Agentic AI represents the next frontier in AI technology, enabling systems to carry out complex tasks through multistep workflows, guided by informed reasoning rather than merely providing answers. These systems integrate generative AI with external tools and resources, such as databases and APIs, to achieve specified objectives, necessitating specific enterprise resources and risk mitigation strategies. Key considerations for deploying agentic AI include orchestration through state machines to manage workflows, implementing guardrails for scope limitation and decision transparency, and ensuring knowledgeable teams are in place. Advanced language models like Cohere Command A are crucial for the multistep tool use required in these workflows. Tool architecture and evaluation processes must be clearly defined to ensure interoperability and performance, while extensive testing and resource planning are vital to move these systems into production. Organizations are advised to begin preparing foundational resources and skills to leverage agentic AI for automating tedious tasks, thereby allowing employees to focus on higher-value activities as the technology continues to mature.