Stepstones, Not Moonshots: Leading Through the AI Shakeup

A century ago, apprenticeships were the scaffolding of work. You swept the floor, shadowed a master, and climbed rung by rung until you became one yourself. Today, AI is quietly dismantling that ladder. Entry-level jobs—the traditional training ground for future leaders—are shrinking, while new roles are emerging that ask us to orchestrate systems rather than simply execute tasks.

AI adoption is rewriting the org chart.
But adoption without absorption creates indigestion. This is what I call the Digestion Gap—organizations consuming AI pilots faster than they can meaningfully process and implement them. The result? Innovation theater instead of lasting change.

This gap reveals itself most clearly in how we’re restructuring work itself.

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The New Architecture of Work

Product leaders are already describing this shift. Instead of seeing teams as “traffic controllers” moving tickets across boards, they now see “shipyard teams”—small crews managing projects like vessels, with AI copilots steering logistics and coordination.

But we can’t run this new architecture with yesterday’s playbook. Words like agile, pivot, disruption, and transformation—which defined the last two decades—now feel like an inside joke. As Greg Storey writes: “Yesterday’s playbook won’t work. For reals this time.”

The new ingredient is agency: the capacity for teams to prioritize, adapt, and own outcomes without waiting for top-down scripts.

Understanding this architectural shift is only the beginning. The real challenge lies in execution—moving from AI experiments to sustainable transformation.

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From Pilots to Compound Advantage

AI hype is full of moonshots: flashy demos, one-off pilots, and grand announcements. But moonshots rarely stick. The organizations that truly change don’t chase one big leap; they build stepstones—the small, repeatable wins that carry you across the river.

Research into AI execution playbooks shows that the difference between dabbling and truly compounding isn’t in the experiments themselves, but in absorption—the rituals, evaluation systems, and shared platforms that turn pilots into lasting capabilities.

The Digestion Gap explains why most AI pilots fail to scale—companies generate experiments faster than they can digest insights. Closing this gap requires deliberate systems that slow consumption just enough to enable absorption.

The solution lies in pairing two elements: rituals and protocols.

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Rituals + Protocols of Adoption

Adoption isn’t magic; it’s designed.

• Rituals: Companies like Netflix and Stripe run hackathons and training loops to normalize AI use, making it part of the daily workflow.
• Protocols: The Model Context Protocol (MCP) treats AI agents like new hires, onboarding them with structured access, guardrails, and repeatability. Fast Company reports that this approach is already reshaping hospitals, retailers, and government agencies.

Culture makes AI used. Protocols make AI useful. Put them together, and hype becomes habit.

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The Hollowing of Entry-Level Work

Here’s the paradox: AI boosts capability while eroding the very rungs where humans once learned the craft.

• A Harvard study found that AI-adopting firms cut junior hiring by 22%.
• A field trial with 70,000 applicants showed AI voice recruiters increased job offers, starts, and retention.

The ladder is disappearing. The grunt work that once taught judgment is being automated. If AI takes the grunt work, where do the next leaders cut their teeth?

The answer isn’t more prompts. Prompts are syntax; literacy is fluency. Literacy means teaching context, judgment, and knowing when not to use the machine. That’s the new on-ramp.

👉 What would an AI-era apprenticeship look like in your field?

This erosion of learning pathways creates a new challenge: if AI handles routine work, where do future leaders develop judgment? The answer lies not in fighting automation, but in redesigning human development around what machines cannot replicate.

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Human Inside

Brian Solis calls for a critical mindshift: stop treating technology as a tool for cost-cutting automation and start designing for empathy, experience, and emotion. Customers don’t remember transactions; they remember how they felt.

IKEA deflected 47% of service requests with a chatbot, but the real breakthrough came when they reskilled human agents as interior designers—transforming a cost center into a revenue stream.

Disney Imagineers obsess over every detail, because only extraordinary experiences are truly remembered.

AI can help, but only if we design for “human inside.” Hype won’t save you. Frameworks won’t save you. AI won’t save you. Your people might—if you help them.

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A Closing Thought

The Digestion Gap—this widening space between what organizations can consume and what they can meaningfully process—reveals itself most clearly in AI adoption. Leaders adopt at machine speed while their teams digest at human pace.

This metabolic mismatch creates organizational indigestion: failed pilots, eroded talent pipelines, and cultural fatigue.

The work ahead isn’t about faster demos—it’s about building stepstones, rituals, and new on-ramps that give people the space to learn, adapt, and grow into new forms of leadership.

👉 Question for readers: If AI is rewriting the org chart, what new on-ramps for growth would you design inside your teams?

Madam I’m Adam