The increase in data volume and amount of data sources submitted as evidence such as from Internet of Things (IoT) devices or cloud computing systems has caused the digital forensics process to take longer than before. The increase in time consumption applies to all stages of the digital forensics process which includes collection, processing and analysing material. Researchers have proposed many different solutions to this problem and the aim of this study is to summarize these solutions by conducting a systematic literature review. The literature review uses a handful of search terms applied to three different databases to gather the material needed for the study which are then filtered by selection criteria to guarantee the quality and relevance to the topic. 29 articles were accepted for the analysis process which categorized the results by using thematic coding. The analysis showed that there were several ways to deal with data growth and different methods can be applied to different areas of digital forensics such as network forensics or social network forensics. Artificial Intelligence (AI) solutions in particular show a lot of potential for responding to the current and future challenges in the field by reducing manual effort and greatly increasing the speed of the processes.