The current paper explores emerging technologies used in online exam supervision. Utilizing a qualitative approach through examining recent literature and detailed case studies of major testing service providers, the paper highlights advances in artificial intelligence (AI), machine learning (ML), deep learning (DL), biometric verification, and blockchain-based methods. These technologies collectively aim to enhance the integrity, fairness, and security of remote examinations by automating identity verification, detecting suspicious behaviors, and ensuring tamper-evident data management. Emerging technologies in online exam supervision have reached a high degree of sophistication and maturity, and online proctoring providers are constantly investing in innovation, regulatory compliance, and improving candidate experience. While these technologies can offer promising improvements in detecting and preventing cheating, they also present particular challenges. These challenges are related to resource requirements, scalability, and ethical considerations. A hybrid approach combining technological solutions with human oversight seems to be the most effective strategy currently. There is also a need for standardized frameworks along with recommendations and guidelines to address privacy concerns and ensure the ethical use of these technologies in online exam settings.