With the increasing popularity of Artificial Intelligence (AI) and Machine Learning (ML), several studies have utilized AI and ML techniques to enhance the digital evidence analysis processes and obtain accurate results with less time and effort. This paper surveys the current research efforts concerned with applying AI and ML techniques into the fields of digital forensics, and provides a comprehensive overview and insightful comparisons of relevant works across different sub-disciplines. All surveyed works were evaluated using traditional quantitative metrics, such as accuracy and F1 score, and the qualitative international standard on digital evidence interpretation ISO/IEC 27042, which provides a bird’s eye view on interpretability, a realistic expectation of a proposed forensic analysis method. Our findings indicate that several existing works fall short from satisfying all the metrics of the ISO/IEC standard.