Busting process ghosts - how to keep enterprise AI from seeing processes that don't exist
Companies are investing heavily in the race to become agentic organizations. But as they strive to implement end-to-end, AI-driven automation, most are running into the same obstacle - the chasm between theoretical business processes and the unique processes that make up their own operational reality.
Every company knows how its processes work on paper, based on the information that was available the last time they were modeled. And every Large Language Model (LLM) trained on the public internet knows how business processes work in general.
But what AI agents need - if they're to drive automation successfully - is to understand how end-to-end processes work right now, and how they should work in the future, for a specific business. For example, one of the world's largest pharmaceutical companies is speeding up clinical operations using AI agents grounded in the granular knowledge of its unique and highly regulated clinical trials process.
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