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In a fracturing world, competitiveness has risen to the top of the agenda. Yet the debate is often muddled. The concept itself is poorly defined—the World Bank’s competitiveness framework, for instance, identifies 1,200 contributing factors, and most economists prefer to focus on productivity, which avoids the fallacy of zero-sum thinking while highlighting what really drives prosperity.  As global competition for investment, industrial capacity, and technology leadership intensifies, however, productive investment offers a practical way through: It serves as both a proxy for competitiveness and a gauge of productivity growth, warranting a central role in the debate.

Companies invest where they expect to be most successful, and when they feel confident that the framework conditions are in place to make an investment both possible and worthwhile. That makes investment a good measure of a country’s current competitiveness. The proof of the pudding is in the eating, as the saying goes, and proof of a country’s competitiveness is its ability to unlock domestic and attract global investment.

Investment also bolsters a country’s productivity, prosperity, and future competitiveness—as well as its resilience against geopolitical shocks—by expanding its production and innovation capacity. Previous MGI research has found, for example, that tangible investments, like infrastructure and machinery, and intangible investments, like R&D and software, together account for up to 80 percent of productivity growth.  Economies with more productive capital per worker tend to be more productive because better equipment, systems, and technologies enable workers to create more value with their labor. Higher output in turn enables more investment to build and renew the productive capital base, creating a virtuous cycle.

Advanced economies have long benefited from this virtuous cycle of rising investment and economic growth that supported their competitiveness. Over the past two decades, however, their investment engine has stalled. The slowdown is most pronounced in Europe, Japan, and South Korea, but, outside the AI-related investment boom, also is clearly visible in the United States.

Recent geopolitical tensions have brought into sharp relief the lack of investment in industries that are now seen as strategic. This includes, for instance, energy infrastructure, semiconductor manufacturing, and, in Europe’s case, also defense industries, digital industries, and AI technology.  Rising costs of capital and shifts from asset-light to asset-heavy business models add challenges, while the technological breakthroughs also create opportunities for a new investment revival.

The shifting investment patterns around the world are changing the global cartography of growth and competitiveness. Layer on global geopolitical shifts, and the need to establish a new balance comes into focus. To understand why investments are being made so readily in some countries and industries and less readily in others, we need take a deep dive.

The bottom-up case for investment.  What drives the divergence in investment trajectories, and what could be done to establish a new balance? Many macroeconomic factors underpin differing investment patterns across regions, including structural trends like the rapid growth of China’s urban middle class, aging populations in East Asia and Europe, varied monetary and fiscal responses to the 2008 financial crisis and the 2009-10 eurozone debt crisis, and the impact of the tech industry in the United States.  A range of factors influence investment decisions. Many strategic considerations come into play, including which markets and technologies to expand into or enter, what types and levels of risk are acceptable, where projects proceed quickly and efficiently, and what is needed to build resilience. Industrial policy also impacts investment, encouraging investments in some technologies and steps of the value chain that support nascent industries and to bolster strategic autonomy or avoiding or creating chokeholds, among other considerations. At bottom, a positive business case is a prerequisite for large-scale investments. Typically, a company will require that expected net present value, or the risk-adjusted value of a project’s expected cash flow, is positive and better than other options to proceed with any investment.

The decisions vary by type of industry. “Anchored” industries providing goods or services that aren’t traded on global markets need to decide whether local market structures and prices are attractive relative to the cost of, say, building energy substations or laying fiber optic cables. “Footloose” industries that trade their products far and wide will choose where it is most cost-effective and profitable to make an investment relative to other geographies. To companies in industries that feature rapid innovation and an escalatory investment race to the top—industries the authors’ call new “arenas” of competition—being able to move fast and to find partners and investors in local ecosystems matters most.

In almost all industries, countries in the sample with lower levelized costs have the highest investment intensity compared to their GDP, while countries with higher levelized costs invest less.  To be sure, the many exceptions to this general rule highlight the importance of other factors that have a role in investment decisions. Markets and ecosystems, as well as fast permitting and building, explain why Singapore builds more AI data centers than its high energy prices would suggest, while Sweden builds less than it could, given its competitive energy costs. Similarly, Germany remains the biggest investor automotive R&D compared to its GDP, despite China’s significant cost advantage. AI data centers and EV platforms are examples of arenas in which ecosystems and speed matter most. Economic geography research suggests that it is extremely hard to manufacture new ecosystems59—but as the example of Shenzhen, China, shows, even complex ecosystems can be recreated if the fundamental economics warrant it.

Industrial policies including subsidies and regulations enable Germany to build more solar energy, the United Arab Emirates to build more nuclear plants, and China to build more polyethylene crackers than their relative cost position would suggest. Nevertheless, business cases clearly are critical for the long-term viability of an industry as well as for the amount of taxpayer money needed to close gaps with industrial policy where that is intended.

What it would take to rebuild competitiveness.  In the past, different endowments allowed different economies to be more competitive: cheap labor here, cheap energy there, innovation strength or deep capital markets with low financing costs elsewhere. Today, some countries—China chief among them—have unusually large advantages across an unusually broad set of production factors, resulting in a lead in almost all the investment cases we studied. This shrinks the space for specialization in other large economies and means that narrowly targeted responses will be insufficient to overcome the large cost differences. Nevertheless, what could be some of the possible pathways to restore competitiveness?

Europe was successful in the industrial age, thanks to high degrees of automation that compensated for higher labor costs, quality leadership in manufacturing, and competitive energy costs, but those advantages are eroding. The United States long accepted large imbalances in manufacturing, instead focusing on technology and services in which it leads globally, although it is now working to address import dependencies. For its part, China has arguably been too successful in manufacturing industries and now struggles with excess capacity, low capital returns, internal and external imbalances, and a need to sustain growth through domestic demand.  All regions will have to step up to achieve their stated goals.

Even heroic assumptions about achieving investment goals could not translate to sufficient change to fully close the gap, however. To escape pure cost competition, companies and policymakers could work by regaining innovation leadership and specializing in differentiated goods and services that play to a country’s strengths or can sustain premium pricing that offsets higher costs.  

Where the gap remains too wide to achieve a country’s aims, macro-level interventions could level the playing field. Such intervention could include reducing exchange rate distortions, using selective trade policy, deploying industrial policy, and renegotiating any policies that currently tilt the global balance in investment.

Until competitiveness is restored, navigating today’s unlevel playing field will require companies to think through tough trade-offs between investing where costs of production are low, ensuring supply chain resilience, and achieving longer-term competitive goals. Understanding the lessons offered by the lowest cost and best-in-class locations today can raise competitiveness everywhere.  The alternative option to deal with differences in competitiveness and levelized cost is, of course, to simply accept them, along with the trade deficits—and surpluses—that come with them.

Countries seeking to catch up with global investment leaders can push or pull seven levers.  Restoring balance to investment around the globe requires more than simply addressing cost differences. Companies and countries can deploy seven levers to level the playing field, though the mix of levers will vary across regions depending on the domestic context and geopolitical priorities.  Capital expenditures: Release the brakes and industrialize construction.  Labor: Push the productivity frontier and lead on AI deployment.  Energy: Secure abundant, competitive, clean energy and locate heavy industry near energy sources.  Time to market: Step on the accelerator and remove regulatory complexity.  Innovate and differentiate to avoid competing on costs alone.  Specialize in less cost-sensitive, more critical industries: future-shaping arenas and critical chokepoints. And level the playing field with industrial policy.

Anthropic—currently the world’s most valuable AI company, with a nearly $1 trillion valuation—has a reputation for publishing strange and heady research. It’s looking into whether AI models can feel pain, for example, and will sometimes cut off chatbot conversations if it suspects users are “abusing” the model. 

One niche that Anthropic spends more time and money on than other AI companies is called mechanistic interpretability, which means looking inside the complex math of an AI model to learn why it comes up with one particular output and not another. It’s complicated stuff; there are millions of data points that might contribute to any result, and wading through them can look more like word salad than anything useful. It’s also controversial. Describing AI models with terms borrowed from psychology and neuroscience can make their behavior seem more sophisticated than we might otherwise judge it to be.

That’s why, when Anthropic announced last week that it had found a new window into its models’ “internal thoughts” as they reason through answers, there was one colleague the author had to talk to. Senior editor Will Douglas Heaven, aside from having a PhD in computer science, has spent a lot of time digging into what we can say about how AI models work. The author spoke with him about what we should take from Anthropic’s new (and predictably quirky) research.

Anthropic has been trying to understand how large language models (LLMs) work for a few years now. Anthropic isn’t the only one looking at this.  What Anthropic learned was that LLMs have a space inside them—which Anthropic calls the J-space—filled with words that don’t appear in their output but that seem to influence the way they puzzle through problems. 

Sometimes these words keep track of where the LLM has got to in a particular task, sometimes they look more like flashes of recognition (for example, “protein” might pop up when you give an LLM only the letters of a protein sequence), and sometimes they represent a kind of internal commentary on the model’s decision-making.  Anthropic also found that LLMs are able to describe and manipulate the words in this space. So somehow they seem to be making use of it. 

Anthropic compares this new space it found inside LLMs to the space that some neuroscientists think our brains use to keep track of conscious thoughts. The author asked the company how seriously we should take that comparison and it said in a statement: “Drawing these analogies was helpful to us in designing our experiments, as they allowed us to make many non-obvious experimental predictions about the J-space that turned out to be true. At the same time, it’s important to note that there are some important differences between the J-space (and language models in general) and the human brain, so we don’t mean to claim there’s a perfect correspondence.” 

Anthropic has said that monitoring the J-space could be a way to catch models doing something they shouldn’t. Because words pop up in this space that don’t appear in a model’s output, they can tell you things about its behavior that you might not have noticed otherwise—such as when it is giving biased responses or when it is weighing the pros and cons of cheating.

Immersion is redefining the consumer experience.  Immersion is being propelled by two converging forces. The first is the rise of the attention economy, in which brands compete for consumers’ sustained engagement. Full immersion is the most compelling attention strategy available. The second is the shift of consumer spending toward experiences over the past three decades, giving businesses a strong incentive to turn memorable moments into products. Those trends are likely to pick up steam as immersive technologies—advanced virtual reality headsets, spatial computing, and AI-enabled interactive characters (from holograms to robots)—move from novelties to mainstream offerings.

Too often, however, “immersive” is a marketing hook equated with elaborate theming rather than absorption. While organizations may be tempted to simply dazzle consumers with technology, the important question is whether an experience draws people in, keeps their attention from start to finish, and culminates with a coherent sense of what it all meant.

What separates the experiences that captivate from those that disappoint isn’t how impressive they look—it’s whether they’re grounded in an understanding of the psychology of immersion.

That psychology follows a structured progression. As people enter a new experience, they seek answers, consciously or unconsciously, to six questions: Where am I? Who am I with? What can I do? What is happening? Am I making progress? and Why does this matter? Each question reflects a distinct psychological dimension. Together they create the underlying structure through which immersion takes hold.

For companies, addressing all six questions can be challenging. Most experiences tend to focus on answering certain questions while overlooking others. True success lies in ensuring visitors can answer all six in order, even if some are addressed more effectively than others. Of course, companies will inevitably face trade-offs. 

Many things in business can be evaluated using the framework outlined here, whether they’re customer journeys, service interactions, workplace events, or moments of organizational change. When people enter any situation, they orient themselves, interpret how they relate to others, test whether their actions have consequences, seek to understand how events unfold over time, look for evidence of progress, and ultimately reflect on what the experience meant to them.

Designing with these six dimensions in mind can improve experiences regardless of their scale, technology, or setting. What matters is whether human psychology is treated as an explicit input rather than as an afterthought.

What does artificial intelligence do to creativity? Are generative AI tools making us more creative, or less? Given that creativity is often the engine behind the most successful ideas and ventures, and that 83% of senior executives rank innovation among their top three priorities, understanding how using AI affects human creativity is critical for businesses.1 On the one hand, generative AI can act as a valuable brainstorming partner, enabling inventors and designers to rapidly prototype ideas and concepts. On the other hand, it risks inadvertently constraining creativity by narrowing the search space too early and encouraging users to anchor on AI-generated suggestions that seem “good enough.”

The authors’ research reveals that the truth lies beyond this simple binary. It was found that although AI can enhance individual creativity, it reduces collective creativity.  

By casting a wider net, organizations can guard against premature convergence on safe, conventional options, increasing the odds of surprising, high-impact breakthroughs. This, however, is where our research reveals an interesting paradox. Individually, AI often enhances creativity, particularly by enabling less experienced or less inherently creative individuals to generate more novel and useful ideas. But collectively, AI often “compresses” the idea space. Because many people anchor on similar AI-generated suggestions, outputs converge. A typical output produced with AI assistance is more creative, but the variance of the full set of outputs decreases. In short, even if an AI-inspired idea looks good, it may turn out to be similar to everyone else’s AI-inspired ideas.  For managers, the implication is profound. The challenge is to harness AI’s productivity and quality benefits while preserving the diversity of ideas that fuels long-term innovation.

How to Use AI in Creative Workflows (Without Sacrificing Diversity).  The evidence across studies points to one conclusion: How you use AI in creative work matters as much as whether you use it at all. Leaders who seek the efficiency gains of AI while preserving or enhancing originality must intentionally design their workflows. Here are some practical strategies you can use:  keep humans in the driver’s seat for ideation, diversify AI inputs, deploy multi-agent and multimodel approaches, and build guardrails and mindful friction to protect human comparative advantage.

Leaders have developed their own stealthy tests to spot high-potential employees ready to move up the next rung of the ladder. Chipotle’s chief operating officer, Jason Kidd, scouts the next cohort of leaders by breaking bread with his staffers. 

Every week, Kidd rounds up three to four members of the regional market in the town he’s visiting. During the 90-minute meals, the Chipotle exec not only bonds with the staff and strengthens the stores’ routine operations but also uses the time to scout promotions within the company. The COO typically visits around a dozen stores weekly, in various locations—giving a wide swath of employees a shot at making an impression. 

“We’re constantly identifying internal talent during these visits, seeing how people show up and see how they react,” Kidd recently told Business Insider.

In 2025 alone, the $46 billion fast-casual chain promoted 23,000 of its employees. And it’s a considerable segment of Chipotle’s workforce, which spanned more than 135,000 people across 4,100 global locations at the end of March. The food giant told Fortune that 100% of its regional vice presidents, 85% of general managers, and 83% of field leaders were promoted internally last year. And Kidd’s dinner-table test is one way Chipotle is tracking down who deserves a senior title. 

The weekly dinners allow him to “get to know people in a different way,” the executive explained, and suss out who is actually interested in growing their careers. And while Kidd is dining with his staffers, he’s keeping an eye out for four key traits that signal they’re a surefire promotion. 

First and foremost, the COO wants to promote team players. Those who work well alongside others and support their peers have the potential for a promotion.  The serial restaurant executive—who also held a leadership role at Taco Bell—is also looking for workers who “own the outcome.” Shying away from responsibility is a red flag; Kidd wants to hear honest assessments of how things are going, whether good or bad. The third trait he’s looking to tick off is the skill of anticipating problems to come. Having that foresight, instead of just confronting issues in the moment, is paramount to earning a higher title and pay.   Lastly, Kidd is on the hunt for talent with problem-solving skills. He wants to promote employees who can not only recognize a problem but also come prepared with solutions for how to move forward. 

Many workers put in the hours, trusting that their hard work will speak for itself and propel them up the career ladder. But as promotions have slowed, employees are going the extra mile—and employers have developed their own tests to pick the best from the bunch.  To have a shot at landing a promotion, workers are eager to get in on the secret formula. And some employers are opening up their playbooks. 

Earlier this year, Accenture told its associate directors and senior managers that they need to consistently use its AI tools in order to be considered for high-level promotions. The consulting giant began monitoring the weekly AI tools log-ins of some of its senior workers, and in the end, only those who boast “regular adoption” of the tech are considered for leadership positions.

Other leaders, like Cisco CEO Chuck Robbins, have more people-focused philosophies on who to move up. The leader of the $470 billion tech company doesn’t follow the routine interview process; instead, he seeks approval from his team to move them up the chain of command. If he runs the idea by the peers of a prospective promotion and they’re unhappy or perplexed, it’s a bad sign. 

“I think when we have two or three internal candidates for a promotion, the whole interview process is stupid to me,” Robbins said on the TBPN podcast earlier this year. “We’ve been watching these people work for a decade. What are we going to learn about them when we sit down in a room for 30 minutes and ask them questions when we can watch them work?”

Right around that mid-career point—now usually during people’s 40s or 50s—professionals often find themselves pulled in multiple directions. They may have to care for both aging parents and young children, juggling doctors’ appointments and after-school sports with increasingly demanding careers. Having done their jobs for a couple of decades, they’re high enough on the corporate ladder to be managing teams and carrying extra weight. In the past, this time used to signal that the joy and relaxation of retirement awaited on the horizon.

But now, with life expectancies increasing (and financial pressures along with them), these extra-stressed professionals sit firmly mid-career—looking at decades more of work ahead.

“We know from happiness data that these can be some of the most unhappy decades,” says Lynda Gratton, a London Business School professor focusing on the future of work. In her research, she’s learned how workers in this age group experienced the pressure. They were stalling their careers, reporting the lowest levels of “calm,” and realizing that decisions they’d made early on in their work lives, such as what types of positions they were striving toward and the industries they’d entered, were still influencing their everyday routines—even though it felt like those decisions had been made by entirely different people. The problem was that these workers were so busy, they didn’t have time to reflect on how to change course.

“What I began to see, particularly for people in their mid-40s and early 50s, was just absolute burnout,” Gratton says. “People feel as if they’ve been in a race. They’ve got to where they want to be, are running out of steam . . . and yet realizing there’s another race ahead of them, [which] they hadn’t anticipated.” 

Here’s what the midway mark of that race looks like for working professionals, and how some have found a way past it.

Working as the meat of the “sandwich”.  Today, mid-career professionals are part of the “sandwich generation,” who are having kids later while their own parents live longer. Constantly moving between home and work responsibilities, says Gratton, carries a “cost.”  Each time the brain switches from one task to another, it must recalibrate, which requires a significant mental lift. That can leave mid-career caregivers exhausted and stressed—not to mention feeling guilty.  That guilt intensifies as the boundary between work and home blurs. That boundary started fading with smartphones, as workers became constantly reachable, but it also increased with the COVID-19 pandemic, as more people began working from home. The guilt manifested,

Many mid-career professionals also derive identity and purpose from their jobs. The thought of no longer being in the right place can take a serious toll on one’s mental health. Increased workloads, however, eclipse time for reflection.  And if you need to provide for three generations of family, you can’t jump off—even if it no longer aligns with your “purpose.”

Recalibrating for a shifting purpose.  “We get into midlife, and purpose shifts suddenly,” says Davies, who now works as a corporate coach for midlife leaders.   “Suddenly we’re 50, and we’re thinking, ‘Okay, wait, there’s somebody else who made this decision to do this career for me, and they were much less mature than I am,’” says psychologist Samantha Stein. Even if early career choices feel right later, she adds, “we get to a point where we’re not challenged in the same way to keep growing . . . because we’re just good at what we do.” That, too, can lead to burnout. Instead of mastering something and then passing that earned wisdom along to younger colleagues before retiring, workers are left treading water in that mastery phase for years, exhausted by the boredom that comes from not being meaningfully challenged—unless they decide to make a big change.  Gratton calls this time the “pivotal point,” when workers need to figure out how to make the next couple decades of their careers sustainable. It no longer makes sense to have just one period of education to get us through all 50-plus years of work.   “You have to retrain, reskill,” she says. “You’ve got to be prepared in a long life to go back to being a child again,” allowing for experimentation, potential failure but, ultimately, growth.  Of course, starting from scratch in a brand-new career isn’t for everyone.

“What do you disrupt for a living?” asks the minky-lashed venture capitalist turned philanthropist, at the Cartway Foundation’s annual benefit. You work in drug discovery, synthetic biology, quantum computing or some other field that took you years to understand, then master, then reimagine. You’re proud of your work. You absolutely need people like this woman and her checkbook to understand it’s important. Halfway through your carefully honed elevator pitch, the evening’s most solvent guest swipes past you mid-sentence. She calls out to a latecomer, “Did all five survive?” You’re left adjusting a cufflink, wondering what you could have done to corner her curiosity. The answer lies in 10 science-backed principles from a storyteller’s toolbox.

Work backward from your mission.  Edgar Allan Poe said every serious plot must have its end worked out before the writing begins.   This can be especially helpful for stories about real-life complex initiatives, because your ending is simple to identify. It’s your North Star. Your ultimate goal. Not your carefully curated, public-facing mission statement, but your actual, unvarnished purpose. The future your work is trying to create.  It’s a picture of a concrete outcome derived expressly from your work. It emerges from specific activities and KPIs, so that the ending feels earned—and even inevitable—should it be realized.  

Let your audience make a prediction.  Now that you’ve aligned your story’s ending with your mission, go back to the beginning. In filmmaking, the beginning’s called the “before snapshot” or the “ordinary world”—the world as it exists before anything changes. For a complex project, it’s a snapshot of exactly what your work is trying to change. It’s the direction the world is heading without your intervention.  Let them form a prediction before you reveal what your work has uncovered and where it may actually lead. This is where the complexity of your work becomes a serious advantage. Hidden inside it are mechanisms, relationships and consequences the audience couldn’t have anticipated. Properly explained, they can overturn the audience’s first prediction without making the reveal feel arbitrary. 

Find your central characters.  Every story needs someone—or something—that the audience can track, relate to or vilify. Rather than simply diffusing information, character roots that information in embodied experience. It gives the audience a portal into the story. Where they can live the story.  Look for the character at the center of the causal chain—the one whose actions or transformations change what happens next, or who has something to gain, lose, resist or overcome.

Find the story’s spine before you try to make it interesting.  An undertaking of any significance is never just one story. It’s a thicket of discoveries, mechanisms, institutions, barriers, histories and ambitions. Your work may scream for explanatory simplification. But before simplification comes selection. Once you’ve decided where you want your story to end, work backward, selecting only the information audiences need to reach that conclusion. Look for obstacles you have overcome or are still working to overcome. Look for the setbacks, failures and mistakes that exposed what wasn’t working—the unforeseen discoveries, turning points and breakthroughs that forced you to think creatively and pursue new directions. None of this could have been plotted in advance, no matter how talented the storyteller. Reality provides far more interesting fodder. When an idea is stress-tested against the world, it produces reversals, surprises, consequences that become rich story beats. These selections—these beats—are the vertebrae to your story’s spine. They’re your story arc.

Find the hook with curiosity.  The hook is the big idea that grabs the audience’s attention and makes them want more. It’s the most important part of the story because, if it fails, nothing that follows will be heard.  With modern storytelling, the hook is first introduced through packaging. In journalism, packaging is the headline and hero image. In book publishing, it’s the title and jacket. In film and television, it’s the title and key art. Across social media, it’s the title and thumbnail. Your audience chooses in seconds whether or not to opt in based on the promise the packaging makes. Once they click, your story must immediately confirm the promise. Don’t start with background. Start in the middle of the action. Start with the anomaly, the contradiction, the decision, the result that shouldn’t exist, the question nobody can yet answer. Lead with what’s happening and why it matters while supplying just enough context to ensure clarity and credibility. The audience must immediately recognize that they’re getting the high-quality story that the packaging promised. Importantly, the hook isn’t the reveal. If the hook reveals too much, there’s no reason to stay for the story. The hook is what makes the reveal worth waiting for.

The other five are:  After you hook your audience, keep them; Turn technical details into consequences; Challenge the belief without threatening the believer; Don’t make people decode the language and the idea at the same time; and Don’t rely too heavily on AI.

Leaders are often really good at looking out in the world around them to find inspiration for their next breakthrough. They scan the market for pain points, potential customers, partnerships, new products and funding opportunities. But inside large, mature organizations, some of the most powerful innovations often start with a founder’s mindset inside the organization.

Internal innovators, often called intrapreneurs, are closest to the work, the friction and the customer experience. When leaders recognize and empower them, those individuals can drive innovation, speed and competitive advantage that competitors struggle to replicate. 5 ways leaders can identify and empower intrapreneurs inside their organizations.

1. Spot the hidden intrapreneurs.  Intrapreneurs are usually the people doing the work who see how things could be better.  These individuals tend to share several traits. First, they are knowledgeable about a specific area of the business. Second, they show genuine passion for improving it. And third, they are credible enough that others believe they can pull their ideas off.  Routine check-ins make a difference. Ask questions like: How is the work going? What are you seeing that we might be missing? What would you change if you could? Sometimes the next breakthrough is sitting quietly inside the organization, waiting for someone to ask.
2. Create psychological safety for innovation.  Innovation struggles in environments where people are afraid to speak up.  Many organizations say they want innovation, but their culture unintentionally suppresses it. One common reason is leadership insecurity. If leaders feel threatened when challenged on their ideas or processes, employees quickly learn that raising new ideas can create problems instead of opportunities.  Culture can also contribute. When specific results become the only metric that matters, experimentation feels risky. If every unsuccessful attempt is condemned as a failure, employees stop proposing new approaches. Leaders must demonstrate that thoughtful experimentation is valued.  When leaders consistently show openness and transparency, innovation becomes part of the culture rather than something employees avoid.
3. Give intrapreneurs room to move.  Intrapreneurs need autonomy to pursue ideas, but that freedom must exist within clear priorities.  Startups often benefit when employees can contribute across multiple areas. People frequently wear several hats as organizations grow. The key is balancing experimentation with accountability.  Leaders can support this by creating pilot projects, protecting time for experimentation and setting clear expectations around priorities.
4. Equip them with a founder mindset.  One powerful question leaders can ask a team member is simple: What would you do if you were the founder? That question changes perspective. Instead of focusing only on tasks, people begin thinking about outcomes and tradeoffs.  Sometimes this reveals solutions that were hiding in plain sight. Other times, it surfaces obstacles that must be addressed. Either way, it encourages employees to think more like owners. 
5. Turn internal wins into competitive advantage.  When an intrapreneur proves an idea works, leadership must help scale it without crushing the energy that created it. That usually requires restructuring priorities so the innovator has time and resources to keep building. Leaders should also communicate clearly with the team so everyone understands shifting responsibilities.