White Paper v0.1: The Adaptive Adoption Maturity Model¶

Structured outline of the planned white paper. Section summaries indicate intended content; full drafting is in progress.

Planned Structure¶

1. Executive Summary¶

A concise statement of the problem (AI adoption outpaces organizational capability), the proposition (maturity-based assessment grounded in behavioral evidence), and the intended audience (CAIOs, CIOs, transformation leaders, governance professionals). Approximately 500 words.

2. The Problem: Why AI Adoption Fails¶

An evidence-based argument that AI adoption failure rates are high and that the dominant explanations (technology immaturity, resistance to change, insufficient training) are incomplete. The deeper cause: organizational capability has not kept pace with technology capability. Draws on McKinsey and BCG survey data on AI adoption outcomes, supplemented by academic research on technology assimilation. Approximately 1,500 words.

3. Why Existing Frameworks Fall Short¶

A critical analysis of prevailing approaches: traditional change management (Kotter, ADKAR), AI maturity models (Gartner, Microsoft), and governance frameworks (NIST AI RMF, EU AI Act compliance checklists). Each is assessed for what it contributes and where it fails when applied to AI adoption at scale. The central argument: existing frameworks address parts of the problem but none addresses the system. Approximately 2,000 words.

4. The Adaptive Adoption Maturity Model¶

The core exposition. Describes the three-pillar architecture (Change Agility, Leadership Delta, Behavioral Governance), the five maturity levels, and the three-layer assessment methodology. Explains the COM-B diagnostic driver integration and the trust driver framework. Includes dimensional definitions with illustrative examples. Approximately 3,000 words.

5. Behavioral Governance: The Distinctive Contribution¶

A focused treatment of Behavioral Governance as the framework's most novel element. Argues that governance is an enacted capability, not a compliance artifact. Describes the six dimensions with their theoretical foundations. Positions Behavioral Governance against existing AI governance approaches. Approximately 2,000 words.

6. The AAMI: Diagnostic Architecture¶

Technical description of the Adaptive Adoption Maturity Index. Covers instrument design, item architecture, assessment layer methodology, scoring approach, and output format. Addresses reliability and validity considerations. Approximately 1,500 words.

7. Practitioner Application¶

Guidance on how organizations use the framework: entry points, assessment sequencing, intervention design based on COM-B diagnosis, and progress tracking. Includes a worked example (anonymized or composite). Approximately 1,500 words.

8. Validation Roadmap¶

Describes the planned validation approach: pilot assessments, construct validity analysis, inter-rater reliability testing, and benchmarking methodology. Acknowledges current limitations with transparency about what has and has not been empirically tested. Approximately 1,000 words.

9. Conclusion¶

Restatement of the core proposition: AI adoption requires a maturity model built for behavioral reality, not aspirational compliance. The framework is offered as a working model — rigorous in design, transparent in limitations, and open to refinement through use. Approximately 500 words.

References¶

Full academic references for all cited sources. Adherence to APA 7th edition format.

Status¶

This outline represents the planned v0.1 white paper. Sections 1-4 are in active drafting. Sections 5-9 are outlined with key arguments identified. Target completion: Q3 2026. The white paper will be published on paulgibbonsadvisory.com and submitted to relevant practitioner and academic outlets.