The web is evolving with the introduction of AI agents, which act as intermediaries between humans and software, utilizing workflows and large language models to perform tasks autonomously or semi-autonomously. These agents bring new challenges in authentication and authorization, requiring protocols like Agent-to-Agent (A2A) and Model Context Protocol (MCP) to standardize secure communication. However, authorization remains a critical issue, necessitating strategies such as the principle of least privilege to prevent security risks like data exfiltration and unauthorized actions. Operational concerns such as auditing, rate limiting, monitoring, and resilience must also be addressed to ensure robust and secure agent interactions. Organizations are encouraged to assess their current use of AI agents, understand the tasks they perform, and integrate them into existing security models to prepare for a future where humans, software, and agents collaborate effectively.