RAIL: An Automatic Classifier of the Artificial Intelligence Readiness Level
Assessing the maturity of artificial intelligence technologies is essential for investment decisions, project management, and policy monitoring, yet the available readiness frameworks are heterogeneous and difficult to apply automatically: the adaptation of Technology Readiness Levels to AI lacks AI-specific gating criteria, the Machine Learning Technology Readiness Levels presuppose access to internal process artifacts, and AI/data readiness dimension models employ scales that resist direct comparison. This paper makes two contributions. First, we unify these three frameworks into the Unified
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- PossiblePossibly related (embedding) · 51%AI in the LIMS: How Machine Learning Is Changing Research Data Management - Technology Networks →
- PossiblePossibly related (embedding) · 50%Artificial Intelligence in Industrial Maintenance Reaches 58% Adoption - Inspenet →
- PossiblePossibly related (embedding) · 49%The foundational elements of AI architecture that IT leaders need to scale →
- FuzzySimilar title/name (fuzzy) · 66%owainlewis/awesome-artificial-intelligence →
“Fuzzy title match (0.78): “RAIL: An Automatic Classifier of the Artificial Intelligence” ≈ “owainlewis/awesome-artificial-intelligence””
- LinkedLinked via arxiv author · 85%Juan Irving Vasquez →
“RAIL: An Automatic Classifier of the Artificial Intelligence Readiness Level”
- LinkedLinked via arxiv author · 85%Juan Terven →
“RAIL: An Automatic Classifier of the Artificial Intelligence Readiness Level”
- LinkedLinked via arxiv author · 85%Laura-Ivoone Garay-Jimenez →
“RAIL: An Automatic Classifier of the Artificial Intelligence Readiness Level”