Why Most AI Transformations Are Just Expensive Theater
- mbhirsch
- Aug 11
- 6 min read
Sometimes the most satisfying moment in strategy isn't being proven right, it's watching the market finally catch up to what you've been quietly building.
This week, Lenny's Newsletter published Peter Yang's research on AI adoption at companies like Shopify, Ramp, and Zapier. Five systematic steps. Twenty-five tactical insights. Valuable documentation of what successful companies actually do.
Reading Yang's insights felt like watching someone discover a trail I've been walking for two years.
The response reveals something telling: leaders are absorbing the tactics, but missing the strategic architecture that makes those tactics work. Yang documented successful behaviors without identifying the cognitive frameworks that generate them. It's like learning to play a virtuoso's piece note-for-note without understanding the music theory and compositional principles that make it work.
Most leaders will read his five steps, create implementation plans, and then wonder why their results feel more like expensive organizational theater than transformation.
Yang surfaced five recurring steps that successful companies take:
Explain the how
Track and reward adoption
Cut the red tape
Turn enthusiasts into teachers
Prioritize high-impact tasks
What he actually documented: the Six Personas of Product Leadership solving the AI adoption challenge systematically. (The Six Personas framework emerged from my discovering that the leap from individual contributor to product leader requires a fundamentally different set of capabilities. In my experience, this transition came with zero guidance. Every persona—from Talent Gardener to Strategic Orchestra Conductor to Political Navigator—represents a blind spot I discovered through expensive trial and error.)
When Whoop's Hilary Gridley brings up a problem and says "Want me to show you how I solve this with AI?" then shares her workflows live—that's the Talent Gardener understanding that effective skill transfer requires demonstration, practice, and structured feedback loops.
When Intercom's CTO Darragh Curran set a goal to "2x productivity with AI" and spent a week every month embedded with individual teams—that's the Strategic Orchestra Conductor assessing capability gaps and designing targeted interventions.
When Zapier assigned a lead PM to work with procurement, legal, and engineering to fast-track AI tool approvals—that's the Political Navigator understanding that organizational friction kills momentum faster than technical complexity.
The Validation I Didn't Expect
The validation came from Yang's observation about "turning enthusiasts into teachers." This aligns precisely with the AI Champions approach I use in my private team training—identifying potential champions within teams and developing their ability to teach and evangelize effectively.
Enthusiasts don't automatically become effective teachers. Teaching requires structured approaches to skill transfer, adult learning principles, and the ability to translate personal expertise into frameworks others can follow. Absent this, you're just hoping your naturally gifted enthusiasts happen to also be natural educators.
What's fascinating is that if you asked Hilary Gridley, Darragh Curran, or Wade Foster what strategic frameworks guided their decisions, they probably couldn't articulate them. They acted on experience, intuition, and yes—a little luck. They intuitively applied sophisticated leadership thinking without consciously recognizing the underlying patterns.
This is exactly why the whole discipline of strategy is taught and learned primarily through case studies. We reverse-engineer success stories to identify the strategic principles that brilliant leaders applied instinctively. Harvard Business School doesn't teach strategy through abstract theory—they dissect what Amazon, Netflix, and Apple actually did, then extract the frameworks that made those decisions repeatable.
This is exactly why most companies will fail to replicate their success. You either need their years of hard-won experience and intuitive grasp of organizational dynamics, or you need to understand the strategic thinking that generates those intuitive decisions.
“You either need their years of hard-won experience and intuitive grasp of organizational dynamics, or you need to understand the strategic thinking that generates those intuitive decisions.”
A Competitive Separation Is Accelerating
Yang's research signals something bigger than successful AI tactics—it reveals a competitive separation that's about to accelerate.
Companies that understand the strategic architecture behind these tactics will build sustainable competitive advantages. They'll develop organizational capabilities that extend far beyond current AI tools. They'll create cultures of systematic learning that adapt quickly to whatever technological shift comes next.
In contrast, companies that copy the tactics without understanding the strategic foundation will hit a plateau. Their initial enthusiasm will fade. Their metrics will stagnate. They'll wonder why their "AI transformation" didn't transform anything fundamental about how they work.
This is sustainable competitive advantage protected by causal ambiguity. Competitors can observe the behaviors—Shopify's "build in the open" culture, Intercom's embedded leadership approach, Zapier's streamlined approval processes—but they can't reverse-engineer the strategic thinking that generates them. The isolation mechanism isn't patents or proprietary technology; it's the subtlety and complexity of leadership development.
Consider how this played out in previous technological shifts. Amazon didn't just adopt cloud computing—they built organizational capabilities around distributed systems thinking that manifested as AWS. Netflix didn't just use data analytics—they developed methodical approaches to content strategy that competitors still can't replicate effectively. The tactics were visible; the strategic architecture was invisible.
Today's AI-forward companies are following the same pattern. They're not just implementing AI tools—they're building structured approaches to capability development that will serve them across multiple technological shifts. The competitive moat isn't the AI; it's the organizational capacity to adapt.
“The competitive moat isn't the AI; it's the organizational capacity to adapt.”
When the next major technological shift arrives—and it will—these same companies will adapt quickly because they've built the strategic thinking capabilities that generate adaptive responses. They won't need new playbooks because they understand the principles that create effective playbooks.
Meanwhile, companies that copied their AI tactics without understanding the strategic foundation will find themselves back at square one, looking for the next set of tactics to copy.
The Framework That Makes It Work
These aren't AI-specific insights—they're applications of proven leadership thinking to the current technological moment. These are tried and true frameworks that have guided successful organizational transformations across decades of technological change, from the PC revolution to the internet to mobile. What makes them powerful isn't their novelty; it's their adaptability.
Yang's research validates my frameworks not because I predicted these specific tactics, but because strategic leadership thinking generates predictable patterns across any domain. The Strategic Orchestra Conductor naturally emphasizes coordination and alignment. The Talent Gardener inherently focuses on capability development and skill transfer. The Political Navigator understands that organizational change requires managing stakeholder dynamics and eliminating friction.
Applied to AI adoption, these produce exactly the behaviors Yang observed—embedding with teams, turning enthusiasts into teachers, fast-tracking approvals, and building coalition support for capability development.
Your Strategic Assignment
Don't just implement Yang's five steps. Use them as a diagnostic tool for your own strategic thinking sophistication.
When you "explain the how," are you providing tactical instructions or building strategic understanding? When you "turn enthusiasts into teachers," are you hoping passion translates to pedagogical effectiveness, or are you developing teaching capabilities?
The questions reveal whether you're thinking tactically or strategically about organizational transformation.
More importantly: start building the strategic thinking capabilities that will serve you long after AI adoption becomes as routine as email adoption. The Six Personas framework, the AI Champions approach, the structured methods for capability development—these aren't just tools for the current moment. They're the strategic architecture for adaptive leadership in whatever technological future we're building.
Because here's what I know after more than two decades of product leadership and studying strategy: the companies that win aren't those that implement the best tactics. They're the ones that build the best strategic thinking capabilities.
Yang documented what that looks like in practice. I teach how to make it work reliably.
Your move: are you building tactics or capabilities?
If this resonated, please share It with that product leader who's still confusing AI tool adoption with AI transformation. They need to read this more than they need another demo of the latest productivity app.
Break a Pencil,
Michael
P.S. If you're ready to move beyond tactical copying to capability development, my next "Build an AI-Confident Product Team" cohort starts soon. This is exactly the kind of strategic thinking that separates sustainable transformation from expensive experimentation. [Learn more here]
P.P.S. Yang's research is excellent tactical documentation. But if you want to understand the strategic thinking that makes tactics sustainable, that requires a different kind of framework entirely. Sometimes the most important insights are hiding in plain sight.
Comments