A sociotechnical perspective for responsible AI maturity models: Findings from a mixed-method literature review

Abstract

As artificial intelligence (AI) is increasingly used in various industries, it becomes crucial for organizations to enhance their capabilities and maturity in adopting AI responsibly. This paper employs a mixed-method approach that combines topic modeling with manual content analysis to provide a comprehensive review of the literature on AI maturity and readiness. The review encompasses an extensive corpus of 1451 papers, identifying the main themes and topics within this body of literature. Based on these findings, a subset of papers was selected and further analyzed to identify AI capabilities utilizing a sociotechnical lens. This further analysis led to the identification of foundational and responsible AI (RAI) capabilities. These capabilities have been integrated in a sociotechnical framework of capabilities for AI maturity models providing valuable insights for organizations and AI service providers and a basis for further research.

Keywords

• Artificial intelligence
• Maturity model
• Responsible AI capabilities
• Topic modeling
• Sociotechnical