A protocol-first framework for understanding AI adoption — from shadow use to planetary infrastructure.
Organizations fail at AI adoption by applying enterprise-software governance logic to a probabilistic, non-deterministic stack. The tools are not the problem.
The AI Capability Maturity Model reframes AI adoption as a protocol design problem. Shadow adoption, quality risk, trust collapse, and over-reliance are all protocol failures: breakdowns in the rules governing how humans and AI systems interact. A maturity model built on that framing generates different, more specific recommendations than one organized around security controls or tooling adoption rates.
Three deliverables. One coherent framework.
Start with the assessment to place your organization. Read the litepaper for the full framework. The blog post is the argument for why this framing matters.
Step through the five levels and place your organization. Receive a level-specific diagnosis: failure modes, blind spots, and a single next action.
Open the assessment →Eight pages. Five levels, each with its governing protocol, characteristic failure mode, historical parallel, and transition requirement. Built for deployment managers and operations executives.
Read the litepaper →Why AI intensifies work at the individual level while organizational standardization lags, and what enterprises keep missing about it. Introduces the bricoleur framing and the F2F pattern.
Read the post →Maturity is defined by the organization's ability to govern uncertainty productively, not process compliance.
The interactive diagnostic walks you through the five levels and returns a level-specific diagnosis with failure modes and a next action.
Protocolized is a publishing and consulting practice within the Summer of Protocols ecosystem. We apply protocol thinking to organizational, institutional, and technical problems. The Protocols for Business Group produces practitioner-facing frameworks for deployment managers and operations executives navigating AI adoption.