This review critically examines the progress and challenges in the field of nanostructured tungsten oxide (WO₃) gas sensors. It explores significant advancements in nanostructuring and composite formation of WO₃, which have improved sensor sensitivity for gases like NO₂, NH₃, and VOCs, achieving detection limits in the ppb range. The review systematically discusses innovative approaches such as doping WO₃ with transition metals, creating heterojunctions with materials like CuO and graphene, and using machine learning models to optimize sensor configurations. Challenges include cross-sensitivity to different gases, particularly at higher temperatures, and long-term stability affected by factors like grain growth and volatility of dopants. Potential solutions include statistical analysis of sensor arrays, surface functionalization, and novel nanostructures for enhanced performance and selectivity. The review also discusses the impact of ambient humidity on sensor performance and current strategies to mitigate it, such as composite materials with humidity shielding effects and surface functionalization with hydrophobic groups. The need for high operating temperatures, leading to higher power consumption, is addressed, along with possible solutions like advanced materials and new transduction principles to lower temperature requirements. The review concludes by highlighting the necessity for a multidisciplinary approach in future research, combining materials synthesis, device engineering, and data science to develop the next generation of WO₃ sensors with enhanced sensitivity, ultrafast response rates, and improved portability. The integration of machine learning and IoT connectivity is posited as a key driver for new applications in areas like personal exposure monitoring, wearable diagnostics, and smart city networks, underlining WO₃'s potential as a robust gas sensing material in future technological advancements.This review critically examines the progress and challenges in the field of nanostructured tungsten oxide (WO₃) gas sensors. It explores significant advancements in nanostructuring and composite formation of WO₃, which have improved sensor sensitivity for gases like NO₂, NH₃, and VOCs, achieving detection limits in the ppb range. The review systematically discusses innovative approaches such as doping WO₃ with transition metals, creating heterojunctions with materials like CuO and graphene, and using machine learning models to optimize sensor configurations. Challenges include cross-sensitivity to different gases, particularly at higher temperatures, and long-term stability affected by factors like grain growth and volatility of dopants. Potential solutions include statistical analysis of sensor arrays, surface functionalization, and novel nanostructures for enhanced performance and selectivity. The review also discusses the impact of ambient humidity on sensor performance and current strategies to mitigate it, such as composite materials with humidity shielding effects and surface functionalization with hydrophobic groups. The need for high operating temperatures, leading to higher power consumption, is addressed, along with possible solutions like advanced materials and new transduction principles to lower temperature requirements. The review concludes by highlighting the necessity for a multidisciplinary approach in future research, combining materials synthesis, device engineering, and data science to develop the next generation of WO₃ sensors with enhanced sensitivity, ultrafast response rates, and improved portability. The integration of machine learning and IoT connectivity is posited as a key driver for new applications in areas like personal exposure monitoring, wearable diagnostics, and smart city networks, underlining WO₃'s potential as a robust gas sensing material in future technological advancements.