Ai Maturity Models

AI Maturity Models is a strategic framework that systematically assesses and categorizes an organization’s level of AI capability development across dimensions such as data infrastructure, technical expertise, governance, and operational integration, differentiating it from general maturity models by its exclusive focus on artificial intelligence adoption and scalability.

49

Publications

2.7K

Citations

180

Authors

108

Institutions

Publications per year

2017–2026

45

Authors

180

  1. MM
    Michael Mylrea

    Pacific Northwest National Laboratory, United States

    2 publications · 104 citations

    2

    h-index

  2. NR
    Nikki Robinson

    Northwestern University, United States

    2 publications · 104 citations

    2

    h-index

  3. AC
    Angelo Corallo

    University of Salento, Italy

    1 publications · 37 citations

    1

    h-index

  4. EG
    Emília Gómez

    Universitat Pompeu Fabra, Spain

    1 publications · 124 citations

    1

    h-index

  5. GM
    Goran Mitrov

    Ss. Cyril and Methodius University in Skopje, North Macedonia

    1 publications · 57 citations

    1

    h-index

1–5 of 180

Venues

  1. Journal of the Association for Information Systems

    JAIS · 3 publications · 73 citations

    3

    h-index

  2. Technological Forecasting and Social Change

    3 publications · 192 citations

    3

    h-index

  3. Procedia Manufacturing

    2 publications · 81 citations

    2

    h-index

  4. Information Systems Management

    1 publications · 160 citations

    1

    h-index

  5. Entropy

    1 publications · 89 citations

    1

    h-index

1–5