Enterprise Automation is Missing Context. Here's How Agentic AI Fixes It

Enterprises are investing more in automation than ever before, yet frustration grows. In 2024 alone, companies spent $365 billion on AI. Despite this, MIT research shows that 95% of generative AI pilots failed to deliver the promised value. Study reports that 99% of companies have yet to reach AI maturity, despite massive investments. The problem isn’t technology itself, it’s the way it’s deployed. Most enterprise automation was designed to execute discrete tasks: fill a form, route a ticket, or process an invoice. It performs these tasks well, but only in isolation and under predictable conditions. Real business operations, however, are messy. They are multi-step, cross multiple systems, and rarely follow a linear path. Whenever automation encounters a scenario it wasn’t explicitly programmed for, it stops. Humans step in to fix the issues, and promised efficiency never fully materializes. The root cause is clear: missing context. What “Missing Context” Means Despite widespread adopti