Things to Know…
Below are several commonly referenced AI maturity assessment frameworks.
Each offers a structured approach to evaluate how organizations adopt and scale AI capabilities.
1 – Gartner’s AI Maturity Model
Provides a five-level progression from Awareness, Active, Operational, Systemic, and Transformational.
Assesses technology readiness, data quality, skill sets, use case breadth, and governance.
It helps map the current state and identify the following steps to scale AI.
(Source: Gartner)
2 – Forrester AI Maturity Model
It defines four stages: novice, experimenter, practitioner, and expert.
Focuses on organizational readiness, data engineering, analytics culture, and business integration.
It helps firms understand their maturity relative to peers and guides strategic planning.
(Source: Forrester)
3 – IDC AI MaturityScape
Outlines a spectrum from Ad Hoc, Opportunistic, Repeatable, Managed, and Optimized.
Considers leadership support, data management, risk controls, skills, and best practices.
Emphasizes continuous improvement, scalability, and alignment with business outcomes.
(Source: IDC, “IDC MaturityScape: Artificial Intelligence”)
4 – Deloitte’s AI Maturity Framework
Deloitte’s AI Maturity Framework is a structured model designed to help organizations assess and enhance their AI capabilities.
It emphasizes a holistic approach, focusing on key dimensions such as strategy, talent, data, technology, and operations. The framework categorizes organizations into different maturity levels, guiding them through initial AI experimentation to achieve transformational AI integration.
Measures progress from exploration to sophisticated, integrated AI ecosystems.
Emphasizes value realization and trust in AI-driven decision-making.
(Source: Deloitte)
5 – MIT Sloan Management Review AI Adoption Framework
Identifies phases based on how firms use AI: isolated pilot projects to enterprise-wide transformation.
Focuses on leadership engagement, workforce enablement, data infrastructure, and ethical use.
Guides organizations in evolving from experimentation to fully integrated AI.
(Source: MIT Sloan Management Review, “Expanding AI’s Impact With Organizational Learning”)
McKinsey’s AI Transformation Framework: Outlines five stages – Ad-hoc, Localized, Integrated, Enterprise, and Embedded
6 – MITRE’s AI Maturity Model
Defines a framework and assessment method to evaluate an organization’s AI capabilities and practices.
Focuses on six domains: Strategy, Data, Technology, Workforce, Governance, and Continuous Learning.
Progresses from foundational experimentation through integrated, enterprise-wide AI adoption.
Emphasizes trust, responsible use, risk management, and alignment of AI with mission objectives.
(Source: The MITRE AI Maturity Model and Organizational Assessment Tool Guide)
7 – TM Forum AI Maturity Model Toolkit
Provides a structured method to assess and improve AI adoption in telecommunications and digital services.
Covers core dimensions like strategy, governance, data management, technology, skills, and processes.
Maps an organization’s progression from initial exploration to fully integrated, AI-driven operations.
Includes practical tools, measurement criteria, and best practices to guide incremental enhancements.
Aligns AI initiatives with business objectives, operational efficiency, and improved customer experiences.
(Source: AI Maturity Model Toolkit)
