The growing demand for ultra-sensitive, highly selective, and energy-efficient gas sensors in industrial safety, environmental monitoring, medical diagnostics, and homeland security has sped up advancements in gas sensing technologies. Conventional metal oxide-based sensors are widely utilized, but their stability, selectivity, and process compatibility issues often cause them to fall short of the performance demands of next-generation applications. Recent developments in materials science have enabled a new class of high-performance sensing materials, including transition metal dichalcogenides (TMDCs), graphene, metal-organic frameworks (MOFs), and MXenes. The exceptional surface-to-volume ratios, tunable electrical properties, and abundance of active sites in these materials enhance sensitivity, selectivity, and potential for miniaturization. This chapter comprehensively summarizes recent developments in emerging gas sensing materials and devices, crucial performance indicators, and structural design methodologies. The sensing mechanism of 2D materials, such as oxygen ion adsorption, Schottky barrier modification, and charge transfer, has also been discussed. Importantly, the integration of artificial intelligence (AI) and machine learning (ML) into sensor systems to revolutionize data collecting, pattern identification, and predictive analysis is also highlighted. The chapter concludes with a critical evaluation of the main obstacles, including environmental stability, device scalability, and material processability, and it looks at potential future developments for converting lab-scale breakthroughs into useful, AI-enhanced gas sensing platforms.