As AI agents transition from passive responders to autonomous actors, they increasingly generate "agentic traffic" by autonomously initiating outbound API calls, often without direct human oversight. This shift introduces unique infrastructure challenges, as traditional systems primarily designed to monitor inbound traffic are ill-equipped to handle the complexities of autonomous outbound requests. The resulting risks include cost overruns, lack of observability, and security vulnerabilities. AI gateways emerge as a solution, providing a governance layer to manage outbound traffic, enforce runtime policies, and ensure safe agent behavior. These gateways complement existing API gateways by specifically catering to the needs of AI-driven autonomous traffic, offering capabilities such as credential shielding, rate limiting, multi-provider routing, and audit logging. As AI standards like MCP and A2A evolve, AI gateways are anticipated to play a crucial role in managing the growing complexity of AI infrastructure by enabling organizations to govern agentic behavior and mitigate associated risks effectively.