AI agents, often built on large language models, are emerging digital assistants designed to execute complex tasks by mimicking human behaviors, raising both opportunities and challenges for businesses, especially regarding fraud prevention. Despite their potential, current AI agents face significant limitations such as high costs, security vulnerabilities, and inefficiencies in handling complex tasks, leading to a hesitance in their widespread adoption for fraud. Contrarily, the more immediate threat to companies comes from sophisticated bots that impersonate humans and carry out various malicious activities, making up a substantial portion of internet traffic and causing significant financial damages. Businesses need robust tools to distinguish between human users and these bots, as traditional bots are typically more efficient and cheaper for fraudsters to deploy. As AI agents continue to develop, their eventual integration into the web could transform digital interactions, necessitating improved detection and differentiation from traditional bots and humans.