial team uses bespoke AI tools to generate match summaries, which humans then review and edit, increasing the team’s content production capacity by 300%. 

On top of that, an operation as large as the U.S. Open comes with major security risks, and IBM plays a key role in deterring them. According to a spokesperson, IBM protects against nearly 500 million suspicious requests targeting the USTA’s infrastructure and digital platforms. Its AI agents help identify, categorize and prioritize potential threats, allowing the team to respond faster and better protect the USTA’s assets.

Rallying fans around the world  

At the heart of this year’s experience is the all-new Live Updates homepage, a smarter, more personalized way for fans to follow the action that matters most. Fans can prioritize their favorite players and quickly zero in on the matches, insights and stories they care about most. From the World Cup to the NBA Finals, this summer has made one thing clear: demand for sports is exploding, but stadium seats aren’t.

For the millions of fans who can’t afford to attend the tournament or live too far away to travel to New York, these digital experiences let them feel closer to the action.

Here are some of the other new features in the U.S. Open app this year:

1. Match Chat: An AI-powered assistant that lets fans ask free-text questions about live matches and receive instant answers and insights based on match statistics, player information, historical performance, and tournament data. Responses are generated using AI agents and models trained in the USTA’s editorial style and the language of tennis.
2. Live Likelihood to Win: A real-time predictive feature that continuously updates each player’s chances of winning as a match unfolds, using live scores, statistics, and expert analysis. The AI-powered visual representation shows how match momentum is shifting in real time, essentially serving as the heartbeat of the match.
3. Key Moments: A generative AI feature within Live Likelihood to Win that goes a layer deeper, explaining why a player’s chances of winning changed by identifying the points, rallies, and sequences that had the biggest impact on match momentum.

While much has been made of the public’s skepticism toward AI, an IBM study found that sports fans have been fairly receptive. The IBM 2026 Sports Survey found that 80% of fans see value in AI-powered sports experiences, particularly real-time statistics, personalized content and translation. Among tennis fans, 64% said they trust AI-generated sports content.

The study also highlights the importance of having a strong digital presence. IBM found that 73% of tennis fans surveyed use sports apps. In comparison, 91% use them during live events, making a reliable, real-time digital experience increasingly important to how fans consume and engage with sports.

Image Credit: IBM

Playing the long game  

The U.S. Open isn’t IBM’s only sports play. The company is also involved with the UFC, the Masters, and Wimbledon, where it runs similar programs, powering digital platforms and handling data for each respective event. But IBM’s sports strategy extends beyond working with some of the world’s biggest events. It’s also looking at the grassroots level of sports and the startups building its future.

Earlier this year, the USTA launched the inaugural USTA Connect Innovation Challenge, a nationwide open call for tech innovators, engineers and startups to build the next high-impact digital solution for tennis. Selected participants receive access to USTA and U.S. Open data sets to power their prototypes, and a panel that includes USTA representatives, venture capitalists, and an IBM team member evaluates submissions. The top three finalists receive fully funded travel to the USTA Connect event at the 2026 U.S. Open to pitch their ideas, while the grand-prize winner receives $10,000 and exposure across the USTA ecosystem.

More recently, IBM launched the IBM Sports Tech Startup Challenge, which will give founders opportunities to showcase their solutions at Web Summit events in Rio, Vancouver and Lisbon, as well as alongside major tech events including a16z Tech Week in New York and San Francisco. The initiative gives startups a platform to pitch their ideas to audiences at the intersection of sports, technology, and entrepreneurship.

From quietly shaping the fan experience behind the scenes to seeking out the next generation of sports innovators, IBM is proving that even the world’s biggest companies are taking sports seriously. And entrepreneurs should, too.

Many brands use the U.S. Open to entertain clients or put up flashy signage. IBM does both, but its involvement goes much deeper. Behind the scenes, the century-old tech titan is the invisible hand shaping the fan experience, powering the U.S. Open app, and engaging 14 million fans worldwide. In the process, IBM is making the case that sports might be the perfect playground for AI integration.

The servers behind each serve 

From a fan’s perspective, it seems simple. You open the app, check the score and maybe watch a highlight or two. But making that experience work requires IBM and the USTA to process a mountain of data in real time, using AI alongside human review to balance speed and accuracy. One new metric, Serve Quality, analyzes 21 data points across a player’s body and racquet 50 times per second, generating roughly 4.6 million data points per match and more than 1.2 billion throughout the tournament. And then there’s the match chat, an AI bot that lets users ask conversational questions about the sport, like “what is the record for x?” 

Users appear to be embracing these features, if the numbers are any indication: More than 14 million unique devices engaged with U.S. Open digital platforms in 2025, generating nearly 47 million visits, up 19% year over year.