Scientific Definition
Stages of organizational AI capability.
Plain-English Definition
Stages of organizational AI capability.
Feynman Explanation
Pilot ≠ production ≠ platform ≠ pervasive.
Core Principle
Stages of organizational AI capability.
Mechanisms
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Inputs (Triggers)
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Outputs (Behaviors)
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Behavioral Signature
Pilot ≠ production ≠ platform ≠ pervasive.
Examples
- Standard maturity frameworks from major analysts.
- Strategy phasing and investment sequencing.
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Famous Experiments
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Design Principles
- Benchmark honestly. Don't claim a stage you haven't reached.
Measurement Approaches
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Evidence
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The Perverse Incentive Lens™
How this behavior is exploited — and how to redesign around it.
- Benchmark honestly. Don't claim a stage you haven't reached.
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Interactive Mini Network
Click any neighbor to re-center the graph and follow the threads of connection.
Knowledge Graph Neighbors
Auto-linked to the rest of the Human Behavior Taxonomy by family, domain, dimension, and shared keywords.
Augmentation strategy vs. substitution strategy.
AI strategy = decisions about which capabilities to build and where.
Augment when judgment matters. Automate when scale matters.
Strategic choice on AI capability sourcing.
AI capability outpacing organizational ability to use it.
Specialized training on domain data.
Open-weight vs. API-only models.
Concentration risk on a single AI provider.
Operating economics shaped by per-token pricing.
A handful of providers shape the entire AI economy.
Documentation of model purpose, performance, limitations, and risks.
Train a smaller model to imitate a larger one.