Ai Scalability

AI Scalability is a strategic framework within artificial intelligence that specifies the capacity of AI systems to maintain performance efficiency and operational effectiveness as they expand in scope, complexity, or deployment scale across diverse organizational and technical environments.

17

Publications

772

Citations

45

Authors

29

Institutions

Publications per year

2017–2026

16

Authors

45

  1. WW
    Walker White

    Cornell University, United States

    1 publications · 59 citations

    1

    h-index

  2. RR
    Rajmohan Rajagopalan

    Saarland University, Germany

    1 publications · 59 citations

    1

    h-index

  3. KS
    Kaj Sotala

    Machine Intelligence Research Institute, United States

    1 publications · 12 citations

    1

    h-index

  4. EO
    Enoch Oluwademilade Sodiya

    University of Maryland, Baltimore County, United States

    1 publications · 88 citations

    1

    h-index

  5. ED
    Ejike David Ugwuanyi

    University of Maryland, Baltimore County, United States

    1 publications · 88 citations

    1

    h-index

1–5 of 45

Venues

  1. Technological Forecasting and Social Change

    2 publications · 157 citations

    2

    h-index

  2. Humanities and Social Sciences Communications

    1 publications · 70 citations

    1

    h-index

  3. Journal of Resource Recovery

    1 publications · 24 citations

    1

    h-index

  4. 1

    h-index

  5. Radiology Artificial Intelligence

    AI · 1 publications · 14 citations

    1

    h-index

1–5