A maturity model for applied generative AI: a framework for senior leaders

In the rapidly evolving landscape of AI, organizations often lack a clear maturity model to assess their progress and capabilities, unlike established frameworks for cloud transformation and DevOps. This text discusses a proposed AI maturity model that spans five levels—Experimenting, Adopted, Observed, Governed, and Optimized—each representing stages of AI integration and sophistication within an organization. The model evaluates five dimensions: visibility and observability, evaluation and quality, cost governance, access and identity, and audit and incident response, providing a comprehensive framework for leaders to assess their AI practices. It emphasizes that the model serves as a diagnostic tool rather than a prescriptive target, encouraging organizations to close specific gaps that hinder progress, such as those in visibility or evaluation, rather than rushing to achieve the highest level. The text also highlights the role of the Pydantic stack in addressing various dimensions of the model and notes areas it does not fully cover, inviting leaders to engage in meaningful conversations about their AI strategies.