As organizations race to unlock the productivity potential of large language models (LLMs) and agentic AI, many are also waking up to a familiar security problem: what happens when powerful new tools have too much freedom, too few safeguards, and far-reaching access to sensitive data?
From drafting code to automating customer service and synthesizing business insights, LLMs and autonomous AI agents are redefining how work gets done. But the same capabilities that make these tools indispensable — the ability to ingest, analyze, and generate human-like content — can quickly backfire if not governed with precision.
