How one ancient linguistic pattern explains the speed of modern organizational transformation
The New Migration Highway
The ancient steppes were a superhighway for a single language that eventually gave birth to English, Spanish, and dozens of others. Today, AI is acting as our modern linguistic superhighway, spreading a new vocabulary of work at a speed that would have been unimaginable to our ancestors.
In her fascinating book Proto: How One Ancient Language Went Global, Laura Spinney reveals how this linguistic conquest unfolded over millennia. But here’s what struck me: we’re witnessing a similar phenomenon today, compressed from centuries into months. The internet has become our modern digital steppe, and AI is spreading new vocabularies across organizations at unprecedented speed.
Words in Transit
Spinney notes that “linguists consider that on average it takes between five hundred and a thousand years for a language to become incomprehensible to its original speakers.” Yet I’m watching business vocabularies transform in quarters, not centuries.
What we’re losing:
- The whiteboard—once the physical heart of collaborative thinking—is becoming a relic
- The entire concept of a “definitive document” or “final version” is vanishing as AI lets us spawn dozens of iterations instantly
- The very practice of laboring over a single perfect artifact
I was in a meeting last month where a team was trying to brainstorm. Instead of walking up to a whiteboard, they opened a shared document and everyone started feeding “prompts” to an AI to generate ideas. The whiteboard was still in the room, but it was just a dusty ghost of a former workflow.
What we’re gaining:
- “Prompt”—once AI jargon—is now the default jumping-off point for everything from marketing copy to project plans
- “Contextual information” and “grounding” have entered the mainstream, as teams learn the value of clean starter data sets
- “Iterative spawning”—rapidly creating variations instead of refining a single version
As Spinney observes, “words can moonlight too, taking on second shifts as new concepts are born and demand labels.” We’re seeing this linguistic moonlighting happen in real-time.
The Distance Effect
Spinney discovered something crucial about how Proto-Indo-European spread: cultures living closer together saw gradual linguistic changes, while groups encountering each other from greater distances often experienced dramatic vocabulary shifts. Concepts without equivalent words simply disappeared.
I’m seeing the same pattern in organizations today. Teams working closely together maintain existing workflows and vocabularies. But when AI introduces concepts from “distant” domains—machine learning, prompt engineering, contextual reasoning—entire ways of working become obsolete overnight.
The Innovation Conquest Model
Organizations are managing this linguistic transformation through what looks remarkably like ancient patterns of cultural diffusion:
- Sense (Border Contact): Scanning for new AI signals, customer needs, and competitive moves
- Frame (Translation Attempts): Defining problems and opportunities in terms the organization can understand
- Translate (Cultural Adaptation): Fitting AI concepts to existing strategy, compliance, and incentives
- Prototype (Mixed-Language Communities): Running small experiments to test new vocabulary in safe spaces
- Institutionalize (Language Dominance): Codifying new processes, roles, and training to make the new language official
- Diffuse (Complete Adoption): Spreading proof points and playbooks across the entire organization
But here’s the critical difference: this process that took Proto-Indo-European centuries now happens in months.
The Digestion Gap
In the past 18 months, the pace of change has doubled—twice. What used to take two years now happens in three months. We can create faster than we can absorb.
This leaves a “linguistic substrate”—traces of old business languages embedded in new AI implementations, much like Latin roots in modern English. Legacy systems, cultural artifacts, and ingrained workflows shape AI adoption, sometimes productively, sometimes as friction.
The challenge isn’t learning new vocabulary—it’s building the cognitive infrastructure to internalize it at digital speed.
The Institutionalize Question
This brings me to what I’m studying most closely. The digestion gap hits hardest at the Institutionalize phase. Many organizations can pilot AI successfully, but struggle to make the cultural shift permanent when they scale.
Some are creating “communities of practice” around new AI vocabularies. Others are redesigning structures to support the new language of work. Many are still figuring it out.
Your Perspective Matters
I’m documenting patterns as they emerge, but your observations can complete the picture:
- What old business vocabulary is becoming obsolete in your organization?
- Which new AI terms are taking hold in everyday language?
- How are you managing the speed gap between AI capability and organizational absorption?
- What “linguistic substrate” do you see—traces of old ways persisting in new implementations?
- How is your team institutionalizing new vocabularies and workflows?
We’re witnessing linguistic evolution at digital speed. Unlike our Proto-Indo-European ancestors, we can be conscious observers of this transformation as it happens.
What patterns are you seeing in the great vocabulary shift of our time?
The future belongs to organizations that can master both the new language of AI and the timeless patterns of human adaptation. Let me know what you’re observing—I’d love to feature your insights in upcoming newsletters.
Adam, this is such an important insight: “The entire concept of a ‘definitive document’ or ‘final version’ is vanishing as AI lets us spawn dozens of iterations instantly.”
Running a design firm for over 13 years, I’ve seen firsthand how difficult it can be for a team to react to a single deliverable. Analyzing multiple possibilities rapidly is such a foreign task, and will definitely require new “corporate muscles”.
Ewww — corporate muscles sounds gross!