AI Ethics Maturity Models: a Systematic Literature Review and Research Agenda

Counts differ because each database indexes a different set of publications. We treat OpenAlex as the canonical count; Google Scholar is not shown (no API, and crawling it violates its ToS).

In recent years, Artificial Intelligence (AI) has advanced rapidly, becoming a routine part of people's lives worldwide. Despite its many benefits, it has also been associated with negative incidents. In response, governments, international organizations, and companies have released documents outlining principles or guidelines for ethical AI. However, the literature also reports ongoing challenges in their practical implementation. In parallel, maturity models have also been developed to assess and guide the implementation of ethical requirements for the development and use of AI systems. This study presents a systematic literature review to understand the state of the art in maturity models focused on ethics in AI and to identify remaining gaps. We found and analyzed 10 such maturity models and concluded that none were sufficiently validated or comprehensive. These findings point to the need for further research on maturity models focused on AI Ethics.