Introduction: Despite advances in understanding the pathophysiology of rheumatoid arthritis (RA) and head and neck cancer (HNC) individually, their shared genetic and molecular mechanisms remain poorly defined. Methods: This study aimed to explore gene-level connections between RA and HNC. A comprehensive literature mining approach identified gene-disease associations from PubMed and bioinformatics databases, covering 19,924 genes. An AI-driven computational pipeline applied the Adjusted Binomial Method Algorithm (ABMA) to assess association reliability. Overlapping genes were analyzed through protein-protein interaction (PPI) networks, functional annotation, and literature-based pathway analyses to elucidate common and distinct mechanisms. Results: The analysis identified 3,697 RA-related and 6,249 HNC-related genes, supported by 13,555 and 16,096 references, respectively, with a significant overlap of 2,549 genes (OR = 7.52; p < 1 x 10(-16)). Statistical refinement yielded 224 significant RA genes and 421 significant HNC genes, including 35 overlapping genes (OR = 9.27; p = 1.63 x 10(-20)), which formed a dense PPI network (206 edges; density = 0.17; clustering coefficient = 0.67). Seven key hub genes- TLR2, RAC1, RELA, CTSK, CDC42, CXCL11, and CYP2C19-emerged as central nodes in immune and inflammatory regulation. Functional enrichment analysis identified nine significantly enriched pathways or categories, including inflammatory response, chemotaxis, and the chemokine signaling pathway. Pathway analysis further revealed a bidirectional regulatory loop linking RA and HNC via five of these hub genes (RELA, CDC42, CTSK, CXCL11, and CYP2C19), which mediate feedback mechanisms in immune-inflammatory signaling. Conclusion: These findings highlight robust immuno-inflammatory mechanisms that may serve as shared therapeutic targets for both conditions.