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The real AI story in most organizations isnt about algorithms; its about habits. New tools arrive with impressive demonstrations and confident promises, yet the day-to-day routines that decide what gets attention, who can take a risk, and what counts as a good job tend to remain the same. Leaders set up special units, roll out training, or look for quick savings, only to find that the old culture quietly resets the terms. When that happens, early gains fade, adoption stalls, and cynicism grows. This article draws on our forthcoming book to look at three recurring myths that help prop up existing cultures and prevent the deep transformations that are needed to support successful AI implementations. Transforming a business to make the most of AI means moving past these comfortable stories and changing the conditions under which the whole organization works. Myth 1: ‘Innovation Units Will Save Us’ After five years of operation, the U.K.s Government Digital Service (GDS) seemed untouchable. Created in 2011, the GDS revolutionized Britains digital services. With the goal of reenvisioning government as a platform, it consolidated hundreds of websites into a single, easy-to-use portal, cut waste by forcing departments to unify their platforms, and showed that, with the right attitude, even government agencies could move with the speed of a startup. In 2016, the U.K.s digital services were ranked the best in the world. Yet by 2020, the GDS had disappeared as a force within the U.K. government. This pattern repeats regularly across corporate innovation labs: create an elite unit, give it special rules, celebrate early wins, watch it die. An innovation unit can deliver extraordinary results so long as it has senior leadership protection, free-flowing resources, and an internal culture that attracts exceptional talent. But the model also contains the seeds of its own demise. The outsider status that enables breakthrough innovation makes large-scale sustainability nearly impossible. When executive sponsors move on, the shield drops, and organizational antibodies start reasserting cultural norms. This predictable lifecycle applies to AI-focused teams as much as those driving any other type of technological change. Leadership transitions are inevitable. New executives question special rules. The innovation unit that draws its power from being outside the system gets pulled back in again, and the flow of novel ideas slows to a trickle. The lesson to take from this isnt that we should abandon innovation unitsits that we should use them strategically and follow up on the gains they make. Innovation units should be seen as catalysts, not permanent solutions. While these teams are forging ahead with quick wins and proving new approaches, organizations also need to transform their broader culture in parallel. The goal shouldnt be protecting the innovation unit indefinitely but aligning organizational culture with the innovative approaches it pioneers. If innovation units are sparks, culture is the oxygen. You need bothat the same timeor the flame dies. Myth 2: “Our People Just Need Training” Companies spend millions teaching employees to use AI tools, then wonder why transformation never happens. The reason is that the underlying problem isnt just about skillsits about the imagination needed to use them effectively. You can train your workforce to operate the new technology, but you cant train them to be excited about it or to care where it will take the business. That requires change at the cultural level. When it comes to AI, the real gap is conceptual, not technical. Employees need to shift from seeing AI as a better calculator to understanding the role it can play as a thought partner. This requires more than tutorials. It means showcasing how AI can transform workflows and then rewarding its creative use. Show a sales team how AI can predict client needs before calls, not just transcribe them afterward. Demonstrate how legal teams can shift from document review to strategic counseling. When organizations tell employees to use the tools but dont change the social norms around using them, people can be punished for doing exactly what leadership asked. A recent experiment with 1,026 software engineers found that when reviewers believed code was produced with AI assistance, they rated the authors competence lower by about 9% even though the work was identical. Even more concerning was that the penalty was larger for women and older engineers, groups who tended to be treated negatively in assessments already. In a companion survey of 919 engineers, many reported hesitating to use AI for fear that adoption would be read as a lack of skillillustrating why access and training dont translate into uptake when the culture signals that visible AI use will harm credibility. Myth 3: “AI Makes It Easy to Slim Down the Workforce” Theres a seductive promise being sold to companies right now. The way to realize AIs value is simply to replace as many workers as you can. Fire half your staff, pocket the savings, let machines handle the rest. Simple arithmetic for simple minds. The messy truth is that AI can and will replace many human jobs, but it wont do it cleanly and it wont do it easily. In most cases, the idea that you can simply swap out the human component and replace it with a machine just doesnt work. Humans work together as parts of multilayered social structures that have evolved as ecosystems. Its often the case that if you change one part, there will be major consequences for another. If we rush into automation too quickly, we risk pulling away the pillars that hold the whole structure up. Think about the tedious hours that junior analysts spend cleaning data, checking figures, and building models from scratch. Or the work a newly appointed manager will do overseeing performance and filling in paperwork. We call it grunt work, but its actually how humans develop the skills they will need in more senior roles. Take away the entry-level jobs and you lose the career path that delivers the highly skilled senior leaders you need. Allow AI-powered deskilling to take place and you lose the human judgment and oversight that institutions rely on. Klarnas trajectory shows both sides of this equation. In early 2024, its AI assistant handled two-thirds of customer chats, delivering resolution times under two minutes and a 25% drop in repeat inquiries. By 2025, Klarnas leadership was publicly acknowledging the limits of an AI-only approach and began reopening human roles and emphasizing the customer experience alongside automation. The real question isnt how many people you can eliminate. For effective AI implementation, you need to understand that humans make essential contributions that dont appear in their job descriptions. The Culture Transformation Playbook: Fixng the Myths Culture change depends on habits, incentives, and expectations, not just adding new tools. The playbook that follows presents concrete steps that leaders can take now to avoid the pitfalls many companies are running into. Run Parallel Transformations (Fixes Myth 1). The innovation unit delivers quick wins while a separate initiative transforms broader culture. These must happen simultaneously, not sequentially. Use the innovation units protected status and early victories to create organizational belief in change but invest equally in preparing the mainline culture for whats coming. Without parallel tracks, the innovation unit becomes an isolated island of excellence that will eventually be washed away. Transform the Middle Layer (Fixes Myth 2). Middle managers are the real gatekeepers of culture change. Stop wasting energy trying to convert skeptics. Instead, identify the curious and give them authority to experiment, budget to fail, and cover from meeting traditional metrics. Try giving selected managers a micro-charter to implement change in their team, along with a weekly show-the-work session (what AI was used, what was accepted or overruled, and why) to share what theyve learned with peers. Build Alternative Learning Paths (Fixes Myth 3). If AI eliminates the experiences that build judgment, you must consciously re-create them. High-fidelity simulations, rotation programs, and human days working without AI become existential necessities. Explicitly preserve activities that develop pattern recognition and business instinct. The investment might seem wasteful until you realize the alternative is a workforce that can operate tools but cant respond when something breaks. The Choice Culture transformation is harder than technology implementation. Its messier, slower, and impossible to fully control. Most companies will choose the easy path: buy the AI, train on the tools, create an innovation lab, and hope for the best. The few who choose the hard pathparallel transformation, cultural evolution, preserved learning experienceswill gain powerful competitive advantages. Theyll have workforces that dont just use AI but think with it, cultures that dont just tolerate change but expect it, and organizations that dont just survive disruption but drive it.
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E-Commerce
There has been a lot of chatter about A24s takeover of the Cherry Lane Theatre. What might seem a quirky side project for the independent studio known for Lady Bird, Uncut Gems, and Hereditary is in reality a sharp, shrewd move in an industry facing disruption and streaming fatigue. Live performance is one of the few cultural experiences that cant be automated, replicated, or played on demand. By stepping into theater, A24 is hedging against an AI-saturated future while also deepening its cultural footprint.When the deal was first announced in late 2023, the scuttlebutt was rooted in practicalities. Its all about creative synergies, was one refrain. Theyre diversifying their revenue streams to help offset the volatility of the film business. Theatre is more predictable than film. They can test out new stories in a low-risk environment. These were all valid comments, sure, but then a close friend and accomplished film industry executive said something that really piqued my interest. I wonder if they are further differentiating themselves in the market by building a futureproof brand. Aha! Now we were getting somewhere. [Photo: Dia Dipasupil/Getty Images] A powerful brand Coming from the branding world, I may be biased. Or perhaps just acutely aware when I sense a company doing something out of the norm. A24 certainly fits the bill. To start, the story its looking to tell, its role in the industry, and how it wishes to be perceived are markedly different from the other studios. As a result, it has a growing community of acolytes who identify with it and love it for that. These are trademarks of a powerful brand. Michelle Yeoh in Everything Everywhere All at Once, 2022. [Photo: David Bornfriend/courtesy A24] Most studios understand that their franchises are brands that they can build around, but when it comes to themselves, there is little to no attention given to an overarching narrative about what they stand for. To a branding person, this is perplexing. There is only one other industry that comes to mind that acts like this: Big Pharma. The drug companies seem to care that their patients know their drugs by name (think Lipitor, Prilosec, Viagra, Prozac) but less about how they themselves are perceived. Adam Sander in Uncut Gems, 2019. [Photo: Julieta Cervantes/courtesy A24] A24 is different. It is one of the very few in Hollywood that seems to be building a truly beloved brand. Do this simple test at home. When A24 flashes up on the screen at the start of a movie, does it mean something to you? Does it affect your perception of what is to come? Like me, do you even get warm and giddy inside? Florence Pugh in Midsommar, 2019. [Photo: Gabor Kotschy/courtesy A24] Perhaps deep down, we all understand that A24 is all about exceptional, original, creative content. The questions one might ask are: How is it going about building a world-class brand? And why does that matter? A$AP Rocky and Rose Byrne in If I Had Legs I’d Kick You, 2025. [Photo: Logan White/courtesy A24] Content is still king One simple idea prevails in our fast-evolving world: Creativity wins. And increasingly so. The adae content is king has been floated around the entertainment industry over the years. And yet, for whatever reason, it seems to get forgotten with every new business cycle. In its place, Im hearing things like, “We’re leveraging AI-driven audience analytics and predictive modeling algorithms to revolutionize content creation through real-time sentiment optimization and it’s a complete paradigm shift that democratizes storytelling via data-driven narrative matrices.” Paul Rudd and Jenna Ortega in Death of a Unicorn, 2025. [Photo: courtesy A24] Its becoming readily apparent that the general public doesnt want an AI-generated model in their Guess ads, or a machine-generated song that Nirvana could have written. Audiences want to be surprised and delighted with new, fresh, exciting content. A24s brand is synonymous with creativity, and younger movie lovers inherently understand this.The brands that matter most today are those that are daring. Anyone who has seen Ons Zone Dreamer campaign with Zendaya floating around in outer space knows what I mean. The Big Five studios are publicly traded, and so by nature forced to drive revenue for shareholders and to mitigate risk (the yin to darings yang). Ironically though, the greatest historical payoffs in Hollywood, either on a % basis or through expansion into other verticals, are those that have taken calculated risks. A24 exemplifies that spirit today, with the Cherry Lane acquisition its latest proof point. Dwayne Johnson in The Smashing Machine, 2025. [Photo: courtesy A24] Daring creativity Another key tenet to building a strong studio brand has to do with the same advice as I give to all the companies and institutions we work with: Do what the robots cant. At its core, this is a euphemism for fostering human interaction. That matters especially now. The U.S. surgeon general recently declared a loneliness epidemic. In this context, A24 isnt just buying a building, its investing in the kind of in-person experiences people are craving. Whether actively or intuitively, A24 is building an increasingly powerful brand that stands for daring creativity. Believed and beloved, it has established a cultlike following that subscribes to this world its creating, a world that gives it license to expand into any line of business that stands for the same. The Cherry Lane is a fascinating early move that insulates the company from a future saturated with AI. The question is whether others will follow suit. Will studios also see an opportunity to congregate people, perhaps by incorporating next-generation movie theater experiences into their businesses? Could they blend hospitality and entertainment through partnerships that deliver immersive venues? The door is open . . . and A24 is first through it.
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E-Commerce
With more than 30 years in digital transformation, Ive seen technology cycles come and go. And the latest wave Im seeing is AI-powered automation. It promises sweeping gains in productivity, but without ethical guardrails, it risks undermining the trust leaders depend on to grow. Thats why leaders can no longer treat ethics as an afterthought. Automation isnt just a technical upgrade. It is a human, cultural, and reputational challenge. The choices that leaders make today will determine whether automation drives sustainable progress or fuels mistrust and inequity. The promise and the peril Automation has a lot of benefits. It can free workers from repetitive tasks, improve customer service, and open new possibilities for innovation. In manufacturing, robots can boost safety by removing people from hazardous environments. When it comes to finance, AI can spot fraud faster than any analyst. And in healthcare, hospitals are using automation to speed up patient admissions (though there are privacy and consent issues). But every gain carries a shadow. Bias in algorithms can lock in discrimination. Displaced workers may find no clear pathways to re-skill. Opaque decision-making can leave customers and regulators in the dark. And what looks like a cost saving in year one can become a reputational crisis by year three. Lessons from the field Global surveys show that leaders remain uncertain about the value and risks of AI adoption. McKinsey reports that while nearly 70% of businesses have adopted at least one AI capability, fewer than one in three have embedded AI into core strategies with measurable returns. The World Economic Forums 2025 Future of Jobs report projects that by 2030, automation and other global shifts will create about 170 million jobs, while displacing around 92 million, for a net gain of 78 million roles. This makes equity, transparency, and upskilling urgent priorities for leaders. The Back on Track Foundation, a not-for-profit case study, illustrates both the potential and the pitfalls. By introducing AI tools to support case management, they improved efficiency but faced immediate questions about data privacy and oversight. Their experience is a reminder that automation is never just about efficiency. Its also about accountability, transparency, and public trust. And it doesnt just impact nonprofits. Manufacturers rolling out automated quality control or banks deploying AI in credit decisions face the same ethical crossroads. How do we balance efficiency and productivity gains with fairness, transparency, and responsibility? Why leaders cannot wait for regulation Unlike the European Union, many countries have not yet built comprehensive legal frameworks for AI. Existing laws around privacy, consumer protection, and workplace rights still apply, but theres no dedicated safety net. That means every board, CEO, and executive team needs to lead with their own ethical compass. Transparency is nonnegotiable. Customers, staff, and stakeholders deserve to know when automation is involved, what guardrails exist, and how to handle recourse if (or when) things go wrong. In my own work with clients, I use AI tools for research, analyzing reports, and preparing strategy briefs. The responsibility and decisions remain mine, but using these tools has reinforced how transparency builds trust. Leaders need to hold themselves to the same standard and be open about where and how they use automation. Equity and the human-first lens Equity is the ethical line thats most at risk. Without deliberate design, automation can deepen divides: between city and region, skilled and unskilled, and insiders and outsiders. PwC estimates that up to 30% of jobs in OECD countries are at potential risk of automation by the mid-2030s, with lower-skilled roles most exposed. A factory that automates its production line might save millions, but what happens to the workforce whose jobs disappear overnight? If you dont reinvest savings into re-skilling or transition, inequity widens. This is the human-first lens. Technology can (and should) amplify the roles of the people in the organization. What it should never do is replace their dignity or the critical and creative lens humans bring. Ethical automation aligns with company values and extends them into every workflow and algorithm. Ethical AI adoption Leaders who are looking to adopt AI in an ethical way should consider taking the following steps Audit your automation footprint. Map where automation already touches your business, who it impacts, and what risks are in play. Create governance frameworks. Decide who is accountable, how they will explain decisions, and what ethical standards apply. Invest in literacy. When it comes to training, you need to go beyond technical staff. Boards, executives, and frontline teams all need a baseline understanding of automation. Googles AI Works 2025 report found that organizations investing in AI training achieved productivity gains of up to tenfold. Measure more than ROI. Track trust, transparency, equity, and social impact alongside efficiency metrics. Be transparent. If automation influences a customer outcome or an employee process, disclose it. Trust grows in the open. Automation is inevitable. Ethical leadership is optional, but only in the short term. Regulation will eventually catch up, and those who embed human-first, transparent practices now will be far ahead of the curve. Ethical automation isnt just about managing risks. It is a competitive advantage. Organizations that lead with equity and transparency will be the ones attracting talent, investors, and customers in the years ahead.
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E-Commerce
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