Staying up-to-date with the latest research can feel like trying to drink from a firehose. Millions of academic papers are published every year, making it nearly impossible for researchers to manually sift through everything. Systematic Literature Reviews (SLRs) offer a structured approach to summarizing key findings, but they are notoriously time-consuming and labor-intensive. What if AI could do the heavy lifting? Researchers have developed PROMPTHEUS, an AI-powered pipeline that streamlines the SLR process using Large Language Models (LLMs). This innovative system automates key stages, from searching databases like arXiv to extracting data, identifying key topics using a technique called BERTopic, and even summarizing findings into coherent reports. PROMPTHEUS significantly reduces the time researchers spend on manual tasks, allowing them to focus on the more creative and insightful aspects of their work. The system uses sophisticated NLP techniques and LLMs like GPT and T5 to ensure that the generated summaries are not only accurate but also readable and well-organized. Evaluations across diverse research areas, from Explainable AI to blockchain, show promising results: PROMPTHEUS can cut down review time while maintaining high precision and organizing topics coherently. But it's not a perfect solution. Challenges remain, including ensuring the AI doesn't 'hallucinate' information and addressing potential biases in the literature selection process. Moreover, the current system relies on proprietary LLMs, raising questions about accessibility and cost. Future research will explore incorporating open-source models and further refining the system's ability to handle complex queries and maintain high readability in generated reports. Despite these challenges, PROMPTHEUS offers a glimpse into the future of research, where AI assists human experts in navigating the ever-expanding ocean of scientific knowledge, ultimately accelerating the pace of discovery.