# Recent Applications of Explainable AI (XAI): A Systematic Literature Review
## 5 Discussion and Conclusions
### Limitations and Future Work  
This systematic literature review has several limitations that should be acknowledged. Firstly, the review relied exclusively on the WoS database to identify and retrieve relevant studies. While WoS is recognized as one of the most prestigious and widely utilized research databases globally, known for its rigorous indexing standards and the high quality of its data sources [38], the reliance on a single database may introduce a potential bias by omitting relevant literature indexed in other databases such as Scopus, IEEE Xplore, or Google Scholar. However, it is important to note that the comprehensive nature of WoS mitigates this limitation to some extent. WoS encompasses a vast array of high-impact journals across various disciplines, ensuring that the most significant and influential works in the field of XAI are likely to be included. Moreover, the substantial volume of results yielded from WoS alone necessitated a practical constraint on the scope of the review. Including additional databases would have exponentially increased the literature volume, rendering the review process unmanageable within the given resources and timeframe. Secondly, the exclusion criteria applied in this review present additional limitations. Only studies published in English were included, which could potentially skew the findings by overlooking valuable contributions from non-English-speaking researchers and regions. Furthermore, the review was limited to studies published after 2021 to ensure the \"recentness\" of the applications of XAI. While this criterion was essential to focus on the latest advancements and trends, it may have excluded foundational studies that, although older, remain highly relevant to the current state of the field. Additionally, the review was restricted to journal articles, excluding conference papers that often publish seminal work, particularly in the fast-evolving domain of XAI. Given the considerable volume of literature, including conference papers would have extended the scope beyond what was feasible within the current study. Moreover, the review process involved manually reading and categorizing each paper to develop detailed codes, allowing for a nuanced analysis of the literature. While more automated approaches to systematic reviews could have incorporated a broader range of sources, such methods may lack the precision and depth achieved through manual categorization. Future research could explore the use of automated methods to include key conference papers and older foundational studies, providing a more comprehensive understanding of the field's development over time. However, for this review, our focus on recent journal publications, combined with an in-depth manual analysis, was necessary to provide a manageable and focused examination of the most current trends in XAI. In summary, while these limitations--namely, the reliance on a single database, language restrictions, the specific timeframe, and the focus on journal articles excluding conference papers--are noteworthy, they were necessary to manage the scope and ensure a focused and feasible review process. Future research could address these limitations by incorporating multiple databases, including non-English studies, expanding the temporal range to include older foundational work, and considering a broader set of sources, such as conference papers. This approach would provide a more comprehensive overview of the literature on XAI and its development over time. Finally, it is important to highlight that the field of XAI is rapidly evolving. During the course of conducting and writing this review, numerous additional relevant articles emerged that could not be incorporated due to time constraints. This underscores the dynamic and ongoing nature of research in this area. Conceptualization, M.S. ; methodology, M.S. ; validation, M.S. and V.P. ; formal analysis, M.S. and V.P. ; investigation, M.S. and V.P. ; resources, M.S. ; data curation, M.S. and V.P. ; writing--original draft preparation, M.S. and V.P.