Informed i’s Weekly Business Insights

For decades America’s soft power put the wind in the sails of its companies as they ventured abroad.  Peddling Americana abroad, however, is getting trickier. Last month Carlsberg, a Danish brewer that bottles Coca-Cola in its home country, noted that consumers there were boycotting the fizzy drink, opting for local alternatives instead. Coca-Cola can thank Donald Trump, who has exasperated Danes—and many others—with his talk of territorial expansion and his trade war. How worried should America Inc be about its new image problem?

Mr Trump’s damage to America’s reputation is clear to see. In a survey across 100 countries carried out last month by Nira Data, a research firm, for the Alliance of Democracies, a Danish non-profit, the share of respondents with an unfavourable view of America exceeded those with a favourable opinion by five percentage points, a sharp deterioration from previous years, and enough to place America behind China in global esteem.

The president’s actions are already weighing on American companies’ sales abroad. The backlash has been strongest in Canada, whose citizens have railed against the suggestion that their country should become America’s 51st state, and Denmark, thanks to Mr Trump’s threats to pinch Greenland. Last month 61% of Canadians told YouGov, a pollster, that they were boycotting American products.  

The souring towards American brands has been on display elsewhere in Europe, too. Tesla, Elon Musk’s carmaker, is the most prominent example: new registrations of its vehicles in Europe fell by more than 40% year on year in the first quarter. But it is not the only one at risk. In a survey conducted in March, the European Central Bank asked consumers how likely they would be to substitute away from American goods in a hypothetical scenario in which the country imposed a blanket tariff that the EU then matched, where 100 indicated a strong willingness to switch. The median answer was 80. Tellingly, Europeans were more likely to cite preference, rather than price, as their main reason for switching.

All this will worry American firms, which make more than $8trn in foreign sales each year. Not all will be equally harmed, though. Morning Consult, another pollster, has examined the correlation between consumers’ views of America and their opinion of the country’s brands. The relationship is strongest for technology companies, carmakers and food-and-beverage firms, and weakest for hospitality companies, logistics providers and health-care firms. Foreign consumers are more likely to forgo a bag of Cheetos in protest than they are a cancer treatment from Pfizer. A lack of alternatives may also make it harder for them to abandon services such as Google or Instagram. Even so, many American firms will have to grapple with the fact that their nationality may no longer be an asset—but a liability.

If you want to know where AI is headed, this year’s Google I/O has you covered. The company’s annual showcase of next-gen products, which kicked off on May 20, shows us just how fast this still experimental technology is being subsumed into a lineup designed to sell phones and subscription tiers.

The firm is bundling most of its multimodal models into its Gemini app, including the new Imagen 4 image generator and the new Veo 3 video generator. That means you can now access Google’s full range of generative models via a single chatbot. It also announced Gemini Live, a feature that lets you share your phone’s screen or your camera’s view with the chatbot and ask it about what it can see.

Those features were previously only seen in demos of Project Astra, a “universal AI assistant“ that Google DeepMind is working on. Now, Google is inching toward putting Project Astra into the hands of anyone with a smartphone.

Google is also rolling out AI Mode, an LLM-powered front end to search. This can now pull in personal information from Gmail or Google Docs to tailor searches to users. It will include Deep Search, which can break a query down into hundreds of individual searches and then summarize the results; a version of Project Mariner, Google DeepMind’s browser-using agent; and Search Live, which lets you hold up your camera and ask it what it sees.

This is the new frontier. It’s no longer about who has the most powerful models, but who can spin them into the best products. OpenAI’s ChatGPT includes many similar features to Gemini’s. But with its existing ecosystem of consumer services and billions of existing users, Google has a clear advantage. Power users wanting access to the latest versions of everything on display can now sign up for Google AI Ultra for $250 a month.  

When OpenAI released ChatGPT in late 2022, Google was caught on the back foot and was forced to jump into higher gear to catch up. With this year’s product lineup, it looks as if Google has stuck its landing.

On a preview call, CEO Sundar Pichai claimed that AI Overviews, a precursor to AI Mode that provides LLM-generated summaries of search results, had turned out to be popular with hundreds of millions of users. He speculated that many of them may not even know (or care) that they were using AI—it was just a cool new way to search. Google I/O gives a broader glimpse of that future, one where AI is invisible.

“More intelligence is available, for everyone, everywhere,” Pichai told his audience. I think we are expected to marvel. But by putting AI in everything, Google is turning AI into a technology we won’t notice and may not even bother to name.

As Saudi Arabia seeks to diversify its oil-rich economy by the end of this decade through its Vision 2030 program, fashion is one of the industries tipped to help achieve that.

The industry, which currently contributes 2.5% of the Kingdom’s GDP, is set to grow further as part of the country’s Vision 2030. Trends like Saudi Arabia’s growing population of locals and expatriates, as well as more economic opportunities for its youth, could be the fuel the fashion industry needs.   

“When you have an infrastructure that supports the creatives, and you put policies in place that really enables their growth and creates and supports their business structure that will help it grow,” H.H. Princess Noura Bint Faisal Al Saud, the founder and CEO of Culture House, a consulting firm in the creative industry, told the Fortune’s Most Powerful Women International Summit in Riyadh.  She launched Saudi Arabia’s first fashion week in 2018 and helped set up the government’s Fashion Commission. Princess Noura is also the great-granddaughter of the founder of Saudi Arabia, King Abdulaziz.   

She gave the example of how designers in Saudi Arabia can now have their commercial registration, which is a key step to setting up and operating a business there. The Kingdom’s Fashion Commission has also launched a “Saudi 100 Brands” initiative to encourage the country’s up-and-coming labels.   Big brands, such as Dolce & Gabbana and Adidas, have noticed the Saudis’ efforts to improve their appeal as a fashion destination. 

Developing an industry to ensure it grows and attracts talent can sometimes be challenging, but Princess Noura said being agile is key. “If you don’t do it, you won’t know,” she told Fortune’s Ellie Austin on Wednesday.

Fashion is one industry in which Saudi women represent a majority of the workforce—52% as of 2022, according to the State of Fashion Sector in Saudi Arabia report released by the government last year. The Princess also pointed out that men and women are paid equally in the creative world.  The Kingdom is also a big driver of the GCC’s fashion and luxury spending, representing 41% of the $80 billion market.  

Tourism, which is expected to nearly triple between 2023 and 2030, promises to be another driver as travel spending has long been boosted by overseas shopping.

Having a meaningful role in the creative industry doesn’t have to be just as a fashion designer or product development expert. “Creativity doesn’t just come from being artistic or creating something. It can also come from creating a new strategy or creating a different model, or creating a genius financial plan that would support the business to grow,” Princess Noura said.

Imagine you were a railway executive with a contract to transport valuable cargo across the country. You wouldn’t have a different engine pulling each individual car of cargo. It would be much more efficient and cost-effective to hitch as many cargo cars as possible to the same engine. In fact, you would want a standard set of trains and connectors that would allow you to pull different kinds of cargo anywhere.

This analogy is particularly germane to the world of data products. Scale and value come from treating a data product like an engine that can support a large number of high-value use cases (or cars). Unfortunately, when it comes to data products, companies are operating much more along the single engine–single car model. The result is fragmenting data programs that fail to scale or generate the value that many had expected.

In some ways, this is a glass-half-full problem. A data product delivers a high-quality, ready-to-use set of data that people across an organization can easily access and reuse for a variety of business opportunities. Since then, organizations across sectors have started to adopt data products as core elements of their data and business strategies. The wave of enthusiasm surrounding gen AI has driven a wider appreciation in the boardroom of the importance of data and the need to better harness it.

That enthusiasm, however, has produced mixed results. Confusion about how data products deliver value, governance practices that favor the individual use case over larger ROI benefits, and institutional incentives that reward building data products over scaling them all have a role in choking value. With companies increasingly relying on data—from harnessing gen AI to developing digital twins—to innovate and expand the business, ineffective or nonexistent data product practices are becoming a top strategic issue.

According to the authors’ experience working with dozens of companies in the past few years has shown that building valuable data products is much less of a technical challenge than a strategic and operational one. That experience can be boiled down to five key lessons:

1. It’s about more value, not better data. The goal of developing data products isn’t to generate better data; it’s to generate value. No data product program should begin until leadership has a firm grasp of the value that each use case can generate and prioritized the biggest opportunities.
2. Understand the economics of data products. A data product’s effectiveness is based on the “flywheel effect” of accelerating value capture and reducing costs with each additional business case that it enables.
3. Build data products that can power the flywheel effect. Harnessing the flywheel effect of ever-lowering costs and -rising value requires building a capability that maximizes reuse and reduces rework.
4. Find people who can run data products like a business. Put in place empowered data product owners (DPOs) and senior data leaders who understand what matters to the business, from articulating the value in business terms to building support.
5. Integrate gen AI into the data product program. Gen AI is already proving that it can help develop better data products faster (as much as three times faster) and cheaper than other methods.

In 2022 one of the author (Bob) was going through the onerous process of moving from one house to another when he stumbled upon an old sketch in his files. It depicted a prototype for a thumbs-up like button, made when Bob was the first employee at the review site Yelp. Today the like button can be found everywhere on the internet. It has transformed digital advertising and marketing and helped fuel the growth of the $250 billion social media industry. Most people assume it was invented by Facebook, the firm that first used it at scale. But intriguingly, the date on the sketch (May 18, 2005) preceded the adoption of the like button at Facebook by nearly four years.

People tend to think that innovations spring from farsighted individuals who change history by creating new solutions to well-defined challenges. Yet here was Bob, standing amid his household detritus with a bemused look on his face and only a distant memory of his contribution to one of the most important mechanisms of the digital realm. Could it be that Bob had, in fact, invented the like button—and that he had simply forgotten about it?

The discovery of the sketch inspired us to have a day-long conversation, then start a three-year research journey, and eventually write a book, Like: The Button That Changed the World. Alas for Bob, our research was unable to identify a single clear inventor of the thumbs-up button, but that’s part of what makes its origin story so instructive. Indeed, the button’s design, development, and deployment could be considered a miniature case study on the true nature of innovation—which is distributed, unpredictable, and often far more modest in ambition than heroic innovation narratives suggest.

Many organizations like to believe that innovation can be channeled along a pathway from concept to implementation that’s been tightly defined by smart managers. That’s a reassuring perspective because it feels empowering and calls for companies to do what they do best—allocate their resources and design and control processes. But the origins of the like button reveal that innovation tends to be serendipitous and social in nature—a melding of accidents, ideas, iterations, false starts, missed opportunities, and unexpected outcomes that cannot be willed or cajoled into existence. While not entirely new, this understanding is hard for companies to internalize. But in an era when artificial intelligence and other technological advances will upend business models, the wild story of the like button holds key lessons for managers who seek a better way to encourage and harness innovation.

The murky origin of the like button illustrates how innovation often emerges from unplanned cooperation across a distributed network of contributors. Each player implemented its own variant of the button, sometimes incorporating elements invented by the others. This story also highlights the power of clustering. In Silicon Valley the proximity of many tech startups and the culture of openness created a fertile environment for the exchange of ideas. Pioneers in the industry were keenly aware of and inspired by their competitors, sharing know-how at frequent meetups and informal discussions. And the story also suggests that sometimes innovations are simply “in the air” and ready to be discovered.

But perhaps most important, the like button’s story demonstrates the disorderly, evolutionary, and iterative nature of innovation. The various companies experimenting with it created a myriad of designs and functionalities. Far from being the result of a single “Eureka!” by an individual, it emerged from a series of small improvements made by different teams working separately yet influenced by one another’s progress.

There are several good reasons to revise the innovation practices at large companies to reflect the reality  described above.  Five ways that companies can improve their innovation models and practices.  A) Be Alert for Surprises( Measure it, Model it, Nurture it, and Reflect on it).  B) Take Things Step-by-Step (Avoid making a master plan, Conduct trail sooner, Be receptive to unintended outcomes, and persist).  C) Lay the Myth of the Solo Inventor to Rest (Recognize multiple heroes, Promote cognitive diversity, and Practice humility).  D) Calibrate Managerialism (Foster curiosity, Avoid the tyranny of averages, and Legitimize inconsistency).  And E) Shift Your Mental Model (Learn from the past, Embrace storytelling, and Model and train people in the new approaches).

Hackathons are a valuable tool for spurring innovative solutions to challenging problems, but they can fail badly. This can be particularly disheartening considering the substantial time, money, and other resources invested in preparation, organization, and execution. So, what causes them to go wrong?

According to the author he has observed 48 distinct hackathons from five different perspectives: participant, mentor, organizer, observer, and adviser. The most significant overarching problem is that organizers don’t establish well-defined goals from the start. Among hackathons I studied, only a minority had well-defined objectives, capabilities, and methodologies for assessing the event’s success, along with a concrete execution plan.  The lessons that follow can help organizers of future hackathons steer clear of common mistakes.

1. Define a challenge that meets the needs of both organizers and participants. Incorrectly prepared, unclear, uninteresting, or impossible-to-solve challenges are among the most common reasons that hackathons fail.  Challenges are the core around which everything else is later built, so they should be clearly defined before any other planning takes place. In the process, check that time constraints are realistic via a test run within the organization or by seeking advice from more experienced organizers.
2. Mentoring is poorly managed, inadequate, or absent. Participants usually need mentoring for issues that stall their progress with the challenge.  Manage the mentoring process closely to ensure that mentors have and follow good guidance on engaging with participants and that they are available as needed.
3. The hackathon has unclear or inadequate judging criteria. Participants should fully understand how their work will be evaluated at the start of the event.  Clear judging criteria communicated in the simplest possible manner are crucial for participants to embrace and understand the challenge.
4. There are too many tools in the toolbox. Many hackathons require participants to use too many disparate and unconnected tools. Those may include registration tools, various data access platforms, a separate submission repository, and diverse communication tools.  People can make mistakes, often causing them to lose hackathons despite a potentially winning project.  Larger hackathons usually require more complex solutions and are therefore harder to manage when it comes to multi-tool disease.  Simplify, simplify, simplify, and consider the time-pressured user experience.
5. Participants’ health and well-being during the event are not considered. The average participant will spend more than 30 hours (24 hours of work and some time for arrival, judging, and award ceremony) with little or no sleep.  Organizers should certainly issue a notice about participants’ responsibility for their own health. But for in-person or hybrid events, organizers should plan for quick medical care or have trained medical professionals on standby. They also should limit energy drinks and provide plenty of water and healthy foods. Some hackathons incorporate physical activities like yoga, stretching, or relaxation sessions. Increasingly, some include tasks, workshops, or seminars on maintaining health and well-being throughout the hackathon.

The key to addressing these challenges is to establish a comprehensive plan and hackathon strategy early on. Careful design, efficient management, establishment of clear objectives, and strategic planning can significantly contribute to mitigating these challenges for hosting a hackathon — and increase the likelihood that the event will yield the solutions and innovations the organizer is seeking.

The insights for this article have been drawn from the book new book is Seeing Around Corners: C-Suite Wisdom from America’s Most Insightful Leaders by Ken Banta – founder and CEO of the Vanguard Network.   An expert in leadership and change, Banta has aided numerous global turnarounds, mergers, and transformations for the likes of Pharmacia and Bausch & Lomb.

The best top leaders know they have the most to learn from people on the frontlines—in sales, making things, inventing things.  This is because these people are most in touch with current reality and with future trends. So, one great daily practice is to spend 15 minutes gaining those insights, whether by asking ChatGPT or trading emails with frontline contacts in your organization.

It can be hard to make unwritten rules explicit because people often feel they gain power and influence by keeping the rules unspoken.  One of the best ways to make negative unwritten rules explicit—and potentially shut them down—is for the most senior person in the group or organization literally to call those rules out in meetings and communications, giving specific examples (such as the conference table rule) and explaining why the rule is counterproductive.

The ability to really listen is more than a skill.  It’s a psychological state. Individuals who combine a high ego level with high insecurities will likely be very self-absorbed and poor listeners. Individuals with high levels of emotional intelligence find listening much easier.  One practice for better listening is stepping back to see yourself as others see you so you can understand what gets in the way of listening.  

Delegation, it’s been said, is the key to executive sanity. It’s also a critical ingredient in developing team members.  One way to do it is to realize that there are many ways to deliver a good result. Recognize that someone else can do the job very well—albeit differently than you would do it.  Another insight is to internalize ‘the wisdom of the crowd.’ Delegating important tasks to small teams instead of handling them yourself is not only efficient, you will gain new ways of thinking and operating that can be better than yours.”

Trust, of course, is the operating system of every good relationship and every high-performing team.  It’s vital to differentiate between assuming trust is granted, and actually earning it.  People don’t grant you trust just because of your role. You personally must behave in ways that earn their trust. You do this by acting on what they say and being consistent about things like goals and performance expectations.  Trust is eroded when a leader “blames others, becomes unavailable, and acts erratically.  By contrast, avoiding blame games, staying close to the team, and staying calm and focused in a crisis will earn you huge reservoirs of trust.

Leadership advice is everywhere, but a lot of it is wrong. The most dangerous ideas aren’t the ones that sound extreme or outdated. They’re the ones that sound reasonable. The ones that show up in offsite decks, leadership books and self-serving LinkedIn posts that feel familiar enough to accept without question.  Here are 10 leadership myths that sound great on paper but don’t hold up in practice — and the reality that’s true instead.

Myth #1: Balance is the goal.  We’re often told that great leadership means finding balance — between work and life, between vision and execution, between being present and protecting your time. But real leadership rarely plays out that cleanly.  Reality: Great leaders make sacrifices.  

Myth #2: Hire people smarter than you.  This advice sounds noble and self-aware, but without context, it can lead to confusion. Intelligence alone doesn’t guarantee alignment, trust or execution.  Reality: Hire people who complement your blind spots. 

Myth #3: Culture is everything.  A strong culture is valuable, but it’s not a substitute for results. In some cases, “great culture” becomes code for low standards or a reluctance to have hard conversations.  Reality: Culture without performance isn’t a business.  

Myth #4: Great leaders set the vision.  Vision is a vital part of leadership, but it’s often romanticized. Creating a compelling vision is easy. Following through on it is much harder.  Reality: Vision only matters when you see it through.  

Myth #5: Protect your calendar at all costs.  Time management is important, but treating your calendar as sacred can make you inaccessible to the people who rely on your leadership most.  Reality: Be available when it matters, not just when it’s convenient.  

Myth #6: Lead with empathy.  Empathy is essential in leadership. But when empathy becomes a way to avoid conflict or sugarcoat hard truths, it stops being helpful.  Reality: Lead with clarity.  

Myth #7: Confidence is key.  Confidence is often framed as a prerequisite for leadership. But too much of it — especially when it’s performative — can cause more harm than good.  Reality: Conviction matters more than confidence.  

Myth #8: Lead by example.  Leading by example is often seen as the gold standard, but it only works up to a point. Showing up early and working hard is fine, but that symbolic effort doesn’t actually scale.  Reality: Lead by design.  

Myth #9: Transparency builds trust.  Open communication is important, but oversharing in the name of transparency can create more anxiety than alignment.  Reality: Consistent communication builds trust.  

Myth #10: Leadership is about influence.  Influence is shiny and seductive. But followers, speaking engagements and press features don’t make you a leader.  Reality: Influence is a perk, but accountability is the job.  

The most persistent myths are the ones that look good from the outside. They tell us that leadership is about being inspiring, strategic, emotionally intelligent, and always available — but in reality, leadership is rarely that polished.  It’s often quiet. Sometimes uncomfortable. Occasionally isolating. And almost always full of trade-offs that don’t show up in the job description.  But when it’s done with clarity, conviction and a sense of responsibility, it works. Not because it’s perfect, but because it’s real.  Let go of the glossy version of leadership. The sooner you do, the sooner you can step into something far more sustainable and effective.

While entrepreneurs create the bulk of U.S. companies and the majority of the nation’s jobs, almost 1 in 5 new businesses fail within the first 12 months of their launch. That daunting total rises to a 50 percent rate within five years, according to government statistics. New data examines the main reasons behind recent closures and sales of some small companies, as well as the lessons their owners want to pass on to benefit other founders.

The insights come from a recent survey by Gateway Commercial Finance, an invoice factoring company, which questioned 213 small business owners who’d been forced to sell or shutter their companies. Titled ”Lessons From Failure: What Former Entrepreneurs Want You to Know,” the compendium of those responses indicates that 54 percent of respondents said they ignored warning signs their firms were in trouble for up to six months before admitting closure was a real possibility. It also suggested the official data on failures within five years is underestimated, with 67 percent of founders telling the Gateway poll they went under within five years.

Most of the principal reasons those owners wound up shutting down or selling up are well established causes of business failures. Poor cash flow led the list, followed by economic uncertainty, declining customer demand, inflation, rising labor costs, and unexpected overhead expenses.  Farther down on the list—but still a notable contributor—were the effects of tariffs from President Donald Trump’s first term, and dramatic increases in import duties after he took office again.

While slight majority of participants admitted they’d ignored red flags that their businesses were struggling for up to six months—with another 19 percent having closed their eyes for up to three—still more said they’d been late to react to those troubles. Nearly two-thirds, or 65 percent of respondents said were particularly tardy taking action to address financial problems.

Topping the list of remedial reactions former entrepreneurs said they should have taken sooner was cutting costs, and adjusting pricing or updating their business model. Others faulted not having monitored cash flow more regularly, not laying off staff when that had become necessary, and failing to apply for loans or other funding they needed.

Indeed, 62 percent of participants believed they’d still be in business if they had secured additional capital. The missed opportunities cited most frequently included securing small business loans, turning to family or friends for funds, using a business credit card, or applying for grants.

“Crowdfunding also stood out as a particular missed opportunity,” the report said. “Only 15 percent tried it, but among those who didn’t, nearly one-third (31 percent) wished they had. This suggests there’s room for greater awareness and education around nontraditional funding paths.”

But those unfortunate entrepreneurs also had advice for aspiring or newly launched business owners. Leading the list was that small company owners must acknowledge their mistakes and learn from them, followed by doing exhaustive market research before opening their doors.

Others recommendations included creating the strongest possible business plan, listening to customer feedback, focusing on cash flow, securing necessary additional funding early, spending more on marketing, having a co-founder or partner, and avoiding the threat of burnout.

What was the last word from those failed entrepreneurs in Gateway’s poll?  For just over half, it was their desire to take a second shot at launching a company. A particular motivator for those who expressed that desire was to rely on “vibecoding”—using intuition, emotion, or gut instinct to make decisions rather than data alone—as a business management tool that didn’t exist when they were bosses.

“This study reveals how often small business closures stem from preventable delays, overlooked funding options, and internal misalignment,” the conclusion notes. “But it also highlights something more powerful: resilience. The majority of former owners aren’t just reflecting on past issues. They’re rebooting, better equipped for what’s next.