  The development of artificial intelligence (AI) has made various industries
eager to explore the benefits of AI. There is an increasing amount of research
surrounding AI, most of which is centred on the development of new AI
algorithms and techniques. However, the advent of AI is bringing an increasing
set of practical problems related to AI model lifecycle management that need to
be investigated. We address this gap by conducting a systematic mapping study
on the lifecycle of AI model. Through quantitative research, we provide an
overview of the field, identify research opportunities, and provide suggestions
for future research. Our study yields 405 publications published from 2005 to
2020, mapped in 5 different main research topics, and 31 sub-topics. We observe
that only a minority of publications focus on data management and model
production problems, and that more studies should address the AI lifecycle from
a holistic perspective.
