In recent years, the convergence of artificial intelligence and optical fiber sensor networks has revolutionized sensor technology, significantly enhancing performance, reliability, and efficiency. Optical fiber sensor networks, known for their high sensitivity, immunity to electromagnetic interference, and extensive bandwidth capacity, facilitate precise and distributed sensing of various physical parameters. These networks are pivotal in industries such as oil and gas, aerospace, environmental monitoring, biomedical diagnostics, and structural health monitoring. AI algorithms are useful in advancing these networks and providing capabilities beyond traditional systems. This study explores AI-driven methodologies that can augment the capabilities of optical fiber sensor networks across various domains. By transforming sensor data into actionable insights, AI can foster advancements in predictive analytics, operational efficiency, and decision-making. Embracing AI methodologies unlocks new potentials for innovation, sustainability, and reliability in sensor network applications, fostering smarter and more resilient technological solutions. Integrating these two domains will result in a transformative leap, enabling sophisticated monitoring, enhanced safety, and efficient management across industrial and environmental domains. This chapter encompasses the synergy of AI and sensor technology that will be useful in driving significant progress, paving the way for smarter, more sustainable solutions in the modern era.