| Alsheiabni et al. (2019) | None | General | 5 (Initial, Assessing, Determined, Managed, Optimized) | 4 (AI Functions, Data Structure, People, Organizational) | Brief | None | None | Bottom-up | Descriptive |
| Yablonsky (2019) | Data-Driven AI Innovation Maturity Framework | Innovation Management | 5 (Human Led; Human Led, Machine Supported; Machine Led, Human Supported; Machine Led, Human Governed; Machine Led and Machine Governed) | 4 (Who produces insight, Who decides and how, Who acts based on decision, Advanced analytics) | Detailed | None | None | Bottom-up | Descriptive |
| Ellefsen et al. (2019) | None | Logistic Processes | 4 (AI Novice; AI Ready; AI Proficient; AI Advanced) | 5 (Strategy, Organization, Data, Technology, Operations) | Brief | Questionnaire | Four logistics sector companies | Adopted organizational model | Descriptive |
| Lichtenthaler (2020) | None | General (AI Management) | 5 (Initial Intent, Independent Initiative, Interactive Implementation, Interdependent Innovation, Integrated Intelligence) or 7 (adding Level 0: Isolated Ignorance and Level +: Intuitive Ingenuity) | 3 (different types of AI, different types of human intelligence, meta-intelligence combining different types of intelligence) | Brief | None | None | Bottom-up | Descriptive |
| Fukas et al. (2021) | Auditing AI Maturity Model (A-AIMM) | Auditing Firms | 5 (Initial, Assessing, Determined, Managed, Optimized) | 8 (Technologies, Data, People and Competencies, Organization and Processes, Strategy and Management, Budget, Products and Services, Ethics and Regulations) | Detailed | None | None | Bottom-up | Descriptive |
| Yams et al. (2021) | AI Innovation Maturity Index (AIMI) | Innovation Management | 5 (Foundational, Experimenting, Operational, Inquiring, Integrated) | 7 (Data, Technology, Organization, Strategy, Ecosystems, Mindsets, Trustworthiness) | Brief | None | None | Top-down | Descriptive |
| Holmström (2021) | AI Readiness Framework | General | 5 (None, Low, Moderate, High, Excellent) | 4 (Technology, Activities, Boundaries, Goals) | Brief | Questionnaire | Insurance sector company | Bottom-up | Descriptive |
| Schuster et al. (2021) | SME-focused AIMM | Small and Medium Enterprises | 5 (Novice, Explorer, User, Translator, Pioneer) | 7 (Culture, Data, Ethics, Organization, Privacy, Strategy, Technology) | Brief | None | None | Bottom-up | Descriptive |
| Chen et al. (2021) | I-AI Maturity Model | Intelligent Manufacturing Systems and Industrial Processes | 5 (Planning Level, Specification Level, Integration Level, Optimization Level, Leading Level) | 2 (Industry, AI) | Very detailed | Questionnaire | None | Bottom-up | Partially prescriptive |
| Noymanee et al. (2022) | AI MM for Government Administration and Service | Government and Public Sector Organizations | 5 (Rookie Level, Beginner Level, Operational Level, Expert Level, Mastery Level) | 4 (Strategy, Organization, Information, Technology) | Brief | None | None | Bottom-up | Descriptive |
| Das et al. (2023) | Trustworthy AI System MM (TAS-MM) | General | 4 (Level 0, Level 1, Level 2, Level 3) | 4 (Auditability, Explainability, Fairness, Safety) | Detailed | None | None | Bottom-up | Descriptive |
| Sonntag et al. (2024) | SMMT Maturity Model | Manufacturing Sector Companies | 5 (Initial, Experimental, Practicing, Integrated, Transformed) | 5 (Culture and Competencies, Strategy, Data, Organization and Processes, Technology) | Detailed | Questionnaire | Three divisions of one manufacturing company | Bottom-up | Partially prescriptive |
| Chukhlomin (2024) | EMERALD-GenAI-CMM-OAL | Online Education and Adult Learning | 5 (Pre-generative AI Level, Foundational Level, Intermediate Level, Advanced Level, Expert Level) | 5 ((E) External Environment and Graduate Skill Expectations (M) Technological Means, Tools and Platforms (examples) (E) Essential Tasks and Use Cases (RA) Required Abilities, Skills, and Competencies (LD) Learning Designs and Strategies) | Detailed | None | None | Bottom-up | Descriptive |