Inside AI Maturity Model

AI transformation with AI maturity model

Software ate the world. The software maturity model (aka Capability Maturity Model, CMM) became a necessary framework for enterprises to standardize and improve software development processes. Now, AI is eating the world. AI maturity model is also essential for AI adoption and refinement.

Along with AlphaGo’s stunning victory in 2016, Gartner, Element AI, Microsoft, IBM, and others started building AI maturity models and frameworks. They have defined different maturity models and frameworks according to their perspectives, but they all curve from low foundational to high transformational levels. Some have segmented the levels into multiple dimensions, forming a 2D model grid. For instance, Element AI has defined five dimensions (Strategy, Data, Technology, People, and Governance) for each stage (i.e., level), from exploring to experimenting, formalizing, optimizing, to transforming.

Gartner and Microsoft AI Maturity Models explained (by author)

Gartner measures an organization against the AI maturity model on five levels, from awareness to active, operational, systemic, and transformational. And Microsoft has defined four maturity levels, from foundational to approaching, aspirational, and mature. Please see detailed descriptions in the above diagram. Companies in the transformational stage are already using AI to achieve significant business value. e.g., Google and Meta use ML extensively to rank pages/posts and advertisements. It’s old news that ML-recommended relevant products or movies have become preferred choices for customers on Amazon and Netflix.

More information refers to Inside AI Maturity Model - Five Steps to Transform with Data-centric AI Engineering on TDS.