In a future where machine identities outnumber human ones significantly, the complexity of integrating AI agents into digital environments is underscored by the challenges in identity management, security, and interoperability. AI agents perform various tasks autonomously, such as shopping or managing sales interactions, but their deployment is hindered by issues in transitioning projects to production and the intricacies of agentic identity management. Security concerns are highlighted by AI models' vulnerability to exploitation, with the Open Web Application Security Project (OWASP) identifying key threats in AI systems. Effective identity management, leveraging standards like OAuth, is essential for secure interactions among AI agents, apps, and users while ensuring seamless and standardized communication protocols. As developers navigate these complexities, they face challenges in integrating multiple tools and maintaining secure, fine-grained access controls. The evolving landscape demands rethinking access control and prioritizing a user, developer, and agent-centric approach to foster innovation and scalability in AI systems.