AI Maturity Model is stages of organizational AI capability. It sits in the Incentives dimension (INC) of the Human Behavior Taxonomy™ as element HBT-INC-0022, within the Strategy family. The core principle: stages of organizational AI capability. In incentive terms, it matters because it changes the payoff people perceive before they choose — which means it can be designed for, or exploited.
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.
Pending editorial review.
Original analysis from The Incentives Lab — how this element behaves inside real payoff structures.
Why this element matters to incentive design
This is one of the elements leaders describe as a values gap. It is a payoff gap. The mechanism underneath it operates in the Incentives dimension — what makes behavior more or less likely?. You can recognize it in the field by its signature: pilot ≠ production ≠ platform ≠ pervasive. Every element in the Incentives dimension changes the perceived payoff of an action before the action happens, which is exactly where incentive design has leverage.
How it gets exploited
Left undesigned, strategy phasing and investment sequencing. It is amplified whenever strategy phasing and investment sequencing. Inside organizations that shows up as strategy phasing and investment sequencing. The pattern is the same one Goodhart's Law describes: the measurable proxy attracts the effort, and the purpose behind it quietly loses funding.
How the Lab designs around it
The redesign move is to benchmark honestly. Don't claim a stage you haven't reached. The test of any redesign here is simple: after the change, can you name what the organization is now doing less of? If not, the payoff structure did not actually move.
Famous Experiments
Pending editorial review.
Design Principles
- Benchmark honestly. Don't claim a stage you haven't reached.
Measurement Approaches
Pending editorial review.
Evidence
Pending editorial review.
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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.
Pending editorial review.
Pending editorial review.
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.
Where AI Maturity Model is cited in the corpus
Essays, field guides, and diagnostics from The Incentives Lab that apply this element.
- Field guideIncentives: definition, types, examples
The parent field guide for this element.
- ReferenceThe laws of incentives
Goodhart, Campbell, and the Cobra Effect.
- EssayAI Agents Inherit Your Incentives
How this element propagates into automated systems.
- CourseIncentives 101
The free ten-part primer on reading a payoff structure.
- ReferenceThe incentive glossary
Definitions for every mental model, bias, and fallacy in the corpus.
- ReferenceThe Periodic Table of Human Behavior
The full 1,267-element map this page belongs to.
Questions about AI Maturity Model
- What is AI Maturity Model?
- AI Maturity Model is stages of organizational AI capability. It sits in the Incentives dimension (INC) of the Human Behavior Taxonomy™ as element HBT-INC-0022, within the Strategy family. The core principle: stages of organizational AI capability. In incentive terms, it matters because it changes the payoff people perceive before they choose — which means it can be designed for, or exploited.
- What is an example of AI Maturity Model?
- Strategy phasing and investment sequencing. The Incentives Lab catalogs everyday, organizational, and historical instances of this element on its Human Behavior Taxonomy™ page (HBT-INC-0022).
- How is AI Maturity Model exploited?
- Strategy phasing and investment sequencing.
- How do you design around AI Maturity Model?
- Benchmark honestly. Don't claim a stage you haven't reached.
- Which behavioral dimension does AI Maturity Model belong to?
- AI Maturity Model is classified in the Incentives dimension (INC) of the Human Behavior Taxonomy™, family "Strategy", class "AI-Behavioral Coupling". Its permanent identifier is HBT-INC-0022 and its evidence grade is C.