Agentic workflow automation: governing AI agents inside workflows

AI agents do not operate like traditional security and IT playbooks, as they dynamically form intent, select tools, and execute actions, leading to potential governance challenges. In response to these challenges, organizations are tasked with accelerating AI adoption while ensuring strict governance, creating pressure on security, IT, and compliance teams to manage autonomous agents without compromising control and oversight. Agentic workflow automation emerges as a solution by integrating deterministic workflows, agentic reasoning, and human-in-the-loop processes within a unified governance framework, thereby coordinating specialized agents, managing state, enforcing checkpoints, and ensuring auditability. This approach differentiates agentic workflows from standalone AI agents and deterministic automation, emphasizing the importance of an orchestration layer to tie these elements together and maintain a consistent governance model. Practical applications of agentic workflows include streamlining security operations, automating ticket triage, and facilitating continuous compliance evidence collection, all of which require a balance between automated processes and human oversight to effectively manage both routine and high-impact tasks.

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