The Invisible Insight: When Value Hides in Plain Sight
"I think we're missing the point. Our difference isn't that we have the largest cinema screens. It's that we help people feel small."
The conference call fell silent. For weeks, I’d been analyzing market trends, conducting stakeholder interviews, and mapping competitive landscapes for this iconic cinema experience company. I’d generated dozens of artful slides displaying unmet needs against brand strengths, social media sentiment, and demographic shifts. The data was comprehensive, well-organized, and—as suddenly became evident—almost entirely irrelevant.
In this case, the person who spoke those words was the CMO, but he was also a seasoned strategist who had spent two decades immersed in moviegoers' emotional landscapes. In a single sentence, he reframed the entire challenge: What if the company's true value wasn’t a technical specification or a service feature, but rather creating a profound psychological state that people could not experience outside of a cathedral or an epic natural wonder?
Within minutes, the energy had shifted completely. The conversation shifted from defensive positioning against streaming services to creating genuine moments of awe that entertainment systems in living rooms, no matter how technologically advanced, couldn’t replicate. It wasn't about pixel density or sound quality. It was about feeling small in the presence of something magnificent.
The revelation wasn't a data-driven insight. No sentiment analysis identified "feeling small" as a key benefit. No competitive audit identified "creating awe" as a market opportunity. It arose from something more mysterious and powerful—a pattern recognition capability developed over decades of observing how humans interact with experiences, stories, and spaces.
The Algorithmic Paradox: When Machines Climb the Wrong Mountains
Just days before that meeting, a Silicon Valley prophet had made headlines by declaring that "AI will handle 95% of marketing work" in the near future. His prediction shook agencies and marketing departments around the world, not because it was particularly novel—technology has been "disrupting" marketing for decades—but because, for the first time, it appeared completely plausible.
Today's AI systems can analyze consumer data at speeds and scales unimaginable to humans, detecting hidden patterns and generating creative variations with incredible efficiency. They can write persuasive copy, create visuals, glean insights from consumer conversations, and optimize messaging across channels for a fraction of the cost of traditional methods.
The economic argument appears simple: if algorithms can produce comparable results at significantly lower costs, why keep costly marketing departments? One Silicon Valley investor bluntly stated, "AI will guarantee the replacement of creative agencies within five years."
However, this calculation reflects a fundamental misunderstanding of customer value creation. Consider what happened during the cinema strategy session I talked about earlier. The breakthrough didn’t come from analyzing existing data more efficiently but in reimagining what information actually mattered. This case illustrates a pattern I have seen in brand strategy over the last three decades: the most valuable insights come from reimagining what we need to know rather than processing what we already know.
This is the intelligence paradox: as AI improves exponentially at climbing strategic mountains, human wisdom becomes increasingly valuable in deciding which mountains to climb in the first place.
The Three Metamorphoses: From Following Recipes to Inventing Cuisines
The difference between machine intelligence and human insight isn't merely philosophical—it reflects a fundamental transformation in how insight happens.
To understand this transformation, consider how a chef's relationship with recipes changes throughout their career.
A culinary student follows recipes with meticulous precision, measuring ingredients exactly and timing processes carefully. Deviation from the recipe typically leads to failure. The novice brand strategist operates similarly, rigorously applying frameworks learned in education—positioning templates, consumer journey maps, and creative briefs—as if they were reliable recipes for strategic success.
The mid-career chef begins breaking from recipes, understanding when to substitute ingredients or modify techniques based on context. They know when a dish needs more acid or when to adjust cooking time for different equipment. Similarly, the experienced strategist adapts frameworks to specific situations, combining different methodologies and modifying "best practices" based on industry context or brand maturity.
But the master chef eventually transcends recipes entirely. They create dishes based solely on intuition, using ingredient combinations and techniques not found in any cookbook. They're not just modifying existing recipes but creating new cuisines. The master strategist operates at a similar level, having so deeply internalized the underlying principles or brand strategy that they sense possibilities invisible to others, developing solutions uniquely tailored to each challenge.
Japanese martial arts traditions call these three stages of learning shu-ha-ri: first following rules faithfully (shu), then breaking from tradition (ha), and finally transcending formal structure altogether (ri). What makes this framework so revelatory for any AI doomsday discussion is how it illuminates the evolving relationship between algorithms and human expertise.
Current AI systems excel at the shu stage—they can follow established frameworks with extraordinary precision. They're rapidly developing capabilities in the ha stage—adapting approaches to specific contexts and suggesting variations. But they remain fundamentally limited in the ri stage—the domain of intuitive wisdom where entirely new patterns emerge from accumulated experience.
The Meijin Mind: Seeing Through Noise to Feint Patterns That Don't Quite Exist (Yet)
In Japanese traditions, someone who reaches this transcendent level of mastery is called a Meijin (名人)—a term that denotes someone whose expertise has evolved into something approaching artistry.
The Meijin doesn't just know more than others; they know differently. Their perception has transformed so completely that they experience their domain in ways beginners cannot imagine.
What makes the meijin mind so valuable is not raw processing power—computers outperformed humans on that front decades ago—but a mysterious ability that only emerges after thousands of hours of immersion: second-order pattern recognition. While algorithms are effective at identifying existing patterns, the meijin can sense patterns in how patterns evolve, detecting possibilities that have not yet manifested.
Think about how Netflix went from delivering DVDs to a streaming service to a studio that makes its own content. This evolution wasn’t just about better analyzing existing data; it also meant predicting future patterns before they happened and thinking of business opportunities that didn’t fit into current categories. When Nike shifted from performance marketing to social justice with Colin Kaepernick, the pivot wasn't driven by marketing metrics but by cultural intuition—sensing a shift in collective values before it fully crystallized.
This ability to "see around corners" is not magical; it is caused by something cognitive scientists call "chunking," which is when the brain starts to recognize complex patterns of meaning instead of processing single data points. That is how chess grandmasters can understand right away the strategic implications that would take beginners minutes to think about. By spending decades immersed in brand-culture relationships, the strategic meijin creates neural networks that alter people's perceptions.
The Metaskill: Learning to Work at the Edge of Knowing
If the most valuable strategic thinking happens in this transcendent state, how does one develop it? The path from technical competence to intuitive mastery isn't automatic—many strategists with decades of experience remain firmly in framework adaptation rather than transcending frameworks entirely.
The evolution toward meijin-level perception involves cultivating specific metaskills—ways of learning that transform how we relate to knowledge itself:
The most effective method is to intentionally cross-pollinate, which means getting involved in areas that don’t seem to have anything to do with your professional focus. One remarkable strategist I know reads poetry and writes music, finding that the metaphorical thinking it requires creates neural pathways that illuminate brand challenges in unexpected ways.
Another practices observational drawing, discovering that the intense visual attention it requires transfers directly to spotting hidden patterns in consumer behavior.
Somewhat counterintuitively, the brand Meijin mind doesn’t come from having more answers; it comes from becoming comfortable with ambiguity—from learning to stay in questions instead of rushing to find answers. While algorithms are excellent at finding solutions to well-defined problems, the meijin is at its best when the problems aren’t well-defined, and it can sense opportunities in the unclear areas beyond current frameworks.
As strategy changes from optimizing within known parameters to reimagining parameters themselves, this ability to dwell in uncertainty becomes more valuable. As one of my veteran strategist colleagues explained, "AI is extraordinary at helping you climb hills more efficiently. But it's not (yet) capable of telling you whether you're climbing the right hill in the first place."
Your 50,000 Hours Are Your Advantage: The Unexpected Value of Years Of Experience
This understanding provides not only professional hope but also existential redefinition for brand strategists in the third chapter of their careers who, like me, are feeling the weight of advancing years and advancing algorithms. The tsunami of generative AI isn't coming; it's already here. And yes, it’ll wash away the low-value aspects of our work that once required whole departments full of bright-minded humans.
But this technological disruption shouldn’t necessarily signal professional obsolescence for brand strategists. Quite the opposite—it adds unprecedented value to pattern recognition capabilities that only emerge after decades of immersion. The question isn’t whether AI will replace you, but rather whether you will evolve beyond the capabilities that AI can replicate.
Your accumulated experience isn't a liability but the essential foundation for Meijin transcendence. The thousands of patterns you've observed, the countless strategic challenges you've navigated, and the deep cultural understanding you've developed aren't obsolete assets but the raw materials from which your irreplaceable capabilities emerge.
The most profound misunderstanding in discussions about AI disruption is treating experience as merely accumulated knowledge—as if strategists with thirty years of practice just know more things than novices.
The truth is far more interesting: experience transforms not just what you know but how you know. It doesn't just add information; it creates new perceptual capabilities that algorithms and LLMs can’t (yet) replicate.
In a world increasingly dominated by algorithmic efficiency and machine intelligence, this metamorphosis in perception represents our profession’s most disruptive technology. The brand Meijin doesn't compete with AI on processing power but transcends it entirely, operating in domains of possibility and meaning that exist beyond algorithmic boundaries.
The brands that will thrive in the coming decade won't be those with the most sophisticated algorithms but those that most effectively integrate algorithmic intelligence with human-based strategic wisdom. Technical capability without cultural intuition produces efficient meaninglessness. Cultural understanding without technological leverage creates meaningful inefficiency. The intersection is where brands are beginning to shift from promise-making to meaning-making.
Rather than resisting the oncoming tide of machine intelligence, I'm convinced that success will come to strategy professionals who embrace its power but transcend its limitations.
About the Author
Adrian Barrow is the founder and principal strategist of Catalyst Strategy, a boutique studio for brand innovation based in Los Angeles. Catalyst brings together business expertise, cultural insights, and experience design to help businesses develop new ways for their brands to create customer value.
