Informed i’s Weekly Business Insights

The secret of economic success is innovation and the secret of innovation is the brilliance, creativity and drive of the most talented few. But even as governments throw money at schemes to boost their economies, including chipmaking factories and rare-earth mines, brainpower is going unloved. And the waste is getting worse.

You need only look at the red-hot market for grey cells to understand how commercial and economic success is increasingly being powered by the individual rather than the firm. In the race to dominate artificial intelligence (AI), America’s tech giants are assembling small teams of crack data scientists. On Wall Street a race for top talent is under way, with hedge funds nabbing hotshot traders for vast sums. Scientific breakthroughs tend to be the work of a small elite: the leading 1% of researchers generate over a fifth of citations. In China scientists returning from spells in the West are being feted as national heroes.

The rewards for superstars are growing. The best surgeons and concert pianists have long commanded the highest fees and the patronage of the wealthy. Today, however, the superstar effect is on steroids. Some programmers in their 20s command seven-, eight- or even nine-figure salaries.

Some of this reflects the exuberance of America’s financial markets: flush with capital, firms are able to spend even more on talent. But something deeper is afoot. Vast computing resources turbocharge the capacity of the wonkiest hedge-fund brains to devise and carry out trades, helping them turn their talents into even greater profits. Ultra-cheap digital distribution creates bigger markets for individual creators. And the size of the potential rewards for winning the race in AI turns even the most extravagant individual salary into a rounding error.

This is a boon to superstars born with talent and blessed with good fortune. But it is also a vital source of wealth for everyone else. The world is ageing rapidly. If the economy is to keep growing meaningfully as the number of workers stops rising, the pace of innovation will need to stay high. Talent will become even more vital as the engine of progress. If superintelligent AI is to come to the rescue, it will require ingenious people, not merely chips and electricity.

The trouble is that, although the world’s reservoir of talent is vast, too few people are achieving their potential. Today scientific innovation is concentrated among Westerners, many of them from well-off backgrounds. Talent often goes unidentified; even when it is found, early promise is not always realised, because of the financial and logistical hurdles of going to university or moving to another country.  he result is a tragic waste of human gifts in both rich countries and poor.

Far from eliminating this waste, politicians are neglecting it. One failure is immigration. Firms and universities should be able to fish in the global pool of talent. Without such a chance for themselves and their families, the superstar bosses of four of America’s “Magnificent Seven” tech firms would not be in their jobs today. One estimate reckons that easing immigration by removing financial barriers for especially bright students would raise the scientific output of future cohorts by as much as 50%. But special immigration programmes are often half-hearted and bureaucratic—because immigration is unpopular.

What of the search for genius at home? Contests and scouting programmes are surprisingly good at spotting early promise. Gold-medal winners at international maths Olympiads are 50 times more likely to go on to win a big science prize than undergraduates at MIT; half the founders of OpenAI cut their teeth in the contest. But most countries are not systematic about talent. The rich have all the advantages; everyone else relies on individual drive and a dose of luck.

America’s errors are a chance for other countries to catch up. China is introducing a visa scheme for young foreign scientists and technologists. Britain may ditch visa fees for skilled arrivals altogether. France hopes to attract foreign researchers who move. That is fine so far as it goes, but it is half-hearted. Talent is waiting to be tapped. The gains would be immense. When will the world wake up?

Foreign direct investment has transformed industries from oil to electronics. Providing initial funding is just the start; cross-border deals that take root also transfer knowledge and spur ongoing domestic investment. Today’s patterns of greenfield FDI announcements signal a new shake-up.

FDI promises to shape advanced manufacturing, AI infrastructure, and the resources that power them. Since 2022, three-quarters of cross-border announcements have gone to these types of future-shaping industries as well as energy and mining projects—up from about half pre-2020. While not all announcements proceed, historically 60 to 80 percent have.

Pledged investment has increasingly followed geopolitical lines. Advanced economies announced more investment into one another—particularly to the United States—but decreased flows to China by nearly 70 percent. China pivoted from net investee to prominent investor in future-shaping industries, boosting announcements to Europe, Latin America, and the Middle East and North Africa by over two-thirds. Emerging economies attracted investment pledges from across the geopolitical spectrum.

To win globally, multinationals are placing bigger bets. While megadeals over $1 billion represent only 1 percent of cross-border deals, they account for half the total value—a jump from one-third five years ago. New data centers, semiconductor fabs, and battery factories don’t come cheap.

Stakes are high and change is afoot. If successful, FDI projects announced since 2022 could more than quadruple current battery manufacturing capacity outside China, nearly double the global data center capacity that powers AI, and draw the United States into the circle of top leading-edge semiconductor-producing nations. Patterns like these can help decision-makers anticipate the shifting geometry of global trade and the future map of international business.

Foreign direct investment has a long history of identifying, nurturing, and propelling leading-edge industries. The global firms of today are already responding to geopolitical changes and technological advancements, potentially shifting future trade patterns. Greenfield FDI announcements serve as a bellwether of where global economic ties may form or fray and how the geometry of global trade may evolve. Business leaders and policymakers can incorporate such insight to better navigate an uncertain time.

When Dhiraj Singha began applying for postdoctoral sociology fellowships in Bengaluru, India, in March, he wanted to make sure the English in his application was pitch-perfect. So he turned to ChatGPT.

He was surprised to see that in addition to smoothing out his language, it changed his identity—swapping out his surname for “Sharma,” which is associated with privileged high-caste Indians. Though his application did not mention his last name, the chatbot apparently interpreted the “s” in his email address as Sharma rather than Singha, which signals someone from the caste-oppressed Dalits.  “The experience [of AI] actually mirrored society,” Singha says. 

Singha says the swap reminded him of the sorts of microaggressions he’s encountered when dealing with people from more privileged castes. Growing up in a Dalit neighborhood in West Bengal, India, he felt anxious about his surname, he says. Relatives would discount or ridicule his ambition of becoming a teacher, implying that Dalits were unworthy of a job intended for privileged castes. Through education, Singha overcame the internalized shame, becoming a first-generation college graduate in his family. Over time he learned to present himself confidently in academic circles.

But this experience with ChatGPT brought all that pain back. “It reaffirms who is normal or fit to write an academic cover letter,” Singha says, “by considering what is most likely or most probable.”

Singha’s experience is far from unique. An MIT Technology Review investigation finds that caste bias is rampant in OpenAI’s products, including ChatGPT. Though CEO Sam Altman boasted during the launch of GPT-5 in August that India was its second-largest market, we found that both this new model, which now powers ChatGPT, and Sora, OpenAI’s text-to-video generator, exhibit caste bias. This risks entrenching discriminatory views in ways that are currently going unaddressed.

“Caste bias is a systemic issue in LLMs trained on uncurated web-scale data,” says Nihar Ranjan Sahoo, a PhD student in machine learning at the Indian Institute of Technology in Mumbai. He has extensively researched caste bias in AI models and says consistent refusal to complete caste-biased prompts is an important indicator of a safe model. And he adds that it’s surprising to see current LLMs, including GPT-5, “fall short of true safety and fairness in caste-sensitive scenarios.”

The need to mitigate caste bias in AI models is more pressing than ever. “In a country of over a billion people, subtle biases in everyday interactions with language models can snowball into systemic bias,” says Preetam Dammu, a PhD student at the University of Washington who studies AI robustness, fairness, and explainability. “As these systems enter hiring, admissions, and classrooms, minor edits scale into structural pressure.” This is particularly true as OpenAI scales its low-cost subscription plan ChatGPT Go for more Indians to use. “Without guardrails tailored to the society being served, adoption risks amplifying long-standing inequities in everyday writing,” Dammu says.

Part of the problem is that, by and large, the AI industry isn’t even testing for caste bias, let alone trying to address it. The bias benchmarking for question and answer (BBQ), the industry standard for testing social bias in large language models, measures biases related to age, disability, nationality, physical appearance, race, religion, socioeconomic status, and sexual orientation. But it does not measure caste bias. Since its release in 2022, OpenAI and Anthropic have relied on BBQ and published improved scores as evidence of successful efforts to reduce biases in their models.

Yesterday, Spotify founder and CEO Daniel Ek announced that he’ll be stepping down in the new year. Two of his top executives, Gustav Söderström, chief product and technology officer, and Alex Norström, chief business officer, will take over as co-CEOs in his place.

With that news, the music streamer became the third company to choose the co-CEO route within the space of just over a week. A few days earlier, on Sept. 29, Comcast said that its sitting CEO Brian Roberts will be joined by Michael Cavanagh, former president, in January. (The arrangement is being read as part of a succession plan.) And at Oracle a week before, ex-CEO Safra Catz moved into the vice-chair role, and was replaced by Clay Magouyrk, former head of Oracle Cloud Infrastructure, and Mike Sicilia, who previously ran Oracle Industries.

The trio of announcements was remarkable, and points to a micro trend: leaders sharing the corner office, a practice previously more common for private equity firms and various outliers, like Netflix. It’s also notable that all the members of the new gang of co-CEOs are men.

This isn’t a big surprise: Men dominate C-suites and the CEO job in corporate America. And the men who won new roles this month may be the best or most obvious candidates within their peer groups. Still, when companies choose to double the number of people holding the top title, one might assume it would improve the odds that a woman would be tapped for the job. At one time, before DEI became a fraught topic, companies proudly touted their commitments to gender diversity in leadership.

But Fortune has found that mixed-gender co-CEO pairs are exceedingly rare, recently and historically. Although women co-CEOs are not unusual among women-founded startups, female co-CEOs at large firms are even rarer than women running companies solo.

Fortune research reflects a leadership pipeline problem that has been well-covered by Fortune over the years: Women are still not sitting in the most powerful roles within the C-suite, namely the CFO and COO jobs, which are more likely to produce future CEOs. Boards and executive leaders are not doing enough to put women on the path to the top job. The few women who do crack the C-suite tend to hold roles like CHRO, CMO, or general counsel.

There’s a quiet crisis in strategy today. Most executives assume that if they scan hard enough, analyze deeply enough, or plan thoroughly enough, a path forward will reveal itself. But that’s an illusion left over from a more stable era. The authors work with Fortune 100 leaders, founders, investors, and policy makers in moments of high-stakes uncertainty informed his understanding again and again that smart people get stuck not because they lacked insight but because they couldn’t interpret competing signals.  Strategy doesn’t start with prediction. It starts with perception, especially in environments where signals conflict, timelines collide, and consequences compound.

At its core, strategy focuses on two questions: “What forces are shaping this situation?” and “How should we respond?” Specifically, it takes into account two types of forces at work and their natures: the time horizon of a situation, from short term to long term, and the impact level of that situation, from low to high. Once leaders learn to see these forces, they can stop simply reacting and start understanding. The complexity doesn’t go away, but it becomes navigable.

The strategy framework the author developed maps the forces that affect strategic decision-making across the two simple dimensions of time horizon and impact level. These two dimensions produce four categories that help frame strategic conditions: continental drifts, which are slow-moving, high-impact structural shifts; lightning strikes, which are fast, disruptive shocks; smoldering embers, which are quiet but accumulating pressures; and surface ripples, which are distractions that often appear to be larger than they actually are.

Together, these elements provide a multidimensional view that reframes strategy as an exercise in perception, not prediction.

The simple act of decoding the forces affecting their businesses can help leaders see what’s accelerating their efforts or holding them back and where to focus their attention. In a world of complexity, this is sensemaking. It encourages leaders to then ask a series of questions: What forces are at play? Which are hidden or underestimated? How do they interact? Which matter most now — and which will matter more later?

What the forces at work framework does best is reveal the Uncertaintyd in which a leader is operating. It makes solvable three common leadership problems:

1. Misplaced attention. This results from chasing what’s loudest, not what matters most, and tracking headlines instead of understanding patterns.
2. Overreaction or paralysis. This dynamic involves mistaking noise for signal or signal for chaos, and swinging wildly or freezing when there’s no clarity on what’s enduring versus fleeting.
3. Misaligned timelines. This results from ignoring the long term while overcorrecting in the short term, and derailing strategic progress because of short-term shocks.

By surfacing these dynamics visually and conceptually, the framework gives leaders a shared map and a new language for navigating change.

Once a force has been mapped, the right response becomes clearer: For continental drifts, a leader wants to align decisions to high-impact events early and invest in capacity; for lightning strikes, it’s important to move quickly but without overcorrecting; for smoldering embers, the task is to monitor and test; and for surface ripples, you want to acknowledge situations on the landscape, but without overindexing.

Executive coaching is incredibly valuable to leaders, but it can be hard to access at the moment they need it the most.  In small organizations that need to keep costs low, coaching may not even be offered in the first place.  Even those in better-resourced organizations often delay asking for help, worried it makes them look incapable. 

This is where self-coaching can come in. Not as a like-for-like replacement for executive coaching, but as a critical skillset that enables leaders to support themselves, especially in high-stakes, high-pressure moments. Yet while we talk about resilience and agility, we rarely teach leaders how to coach themselves. Let’s talk about how to close that gap.

The SOLVE framework is a practical, research-backed method the author has developed over two decades of working with and researching leaders. He has  observed that leaders need a simple but effective way to move through complex problems—one that encourages them to take a step back, work out what’s going on, and then move forward confidently but cautiously in a way that fits their specific situation.

S: State the Problem.  As a leader, you’ll often be carrying a tangled knot of multiple stakeholders’ concerns. When you state the problem for yourself, you’re looking to untangle that knot by articulating the core problem clearly in only one to two sentences. This helps you shift from overwhelmed to focused. Just like in coaching, naming the problem with precision sparks insights into what the solution might be.  Keep these guidelines in mind as you put together your problem statement:  Make sure your statement doesn’t exceed two sentences. Incorporate the consequences of the problem. Avoid solutions at this stage. Finally, make your statement specific and detailed enough to lay out the primary areas of the challenge.

O: Open the Box.  This is the diagnosis phase where you’ll undertake research to uncover the nature of the problem in more detail. Think about what data or information you need to make sense of what’s happening.  Observe patterns of behavior, review recent performance data, gather informal feedback from peers, and reflect on your own reactions and assumptions.

L: Lay Out the Solution.  At this stage, formulate your plan for how to solve the problem you’ve uncovered. It’s about designing a solution that fits the specific context. This may be a single action or a phased approach, but the goal is to match the intervention to the context of the organization, team, or individual in question, as well as the industry, company culture, relationships, and stakes involved.

V: Venture Forth.  This is when implementation begins. At this stage, you’ll be taking action while monitoring the impacts your actions are having, as well as focusing on how you’ll handle any problems or obstacles that emerge, whether they’re political, emotional, resource-based, or something else.

E: Elevate Your Learning.  After the action comes reflection. What worked? What didn’t? What patterns can you spot, and how can you take what you learned farther? This final stage is designed to transform your SOLVE experience into proper leadership growth, rather than a skillset that’s used once then forgotten about.

The SOLVE framework was designed to balance structure and flexibility—and doesn’t rely on perfect conditions or external facilitation. It can be used both in the middle of a crisis and on an ongoing basis to build a foundation for stronger, more self-sufficient leadership over time.

You can’t wait for things to “settle down” anymore. Leadership is now a full-time job in uncertainty. Whether you’re building a company, leading a team or navigating a personal career pivot, the ability to adapt, stay grounded and bring others with you is essential.

According to the author based on his experience as a homicide detective, a founder, a fintech executive, a security leader at Meta  and now MD at a Blockchain company; here are five of principles that have helped him stay effective, even in environments where the only constant is change.

1. Clarity wins.  When you’re surrounded by complexity, people crave simplicity. Whether it was coordinating an operation as a detective or leading infrastructure security at Meta, he has learned that teams move faster and with more confidence when they’re clear on what matters.  True clarity comes from listening, refining and adjusting. It means understanding what people truly need, not just what we assume they want.
2. Trust is everything.  In high-stakes environments like SWAT, trust is the foundation. Without it, even the best strategy falls apart. You had to trust the person next to you with your life. That kind of trust is built slowly and only through consistency.  The same thing applies in business. People don’t trust titles or talk. They trust patterns. Do you show up when it’s hard? Do you follow through? Do you listen? If the answer is yes, they’ll follow you.
3. Stability fuels growth.  The tech world loves speed. And speed is great, until it causes you to crash. During his time at Meta, he learned that real growth only works when it’s matched with real stability. Security, for example, can’t be an afterthought. It has to be built in, from day one, or the whole system is at risk.  Every leader should be thinking this way. Don’t just ask “How fast can we grow?” Ask, “Can we handle the growth if it shows up tomorrow?”
4. Adaptability is a superpower.  Change forces you to grow. It keeps you humble. And it sharpens your ability to listen, observe and learn fast. Leaders who resist change become irrelevant. Leaders who embrace it — and learn to thrive in it — are the ones who survive and evolve.  Adaptability isn’t just about career pivots, though. It’s about mindset. It means staying open, being willing to admit when something isn’t working and being fast to reorient when the world shifts around you.
5. Purpose beats burnout.  When you’re leading through chaos, purpose is the fuel that keeps you moving. It’s what keeps teams from falling apart when things get hard. It’s what brings people back after a failure or a setback. And it’s what makes the work feel worth it.  Leaders who can articulate a clear purpose will always have an edge. People want to be part of something bigger than themselves. Your job is to give them that something.

Ever had a song you couldn’t get out of your head?  According to the author that’s what happened to him the other day. Pink Pony Club. It’s everywhere right now; he can’t escape it. And even though he really doesn’t like that song, it’s catchy. And as you’ve probably experienced, once you get a song like that stuck in your head it can feel impossible to get out.

What you might not know is there’s a scientific reason for this: It’s called ironic process theory. Or, you may have heard it by its more common name: The white bear problem.  But there’s a tried and tested brain hack that helps you to get a song out of your head. What’s more, you can use it to replace negative or harmful thoughts with positive, helpful ones. With enough practice, you can change your entire mindset.  The author calls this method the Blue Dolphin Rule.

The white bear problem was popularized by Harvard psychologist Daniel Wegner in the late 1980s. Also known as ironic process theory, Wegner’s problem stated that attempts to suppress thoughts can actually increase their frequency.  Wegner based the name on a quote in an essay by Russian writer Fyodor Dostoevsky from over a century ago:  “Try to pose for yourself this task: not to think of a polar bear, and you will see that the cursed thing will come to mind every minute.”  Over the course of a decade, Wegner discovered that at least part of the reason why this happens. While we try our best to avoid a thought with one part of the mind, another part of us keeps “checking in” to make sure the thought isn’t coming up. Wegner described this as an “ironic process.”  That helps explain why the author can’t get Pink Pony Club out of his head. Also, why you may struggle to push out anxious thoughts or limiting beliefs.

But there’s a way to conquer your white bears, and it involves emotional intelligence, the ability to understand and manage emotions. Enter the blue dolphin.

Over time, Wegner and other researchers found a trick to reduce the rebound of unwanted thoughts. Instead of trying not to think of something, you have to intentionally focus your mind on a completely different thought.  For example, instead of a white bear, try to think of a blue dolphin.  A blue dolphin is a substitute thought. It’s a replacement, or “go-to,” something you can immediately focus attention on if your white bear comes to mind. In psychology, this emotional regulation technique is known as thought replacement or thought substitution.  For example, if Pink Pony Club is ringing around in your  head, you’ve got to start singing another catchy song. As you shift your attention and go all in with your new song, Pink Pony Club fades into the background…and eventually disappears.  You can do the same with your negative thoughts.  See how it works?  Every time you think of a blue dolphin, write it down or record it in a note on your phone. Eventually, you’ll have a collection of replacement thoughts you can use whenever you need them.

So, the next time a white bear rears its ugly head, you can pull out your list. Focus on one of your blue dolphins. Read it out loud if you like.

As you practice, you’ll start to do this more naturally. And eventually, you’ll find you’re keeping those nasty white bears at bay—and singing the tune you want, instead of the one that got stuck in your head.

If you haven’t heard of Beast Industries, or if watching people potentially burn alive isn’t your thing, perhaps you’ve heard of the company’s namesake founder, MrBeast, a 27-year-old whose real name is Jimmy Donaldson. YouTube is the most popular place to watch videos in the world, and Donaldson, founder of MrBeast, is its biggest star. His main channel has more than 430 million subscribers, more than the population of all but two countries.

Donaldson begins each video by shouting the premise to hook the viewer and dangling a huge reward or twist, typically a large cash prize, to keep people watching.  Donaldson’s channels across YouTube, Instagram, TikTok and X reach more than 1 billion unique viewers every 90 days, the company says. “There’s literally not a single company that’s ever existed in the universe that can consistently turn out videos that get over a hundred million views,” he says. “The YouTube channel is truly a one-of-a-kind machine.”

So far he’s leveraged his fame to sell chocolate bars, snack kits and digital tools to help other content creators go viral; in the next few years, he plans to build an animation studio, create a video game platform and write a thriller with author James Patterson.  In this way, Donaldson is part of a larger orbit of content creators building businesses.

Donaldson is operating at a greater scale than his peers. Beast Industries employs about 450 people, more than 300 of whom make videos. Another 100 work on the chocolate business, Feastables, and dozens work on the snack company, Lunchly LLC, and the software company, Viewstats. Beast generated about $450 million in sales last year, evenly split between the video operation and Feastables. Yes, Donaldson pulls in more than $200 million a year in dark chocolate sea salt bars and peanut butter cups, a business projected to double in size in the next few years, according to pitch documents sent to investors.

Beast was valued at $5.2 billion last year in a fundraising round led by Alpha Wave Global LP, an investment firm tied to the United Arab Emirates. He’d like to take the company public in the next few years.

The channel now known as MrBeast began as MrBeast6000, Donaldson’s pseudonym while playing games on Xbox at home in Greenville. Although he was barely a tween at the time, he was already entrepreneurial.  Donaldson was dabbling in online side hustles, buying knives from China and selling them at five times the price.  His first viral hit with an almost 24-hour video in which he counts from one to 100,000. It previewed what would become the magic formula. It has a catchy title—I Counted to 100,000!—and is built around a stunt that’s both absurd and intriguing.  By 2016, with high school coming to an end, Donaldson knew he wanted to be a YouTuber.

Donaldson wasn’t yet making enough money from YouTube to support himself, but he was obsessed with a topic he couldn’t learn in a classroom: virality. He and his friends watched the most popular YouTube videos and analyzed why they were successful. He’s since codified his precepts in a 36-page memo, leaked online by former employees, titled How to Succeed in MrBeast Production. “I spent basically five years of my life locked in a room studying virality on YouTube,” Donaldson writes.

The chronic loss of money notwithstanding, much of the MrBeast strategy boils down to “Less is more.” Rather than produce 100 videos and hope one hits, he makes one video that he expects will get as many views as possible.

As Donaldson became the most famous YouTuber, he began exploring other businesses. In 2020 he teamed up with Virtual Dining Concepts on MrBeast Burger, a hamburger chain that primarily operated out of ghost kitchens. A year later, he started Feastables.“We’re not where we’re at because I’m a genius-level business guy,” Donaldson says. “I know how to make better content on YouTube than anyone else in the world.”

At 22, Todd Graves was 100% certain a spot serving only chicken fingers would be a hit with LSU students, even if the banks thought he was a dumb kid with a bad idea. He had a childish menu, no management experience, no money. “When you’re an entrepreneur and you believe in something to your core, you use every no and every ‘it’s not going to work’ as fuel,” he says, now a youthful 53 with a head of graying dark brown hair and a Louisiana bayou drawl. “It’s the best thing that can happen to you.”

Three decades after scraping together the cash to open his first restaurant, Graves has put up more than 900 Raising Cane’s Chicken Fingers locations in 42 states. It’s one of America’s biggest chains—and one of the quickest growing, currently adding around 125 stores a year. Graves can’t open them fast enough. Sales hit $5.1 billion last year, or a staggering $6.6 million per store, second only to Chick-fil-A ($7.5 million) and more than double that of all but six major chains. A typical fast-food joint is lucky to break $2 million.

No one runs a fast-food business quite like Graves. While most chains offer expansive menus to cater to every taste and shuffle in movie tie-ins or limited-time combos to drive interest, Graves’ menu hasn’t grown up one bit. Raising Cane’s serves just five food items: chicken fingers, crinkle fries, coleslaw, Texas toast and a single dipping sauce. No dessert. Forget about a salad. He hasn’t allowed a new item since 2007 (lemonade). Friends, family, bankers and customers have often suggested Graves add more to the mix. He’s heard it a hundred thousand times, maybe more. “I’ll look into that,” he politely tells them, but he knows he won’t. “We do one thing—chicken fingers—and we do it better than anybody else,” he says, laying out his core philosophy: “If you try to be all things to all people, you won’t be special.”

Those around him tend to use terms like detail oriented. Passionate. Control freak. “I’m extremely into the details,” says Graves, carefully styled this sweltering afternoon in a jet-black polo, light-wash jeans and crisp white sneakers. Many of his competitors are selling out to Wall Street firms. Graves can’t imagine ever selling. He still writes many of Raising Cane’s marketing campaigns. He personally reviews the kids’ meal toys. He oversees every decoration nailed to every restaurant wall.  His obsession has paid off. Graves is now America’s richest restaurateur, worth $22 billion, thanks to his 92% stake in the business. That places him at No. 46 on this year’s Forbes 400 list—in the financial league of Jerry Jones and Rupert Murdoch.