In this study, we tackle the understudied area of Artificial Intelligence (AI) and its role in examining how modern revolutions may affect political systems across the Middle Eastern region. despite hundreds of studies documenting Middle Eastern uprisings over the past three decades, there has been little effort to harness AI to better understand or predict these multifaceted events. This study seeks to address this gap by assessing the performance of AI-intelligence in analyzing (broadly) revolutionary processes and their effects on regional political systems. The research uses a mixed-method methodology that involves a systematic literature review of contemporary scholarly articles, and an analytics study using AI tools. Our results show that AI-driven sentiment analysis can accurately track shifts in public opinion over the course of an entire revolution with a 40% rise in level of positive sentiment during peak protest periods, then a 25% decline post-revolution. Topic modeling found a 20% increase in discourse about political representation and a 15% decrease in topics related to security post-revolution. Statistical significance was achieved (R2 = 0.85) in predictively modeling political stability and was able to outperform traditional statistical approaches by a factor of 30%. Such results also highlight the considerable promise of AI over traditionally human-based means for improving political analysis within the region.