Today's modern technologies and requirements make the utilization of crowdsourcing more viable and applicable. It is one of the problem-solving models that can be used in various domains to reduce costs and time. It is also an excellent way to find new and different ideas and solutions. This paper studies the use of crowdsourcing in software engineering and reveals adequate details to highlight its significance. A few recent literature reviews have been published to address specific topics or study general attributes of papers in crowdsourced software engineering. This paper, however, explores all recent publications related to software and crowdsourcing to find the trends and highlight mobile and AI usage in software crowdsourcing. The findings of this paper show that most research papers are in the areas of software management and software verification and validation. The results also reveal that machine learning and data mining techniques are predominant in software management crowdsourcing and software verification and validation. Furthermore, this study shows that the methods and techniques used in general crowdsourcing apply to mobile crowdsourcing except in mobile testing, where there is a need for clustering and prioritization of test reports.