This perspective provides an overview of the sensing systems that combine FBG and AI technologies in medicine, focusing on their working principle, potentials, and challenges. It also explores the open research directions for encouraging further investigations in this field. Fully automatic fabrication of fibre Bragg gratings using an AI-powered Wenbo Liu, Guiyuan Cao, Zian Liu, Hongyang Chen, Hao Zhang, Renjie Li, Keng-Te Lin, Han Lin, Baohua Jia Fully automatic fabrication of fibre Bragg gratings using an AI-powered femtosecond laser inscription system Wenbo Liu#. Among many solutions, fiber Bragg grating (FBG) sensors have gained significant acceptance in the medical field, due to their good static and dynamic performance, small dimensions, biocompatibility and immunity to electromagnetic interferences. The integration of artificial intelligence (AI) with. This paper presents a comprehensive review of AI-enhanced OFS technologies, encompassing both localized sensors such as fiber Bragg gratings (FBG), Fabry–Perot (FP) interferometers, and Mach–Zehnder interferometers (MZI), and distributed sensing systems based on Rayleigh, Brillouin, and Raman. The ML models in the legend are polynomial regression (PR), support vector regression (SVR), decision tree regression (DTR), k-nearest neighbors (KNN) and extreme gradient boosting (XGB). This is achieved by creating a periodic variation in the refractive index of the fiber core, which generates a. In the vast realm of optical fiber sensing, where precision and innovation converge, Fiber Bragg Gratings (FBGs) stand as luminaries, casting their influence across myriad applications. These microscopic structures within optical fibers have become the bedrock of cutting-edge sensor.