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Are you looking at the careers of successful people, trying to retrace each step they took to get to where they are? It’s a futile endeavor, says OpenAI’s chief economist Aaron “Ronnie” Chatterji. 

Chatterji, who is also a distinguished professor at Duke University, said in a recent interview on the Summation podcast that job-seekers often study success in the hopes of making it their own. Conventional wisdom advises them to look at other people’s resumes and try to replicate their wins. This is “relatively bad advice,” Chatterji said. 

“People often say something like ‘success leaves clues,’ meaning you should follow the paths of other successful people,” Chatterji said. 

However, a successful person’s public resume often omits times of uncertainty, failure and hardship. It is the polished version of their history, not the most truthful. Economic moments shaped the choices they took; their success depended on the environment they lived in, he said. 

“The path that they took whenever they took it was very context dependent,” Chatterji said. “Very rare to find someone self-aware enough to say, you know, the way I did it won’t work for you anymore. It won’t work for anybody.”

Silicon Valley success stories 

When Chatterji spoke, he avoided singling anyone out, but the pattern is hard to miss. Many of Silicon Valley’s most recognizable leaders emerged alongside life-changing technological shifts, situating their success within broader trends. 

For example, Mark Zuckerberg grew Facebook just as widespread Internet access pushed social networking into the mainstream. Meanwhile, Jeff Bezos built Amazon as ecommerce began to take off, and Sam Altman has steered OpenAI through the AI surge. 

“We should use our heroes, our career heroes, our occupational heroes for inspiration but not step-by-step advice,” Chatterji said.

Skills to emphasize

As AI grows more popular, it requires workers to evaluate their skills. Chatterji said that coding, math, formal reasoning and AI skills will be vital in an AI-driven economy. He said that as AI absorbs a growing share of routine work, skills like sound judgment, adaptability and resilience will only grow in importance. 

Other leaders emphasize skills like critical thinking. For example, JPMorgan Chase CEO Jamie Dimon said last year that AI taking over tasks “doesn’t mean that people won’t have other jobs.”

“Learn EQ [emotional quotient or emotional intelligence], learn how to be good in a meeting, how to communicate, how to write,” Dimon told Fox News’ Sunday Morning Futures. “You’ll have plenty of jobs.”

Meanwhile, Meta’s chief AI officer, Alexandr Wang, said last year that AI’s coding abilities were a game changer for him. 

“It’s impossible to understate the degree to which I’ve been radicalized by AI coding,” Wang said on the TBPN podcast.

He said that teenagers should spend “all” of their time vibe-coding, or using AI to generate blocks of code from simple English prompts. He added that teenagers who spend “10,000 hours” getting familiar with AI coding tools have “a huge advantage.”

Are you looking at the careers of successful people, trying to retrace each step they took to get to where they are? It’s a futile endeavor, says OpenAI’s chief economist Aaron “Ronnie” Chatterji. 

Chatterji, who is also a distinguished professor at Duke University, said in a recent interview on the Summation podcast that job-seekers often study success in the hopes of making it their own. Conventional wisdom advises them to look at other people’s resumes and try to replicate their wins. This is “relatively bad advice,” Chatterji said. 

“People often say something like ‘success leaves clues,’ meaning you should follow the paths of other successful people,” Chatterji said. 

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Wade Oney started as a Domino’s store assistant in 1981. Today he owns 112 restaurants across three brands, including 96 Papa Johns locations, and he’s letting his employees in on the big picture success. Bam-Bam Pizza Inc., his franchise group, generates $160 million in annual revenue, Franchising.com reports.

Oney spent over a decade climbing the ranks at Domino’s before Papa Johns lured him away to help grow the then-emerging brand, eventually making him COO. He stepped down in 2000 to focus on being a franchisee full time, scaling from 35 stores to 96 today.

His signature program is letting managers, supervisors and executives buy minority stakes in the restaurants they run. About a third to half of his leadership team now owns a piece of the business. “It helps them know it is a team and a career and not just a job,” Oney said. “That is a pretty cool thing that has happened, and our people love it.”

Wade Oney started as a Domino’s store assistant in 1981. Today he owns 112 restaurants across three brands, including 96 Papa Johns locations, and he’s letting his employees in on the big picture success. Bam-Bam Pizza Inc., his franchise group, generates $160 million in annual revenue, Franchising.com reports.

Oney spent over a decade climbing the ranks at Domino’s before Papa Johns lured him away to help grow the then-emerging brand, eventually making him COO. He stepped down in 2000 to focus on being a franchisee full time, scaling from 35 stores to 96 today.

His signature program is letting managers, supervisors and executives buy minority stakes in the restaurants they run. About a third to half of his leadership team now owns a piece of the business. “It helps them know it is a team and a career and not just a job,” Oney said. “That is a pretty cool thing that has happened, and our people love it.”

Picture a typical day at your office. People typing at desks. Sitting in meetings. Sitting in the kitchen grabbing lunch. You can go through an entire workday without standing up once. That should worry any founder trying to get real output from a team.

I’ve spent nine years building and scaling BetterMe, and if there’s one lesson I keep returning to, it’s this: movement is one of the most underrated drivers of productivity in business, and most companies treat it as a wellness perk instead of infrastructure. A meditation stipend or a gym reimbursement doesn’t fix a workday designed around sitting. Rethinking the workday itself does.

Here’s how I approach it — for myself and for my team.

What happens when people stop moving

Think about a lazy, couch-bound Sunday. After a day like that, do you feel energized? I don’t. I feel sluggish, slower and even simple decisions get harder. That’s the exact state employees end up in after spending a day moving from one chair to another.

The qualities we value most at work — creativity, mental clarity, problem-solving — all rely on good blood flow and oxygen reaching the brain. Movement supports both. When you move, circulation improves, more oxygen reaches the brain and cognitive function sharpens.

There’s a real economic case too. The McKinsey Health Institute estimates that improving employee health and well-being globally could create up to $11.7 trillion in value each year. Much of that comes from higher productivity and less presenteeism — people who are technically at work but nowhere near their full capacity.

What my day actually looks like

Staying physically active isn’t a wellness habit for me. It’s one of the tools that keeps my energy and focus where they need to be. Instead of squeezing in a workout when I can find time, I’ve built movement into the structure of my day.

In the morning, I start with at least an hour of movement. Most days it’s Pilates or yoga. A few times a week I get out for tennis or golf. By the time I sit down to work, I already feel switched on. During the day, I schedule short breaks for stretching, walking or a quick exercise. Even ten minutes can reset your energy. In the evening, I slow things down with quieter mindfulness practices — meditation, chanting mantras and Pranayama breathing. It reduces stress and clears mental noise. When I go to sleep with a calm mind, I wake up more focused.

None of this is unusual. What’s unusual is treating it as non-negotiable and letting it shape how the workday is structured.

The changes that actually move the needle

Culture isn’t purely top-down, but it helps when leadership sends the first signal. When a team sees a founder step away for a walk between meetings, others feel like they can do the same without overthinking it.

From there, a few specific changes make it easier for everyone.

Make the environment movement-friendly. Adjustable desks that let people switch between sitting and standing. Whiteboards, coffee and supplies placed farther from workstations. Open space to stretch or walk between calls. A dedicated recovery zone with soft lighting, plants and a view outside.

Rethink meeting culture. Not every meeting needs to happen sitting down. Turn 1:1s into walks. Make stand-up meetings live up to their name at a standing table. And on some calls, make cameras optional — say upfront that they can stay off so people feel free to stretch, walk or move while listening. That one change did more for our meeting culture than anything else we tried.

Create shared rituals. A quick stretch before any meeting that runs more than an hour. A short exercise after 30 minutes of sitting. A Friday step-count check-in with a weekly leaderboard. Small habits, shared by the team, give the day structure.

Make it social. It’s easier to stay consistent when you’re not doing it alone. Sign up for a step challenge as a team. Turn team-building events into something active — badminton instead of drinks. Set up a Slack channel to share progress and small wins.

Block it on the calendar. If it’s not scheduled, it’s easy to skip. Encourage employees to block windows for movement resets. When people see those blocks on each other’s calendars, stepping away stops feeling like something only they do.

The point isn’t to turn the office into a gym. It’s to stop pretending that eight hours of sitting produces the best version of the people you hired.

Why this compounds

A study from Oxford University’s Saïd Business School found workers are 13% more productive when they feel better at work. Movement is one of the most direct, cheapest levers a leader has to move that number.

Strong teams don’t just brainstorm together. They move together.

And if it’s been a while since you last stood up, this is a good moment to do it — and to show your team it’s okay to do the same.

Picture a typical day at your office. People typing at desks. Sitting in meetings. Sitting in the kitchen grabbing lunch. You can go through an entire workday without standing up once. That should worry any founder trying to get real output from a team.

I’ve spent nine years building and scaling BetterMe, and if there’s one lesson I keep returning to, it’s this: movement is one of the most underrated drivers of productivity in business, and most companies treat it as a wellness perk instead of infrastructure. A meditation stipend or a gym reimbursement doesn’t fix a workday designed around sitting. Rethinking the workday itself does.

Here’s how I approach it — for myself and for my team.

I was finishing my doctorate. I had two teenagers, one across the country at boarding school. I was working full-time, flying cross-country for school visits, writing and analyzing data in every available hour. Everyone said I was impressive. I was barely managing.

One morning, I arrived to back-to-back meetings on less than four hours of sleep. I had not eaten. My daughter had called in tears the night before. I walked into my office, closed the door and cried. Then I made a spreadsheet. I listed everything I was doing and calculated the cost. 60% of my time was going toward activities contributing to 10% of my actual goals.

The question shifted. Not “how do I fit more in?” but “what can I cut?” Within six months, I had eliminated 30 hours of weekly commitments. I finished my dissertation. My performance improved. And I got clear on my next move. The problem was never capacity. It was strategy.

Black women have always understood this. Domestic workers raising other people’s children while raising their own did not succeed by doing more. They succeeded by doing what was essential and letting go of the rest. My research put numbers to what they already knew.

This is what I call the 60/10 problem. Based on research across more than 600 Black women professionals, most are spending roughly 60% of their time on activities that organizations say matter. Those same activities account for only about 10% of what actually drives advancement. Following the signals. Showing up. Getting exhausted. Not getting promoted. Here is what is actually happening.

Where women’s time actually goes

The work companies publicly value

This includes committees, development programs, employee initiatives and external visibility. Women say yes to this work because it aligns with what the organization promotes. It feels meaningful. It signals commitment. The issue is that much of this work is performative when it comes to advancement — it is visible, but it is not always tied to decision-making power. These are vanity metrics, easy to count but not connected to what actually drives promotions.

This is not a personal failure. Organizations built these signals, and organizations need to change them. If your company measures ERG participation and conference appearances but not internal visibility and decision-maker access, your measurement system is producing the wrong outcomes.

The work women feel responsible to carry

This is the invisible layer. Mentoring others. Supporting team culture. Managing conflict. Bridging gaps across teams. For Black women, add another tax on top: code-switching, being the unofficial spokesperson for an entire demographic, carrying the organization’s moral compass while the organization carries none of the weight. This work sustains organizations. It almost never translates into promotion.

The work that fills the space

Then there is everything else — meetings without clear outcomes, committees that produce reports nobody reads. High-performing women become the default solution. That reputation is real, and it is also a ceiling, because reliability isn’t what drives promotion.

A strategy reset: the 4-question audit

The shift starts with a simple question: If I continue doing this for the next six months, does it increase the likelihood of promotion? Most women have never been asked to evaluate their work this way. They are evaluated on performance, responsiveness and contribution, so they keep doing more of what is asked, assuming it will eventually lead somewhere. This audit interrupts that pattern.

Start by writing down everything you do on a regular basis — meetings, projects, committees, mentoring, external work, informal responsibilities people rely on you for. Include the work that lives outside your job description but still takes your time. Then evaluate each item using four questions.

1. Does this have a direct line to the people who make decisions about my advancement?

This is the question most people skip. Every organization has a real decision-making process, whether it is written down or not. Promotions are driven by specific leaders, priorities and outcomes. If you cannot clearly connect an activity to those decisions, it may be valuable work — but it is not strategic for your advancement.

2. What has this actually produced so far?

Not what it was supposed to produce. Not what it could produce. What has it actually produced?

• Has it led to increased visibility with decision-makers?
• Has it resulted in measurable outcomes?
• Has it changed how leadership sees your capabilities?

This question forces you to move from intention to evidence.

3. What does it cost me in time and energy?

Women are often taught to focus on output, not cost. But every activity has a price. Some work looks small but drains significant energy. Some commitments expand quietly over time. Some roles require emotional labor that is never accounted for. If something is high-cost and low-return, your time with it should be reduced.

4. Am I doing this because it advances me, or because someone asked and I said yes?

Women are often responsive. Reliable. The ones who step in. But being asked to do something and being advanced because of it are not the same. This question creates a pause between the request and the acceptance. One more practice: stop saying yes immediately. “Let me think about that” is a complete answer. It creates space between the request and your commitment.

The shift that moves careers

This is not a time management problem. Time management lets organizations off the hook. This is a strategy problem: organizations reward the wrong things, high-performing women follow those signals in good faith, and they end up exhausted with careers that aren’t moving.

The reset is simple. Stop measuring effort. Start measuring access. At the end of every week, ask one question: Did anything I did move me closer to the people who determine my next opportunity? If the answer is consistently no, the audit needs to go deeper.

And if you lead an organization, the same question applies. If the activities you reward aren’t the ones that drive advancement, you are not running a broken pipeline — you are running a misaligned measurement system. The fix is not more programs. It is better metrics. That is the work. Not just for you. For the systems around you.

I was finishing my doctorate. I had two teenagers, one across the country at boarding school. I was working full-time, flying cross-country for school visits, writing and analyzing data in every available hour. Everyone said I was impressive. I was barely managing.

One morning, I arrived to back-to-back meetings on less than four hours of sleep. I had not eaten. My daughter had called in tears the night before. I walked into my office, closed the door and cried. Then I made a spreadsheet. I listed everything I was doing and calculated the cost. 60% of my time was going toward activities contributing to 10% of my actual goals.

The question shifted. Not “how do I fit more in?” but “what can I cut?” Within six months, I had eliminated 30 hours of weekly commitments. I finished my dissertation. My performance improved. And I got clear on my next move. The problem was never capacity. It was strategy.

In 1975, a 17-year-old named Peter Cancro bought his first sub shop in Point Pleasant, New Jersey. On Wednesday, that shop’s parent company went public at a $7.3 billion valuation. Jersey Mike’s and its backers raised $1 billion in an IPO priced at $23 a share, more than 10 times oversubscribed, Bloomberg reports.

The chain now has more than 3,300 US and Canadian locations, plus an expansion deal with Cancro to open roughly 300 more across the UK and Ireland. Revenue grew 11% to $724 million last year, and Jersey Mike’s US sales growth has outpaced rivals like Jimmy John’s, while Subway has actually declined, as diners lean toward sandwiches over pricier bowl concepts.

Blackstone, which bought Jersey Mike’s last year for about $8 billion including debt, will retain 68% of voting power after the IPO. Cancro stepped back from CEO to chairman in April, handing the role to Charlie Morrison, who previously ran Wingstop and Salad and Go. Shares began trading Thursday on the NYSE under the ticker JMKE.

In 1975, a 17-year-old named Peter Cancro bought his first sub shop in Point Pleasant, New Jersey. On Wednesday, that shop’s parent company went public at a $7.3 billion valuation. Jersey Mike’s and its backers raised $1 billion in an IPO priced at $23 a share, more than 10 times oversubscribed, Bloomberg reports.

The chain now has more than 3,300 US and Canadian locations, plus an expansion deal with Cancro to open roughly 300 more across the UK and Ireland. Revenue grew 11% to $724 million last year, and Jersey Mike’s US sales growth has outpaced rivals like Jimmy John’s, while Subway has actually declined, as diners lean toward sandwiches over pricier bowl concepts.

Blackstone, which bought Jersey Mike’s last year for about $8 billion including debt, will retain 68% of voting power after the IPO. Cancro stepped back from CEO to chairman in April, handing the role to Charlie Morrison, who previously ran Wingstop and Salad and Go. Shares began trading Thursday on the NYSE under the ticker JMKE.

Most leaders assume performance problems start with talent. When a project misses the mark or engagement drops, the instinct is to question whether the right people are in the right seats. After years of leading schools, I have learned a different lesson: most performance problems are communication problems wearing a talent costume.

The people on your team may be highly capable. The real question is whether they have the support required to perform at their best. I learned this long before I became a business owner. I learned it standing in a classroom.

People don’t know what’s expected

As a teacher, I quickly discovered that capability and performance are two different things. I had students who were eager to learn but struggled to complete assignments or meet expectations. It would have been easy to label them as underperformers. Instead, I learned to ask a better question: have I made success clear enough for them to achieve it?

The same lesson applies to adults. One of the biggest mistakes I made early in leadership was assuming that because I explained something, people understood it. I would paint beautiful pictures of the future I was building and walk everyone through the reasoning behind a decision, believing that all that explanation would create understanding. People were still leaving meetings with unanswered questions — chief among them: how does this affect me?

When expectations are vague, people fill in the blanks themselves. That creates inevitable confusion and frustration. Whenever I introduce a new initiative or process now, I run it through five questions:

• What needs to happen?
• Who owns it?
• When is it due?
• Why does it matter?
• How will it affect each person involved?

Clarity removes guesswork. When people know exactly what success looks like, performance improves dramatically.

People don’t feel safe speaking up

Many leaders say they want feedback but fail to create an environment where feedback feels safe. Psychological safety has become a popular leadership topic, but its impact remains deeply practical: if people fear being punished for speaking honestly, valuable information never reaches leadership. That silence becomes expensive.

One of the strongest teams I ever led included employees who challenged my thinking regularly. Those conversations were sometimes uncomfortable, but they pointed out blind spots and highlighted issues I couldn’t see from my position. Those employees became some of my most trusted team members — because honesty is a form of commitment. People who care enough to tell you the truth are helping you improve. People who stay silent while problems grow are usually protecting themselves.

Leaders often assume employees hold back because they lack confidence. In many cases, employees hold back because previous experiences taught them that honesty comes with consequences. If you want better communication, examine your reaction to difficult feedback. Do people leave conversations feeling heard, or feeling punished? Your response teaches them whether speaking up is worth the risk.

Leaders assume understanding instead of confirming it

I learned this the hard way when a leadership team questioned an employee rewards program I had implemented. I thought the reasoning was obvious. It turned out I had explained what we were doing but never why. Once I walked them through the financial benefits for both employees and the business, the confusion disappeared. What I thought was resistance was simply an incomplete understanding.

Communication is only successful when the other person understands the message the way you intended it. Instead of asking, “Any questions?” try asking, “How do you see this working?” Their answer will quickly reveal whether alignment actually exists.

How to know if your team feels safe

Many leaders believe they have an open-door policy. The better question is whether people actually walk through the door.

One of the most effective tools I’ve used is anonymous feedback surveys. But the key isn’t the survey itself — it’s what happens after. Too many organizations collect feedback and never act on it. Employees notice, and trust declines fast.

Recently, I conducted a survey with leadership teams across my organization. The feedback revealed a consistent need for additional classroom support. Based on that input, we restructured resources and made significant staffing changes. The survey mattered because the feedback led to action. Trust grows when people see evidence that their voice influences decisions.

If your team consistently shares ideas along with constructive criticism, that is usually a sign of safety. If everyone agrees with everything you say, you may have a communication problem hiding beneath the surface.

A weekly clarity check-in

Improving communication doesn’t require complicated systems. Start with a simple weekly check-in built around three questions:

• What is your top priority this week?
• What obstacles are slowing progress?
• What support do you need from me?

These conversations create alignment, uncover challenges early and reinforce accountability. More importantly, they give employees space to speak honestly before frustration turns into disengagement.

The team you need may already be there

The strongest teams are built through clarity, trust and consistent communication. When people understand what is expected of them, feel comfortable raising concerns and have confidence that their leaders are listening, performance tends to follow.

It’s easy to look at a struggling team and search for individual weaknesses. But our job as leaders is to examine the environment we have created around them. That’s often where the real opportunity is. The way we communicate and clarify expectations shapes how people show up every day.

Most leaders assume performance problems start with talent. When a project misses the mark or engagement drops, the instinct is to question whether the right people are in the right seats. After years of leading schools, I have learned a different lesson: most performance problems are communication problems wearing a talent costume.

The people on your team may be highly capable. The real question is whether they have the support required to perform at their best. I learned this long before I became a business owner. I learned it standing in a classroom.

People don’t know what’s expected

As a teacher, I quickly discovered that capability and performance are two different things. I had students who were eager to learn but struggled to complete assignments or meet expectations. It would have been easy to label them as underperformers. Instead, I learned to ask a better question: have I made success clear enough for them to achieve it?

According to a recent report, 94% of 250 surveyed enterprise C-level executives plan to ramp up spending on AI visibility efforts in 2026. However, while almost all executives agree that generative engine optimization had a positive impact on their business in the previous year, a HubSpot study showed that 32.5% of marketers have no clue how to monitor AI citations — let alone measure their impact.

Unlike traditional search optimization, tracking a brand’s AI visibility isn’t as easy as opening Search Console. For many businesses, it’s not even as easy as signing up for an Ahrefs subscription — although there are already similarly designed products available. The truth is that the most effective AI visibility tracking requires a layered approach. Here’s the system I’ve been running since the start of 2026.

1. Get clear on what you’re actually tracking

Before you touch a single tool, decide what success looks like. In my experience, most founders lump together several very different signals and then wonder why their reporting tells them nothing useful.

The first is citations. A citation is when an AI engine links to your website or clearly uses your page as a source inside its answer. It is the closest thing AI visibility has to a traditional SEO signal, which is why so many teams start there.

The second is mentions. A mention is when your brand name appears inside the response, whether or not the AI links back to you. Mentions matter because they show your brand is part of the model’s vocabulary on a topic. But mentions can also flatter you. A brand can be mentioned as a passing example and still lose the commercial intent of the query.

That is why I treat recommendations as a third and separate metric. This is the question that matters most: When someone asks for the best option, does the AI actually suggest your product, company or service, or does it just acknowledge that you exist? As I wrote in my previous Entrepreneur piece on how AI recommends local businesses, being visible and being recommended are not the same thing.

If you only track citations, you can end up celebrating movement that never turns into revenue. Track citations, mentions and recommendations separately, or your reporting will blur the thing you actually care about.

2. Build a prompt library that sounds like a real customer

Nothing in AI visibility works without a serious prompt library filled with the questions a real buyer would ask to discover a brand like yours.

I always start manually. Before I ask any AI tool for help, I write the first 10 to 20 prompts myself. That matters because you already know the language your customers use, the objections they have and the competitors they compare you against. Start with the obvious commercial prompts, then expand into comparison queries, pain-point queries, and local variations.

Good prompt libraries also need specifics. Add city names where geography matters. Add competitor names where comparison matters. Add budget, company size, use case or industry where those filters would realistically shape the answer. OpenAI’s own data shows how conversational ChatGPT usage has become, which means generic one-line prompts often miss how people actually search.

Once you have that manual base, use Claude or ChatGPT to generate variants and cluster them by intent.

It’s better to have 50 good prompts than 300 bloated ones. Too few prompts and you miss the long tail. Too many, and you start tracking noise instead of buying intent.

3. Use platforms for scale, but understand their limits

A growing number of tools now cover AI visibility directly, including Peec, Semrush, Ahrefs and DataForSEO. What makes them useful is not just that they collect data. It is that they make the data operational.

A good platform can track multiple engines at once, automate daily checks, visualize trend changes, generate reports for your team and often let you set a location. Some also suggest new prompts to monitor, identify competitors you had not considered and surface content gaps that may be hurting your visibility. Once you spend the time setting them up properly, the maintenance burden is relatively low.

But there is a big catch. A lot of this tracking still depends on search-enabled environments, model snapshots or vendor-specific ways of querying the models. 

That matters because the answer a user gets from a live AI session can look very different depending on whether web search is active, what context is available and how the system decides to compose the response. In other words, platform data can be directionally useful without being a perfect reflection of what every real user sees.

This is where teams get overconfident. They subscribe to a dashboard, see a neat visibility chart and assume they now understand the market. They do not. They understand one layer of it.

That does not make the tools useless. It just means you should treat them as monitoring infrastructure, not ground truth. For a useful overview of how these products fit together, this guide on measuring AI visibility in 2026 is a solid reference point.

4. Keep a manual tracking layer for the prompts that matter most

The most labor-intensive part of AI visibility tracking is also the most revealing. Once a month, I like to take the most commercially important prompts from my library and run them manually across ChatGPT, Claude and Gemini in fresh chats.

The point of doing this is control. You can test the exact prompt phrasing, add the location directly into the query when geography matters and compare outputs side by side. You also get the full richness of the response instead of a summarized score inside a platform dashboard.

From there, I save the responses and use a high-reasoning model to analyze them. I want a clean breakdown of how often my brand was cited, how often it was mentioned, whether it was actively recommended, how prominently competitors appeared and what patterns keep repeating across answers. You can also use this layer to ask for hypotheses about why certain competitors keep outperforming you on specific prompts.

This approach takes more effort, but it gives you something automated tools often flatten: context. You see not just whether your brand showed up, but how it showed up and what narrative surrounded it.

In practice, the best setup is usually hybrid. Use a platform subscription to monitor broader patterns, and use manual checks on the prompts that actually matter to your pipeline.

5. Measure business impact, not just AI visibility

Visibility is interesting. Impact is what pays for the work.

The most obvious place to start is Google Analytics. Track identifiable AI referral traffic where possible and monitor how those visitors behave compared with other channels. That still will not show you the full picture, because some people will discover your brand through an AI answer and come back later through a branded search, direct visit or referral.

That is why I also like simple operational fixes. Add “AI assistant” as an answer option to your “How did you hear about us?” field. If your business uses sales calls, train the team to ask whether the lead first heard about you through ChatGPT, Claude, Gemini or another AI tool. It sounds basic, but this kind of qualitative data becomes surprisingly valuable once patterns start repeating.

Watch for indirect signals too. When your recommendation rate improves on important prompts, do branded search, demo requests and direct traffic rise soon after? If your visibility numbers look better but none of those downstream indicators move, something in the chain is broken.

According to a recent report, 94% of 250 surveyed enterprise C-level executives plan to ramp up spending on AI visibility efforts in 2026. However, while almost all executives agree that generative engine optimization had a positive impact on their business in the previous year, a HubSpot study showed that 32.5% of marketers have no clue how to monitor AI citations — let alone measure their impact.

Unlike traditional search optimization, tracking a brand’s AI visibility isn’t as easy as opening Search Console. For many businesses, it’s not even as easy as signing up for an Ahrefs subscription — although there are already similarly designed products available. The truth is that the most effective AI visibility tracking requires a layered approach. Here’s the system I’ve been running since the start of 2026.

1. Get clear on what you’re actually tracking

Before you touch a single tool, decide what success looks like. In my experience, most founders lump together several very different signals and then wonder why their reporting tells them nothing useful.

Key takeaways

• When buyers ask AI platforms hyper-specific, bottom-of-funnel questions, the models often hedge, hallucinate, or contradict themselves — because the authoritative source material simply isn’t there.
• The founders who publish clear, structured answers into those gaps first will become the default response AI gives for years to come.

Identifying the gap between what people want to know and the information available to them is the game — and good SEO practitioners have been playing it for years.

Generative AI is just the next evolution of that process. Traditional search shows you what people are asking. Generative AI exposes something more valuable: the high-intent questions that search engines still answer poorly. That’s the opportunity.

Stop optimizing where everyone else is

Founders naturally focus on what’s visible when building strategy. Competitive analysis provides benchmarks. Market research examines established demand. Industry commentary reveals dominant trends. Everyone looks at the same signals — which is exactly why so many strategies end up looking identical.

In traditional SEO, this shows up as fighting for contested keywords and racing to outbuild backlink profiles just to land a spot under AI Overviews and sponsored ads. Marketing budgets drain quickly, and returns rarely follow.

With Generative Engine Optimization (GEO), search has shifted from keywords to intent. Platforms like ChatGPT, Claude, Gemini and Perplexity are now where people compare products and services. Users aren’t searching in fragments anymore; they’re writing full sentences and expecting full answers.

If you want your brand recommended first in that environment, understand what these systems actually reward: the most structured, authoritative and complete knowledge on a topic. Keywords no longer determine rank. What matters is how thoroughly and clearly your company is represented to the world.

How negative space reveals opportunity

When a buyer asks a bottom-of-funnel question and the retrieval pool is thin or non-existent, the model comes unstuck. AI is trained to answer confidently — so when the information it needs is missing, incomplete or poorly structured, it hedges, invents or contradicts itself.

That’s negative space: the unanswered questions, the under-explained problems, the contradictory responses, the outright hallucinations. It exposes what’s absent from the knowledge base these models draw from.

If your brand isn’t present in that space when prospects are asking the questions that precede a decision, you’re losing deals you never knew existed.

These gaps won’t stay empty forever. The companies that publish authoritative content into them first will shape how future AI responses are generated. Timing is the competitive advantage.

Why targeting negative space matters

Targeting negative space creates informational authority where none currently exists. It’s an evolution beyond competing for visibility.

Most companies optimize for visible demand — and as traditional SEO has shown, that market is saturated, costly and difficult to rise above. Negative space, by contrast, is unmapped territory. Most companies don’t yet realize it exists. Where definitions are inconsistent and structured knowledge is incomplete, there’s room to become the answer.

The work is to find the questions where AI responses lack depth, structure or clarity, and provide the authoritative explanation. Instead of creating content for top-of-funnel curiosity, focus on the questions prospects ask when they’re preparing to make a decision. If your answer is the one they encounter — clear, credible, complete — they’ll remember it.

Strategy shifts from volume to informational leverage. AI systems don’t rank pages; they use them to construct an answer. A single, well-structured, explanatory article beats a stack of SEO-optimized copy. When your content is the first authoritative source — entity-structured, statistic-rich, citation-heavy — the AI is more likely to draw from it.

From visibility to authority

Negative space is the gap between what your prospects are trying to find out and what AI can confidently answer. Where traditional SEO optimizes for attention, AI SEO builds better interpretations for AI systems. That’s the next real competitive advantage.

Be the first credible explanation in an empty space, and you don’t just show up in the answer — you define how the topic is understood, and you’re front and center at the moment prospects are ready to act.

Key takeaways

• When buyers ask AI platforms hyper-specific, bottom-of-funnel questions, the models often hedge, hallucinate, or contradict themselves — because the authoritative source material simply isn’t there.
• The founders who publish clear, structured answers into those gaps first will become the default response AI gives for years to come.

Identifying the gap between what people want to know and the information available to them is the game — and good SEO practitioners have been playing it for years.

Generative AI is just the next evolution of that process. Traditional search shows you what people are asking. Generative AI exposes something more valuable: the high-intent questions that search engines still answer poorly. That’s the opportunity.

Stop optimizing where everyone else is

Founders naturally focus on what’s visible when building strategy. Competitive analysis provides benchmarks. Market research examines established demand. Industry commentary reveals dominant trends. Everyone looks at the same signals — which is exactly why so many strategies end up looking identical.

You’re doing the work. The phones are ringing and your reviews look good. But you’ve noticed that your leads are not the same as they were last year. Referrals that used to flow in steadily have slowed as well. You’re not losing deals. You are losing the opportunity to compete for them like you used to.

The number that should concern you: 46%. I studied 400 companies across five industries. That’s the percentage of business owners who are completely invisible to AI. Not underperforming. Not dropping to page two. Gone. When a prospect asks ChatGPT, Perplexity or any AI assistant for a recommendation, nearly half of all business owners I studied are invisible in the answer.

And here’s the part that should surprise you: Your company may show up, but if the owner behind it is not visible, AI treats the business differently. The algorithm appreciates the company info but craves information about the owner or key person in the business — who is the human behind the brand and are they credible?

The gap that nobody is talking about

Companies where both the owner and the business were visible to AI saw an average year-over-year traffic increase of 2.5%. Companies where both were invisible? Down over 28%. That’s a 30% difference — same industries, same time frame. The difference is whether the person behind the company had any presence in places AI considers trustworthy.

On the surface, a 2.5% increase seems minimal. However, Gartner research predicts that organic traffic to websites will drop by 25% this year. Over the next three years, that kind of gap translates into millions of dollars in revenue the invisible owners never enter their sales funnel — not because the work was bad, not because the market or economy shifted, but because humans and machines couldn’t see who was behind the company. This is not a marketing problem or a traditional SEO problem.

I know what you’re thinking: “So I need to post more on social media.” Nope. This is an entity recognition problem. AI doesn’t really care about your Instagram reels or TikTok followers. It cares whether you are credible on the platforms AI approves as relevant to your expertise and authority. The venues change often, but the basics include published articles, podcast appearances, speaking engagements, industry directories and local press. The common thread: places where you are findable and verifiable.

Think of it this way: Would you hire a contractor with no reviews, no references and no one who could vouch for them? AI works the same way. It loves third-party signals of trust.

The owner is the multiplier

Here’s what surprised me in the research: The company’s brand visibility matters, but the owner’s visibility is the multiplier. A business with a strong brand and an invisible owner underperforms a business with a strong brand and a visible owner or subject-matter expert — every time. The owner’s visibility doesn’t just add to the company’s credibility; it amplifies it.

This makes sense if you think about it from the customer’s point of view. People want to know who they’re trusting with their money, their home, their family’s health. A faceless logo doesn’t answer that question. A person does. AI is simply reflecting what humans have always deferred to: I trust people more than brands.

What invisible owners get wrong

Most invisible owners are busy running their business. They’re not hiding on purpose. They assume their work speaks for itself. They’ve convinced themselves that marketing can handle visibility for the company.

But the world has shifted. Your prospects aren’t searching on Google alone anymore — they’re asking AI to help them decide. And AI builds its recommendations from a variety of sources and trust signals most business owners aren’t knowledgeable about.

The good news is that you don’t need to become a content machine. You don’t need to go viral. You need to exist in the places that matter to AI. Get your name in a local business journal with your point of view related to your industry. Show up on someone else’s podcast. Speak at your Rotary club or chamber event. Film it with your phone and post it to LinkedIn and YouTube. Share what you know in a way that helps people. Forget the sales pitch. Provide genuine value. When you teach, you build authority. When you build authority, AI pays attention.

The question you need to ask yourself

If someone asks an AI assistant to recommend a business like yours in the area, does your name show up? Not your company’s name — your name. Check it now.

The data is clear. When the owner is invisible, the company pays the price. When the owner is visible, everything compounds: trust, referrals, traffic, revenue. You built the business. You hired the team. You took the risk. The one thing you need to focus on now? Let the people — and the machines — know who’s behind it all.

That’s the invisible owner problem. And 46% of you are living it right now. The good news is that visibility isn’t reserved for people with PR teams and huge marketing budgets. It’s available for any owner willing to step out from behind their logo and be known for what they do.

You’re doing the work. The phones are ringing and your reviews look good. But you’ve noticed that your leads are not the same as they were last year. Referrals that used to flow in steadily have slowed as well. You’re not losing deals. You are losing the opportunity to compete for them like you used to.

The number that should concern you: 46%. I studied 400 companies across five industries. That’s the percentage of business owners who are completely invisible to AI. Not underperforming. Not dropping to page two. Gone. When a prospect asks ChatGPT, Perplexity or any AI assistant for a recommendation, nearly half of all business owners I studied are invisible in the answer.

And here’s the part that should surprise you: Your company may show up, but if the owner behind it is not visible, AI treats the business differently. The algorithm appreciates the company info but craves information about the owner or key person in the business — who is the human behind the brand and are they credible?