Optical Fiber Sensing (OFS) technology is termed a highly sensitive and reliable method for monitoring physical conditions, such as temperature, humidity, pressure, and strain, across myriad and often difficult environments. Comprehended for its durability and low power consumption, OFS has evolved as an indispensable component in applications ranging from structural health monitoring to environmental and industrial sensing. Artificial Intelligence (AI) integration into OFS systems has recently elevated its capabilities. It facilitates improved data processing, decision-making, anomaly detection, knowledge extraction, and predictive insights, qualifying for real-time and adaptive responses in crucial situations. Nevertheless, the OFS and AI augmentation are prompting cybersecurity and ethical challenges. As AI-integrated OFS systems are implanted across sensitive sectors that range from healthcare to national security and critical infrastructure, the risks associated with data security and privacy, unauthorized access, and bias in AI models turn out to be increasingly important. This study thoroughly explores the cybersecurity vulnerabilities and ethical considerations associated with AI-driven OFS technology. This work highlights the significance of robust cybersecurity protocols and ethical standards to unlock AI’s full potential in OFS applications responsibly.