By their very nature, agentic AI methods function with a big diploma of autonomy. This autonomy has actual worth: Cloud-based brokers can remediate incidents, optimize prices, or work together dynamically with customers. Nonetheless, when autonomy is unchecked or poorly outlined, you typically find yourself with unpredictable behaviors, inefficiency, and even compliance breaches. Let’s take a look at 3 ways enterprises can get extra enterprise worth out of agentic AI.
Preserve methods on a decent leash
A sensible method is to begin by designing clear, policy-driven constraints for the precise actions that brokers can take and beneath what circumstances. All three main clouds—AWS, Azure, and Google Cloud Platform—supply instruments reminiscent of id and entry administration (IAM), useful resource tagging, and coverage engines that allow you to prohibit an agent’s privileges and the scope of its actions.
Right here’s a fast instance: A significant SaaS supplier launches an AI agent that mechanically provisions new compute assets throughout demand spikes. Inside days, the agent’s unchecked autonomy causes giant, surprising cloud prices resulting from misinterpreted telemetry knowledge. The corporate responds by creating extra restrictive IAM roles in AWS, utilizing tagging to regulate the agent’s surroundings, and activating price range alerts and approval workflows for high-impact actions.