Modernizing legacy applications has become one of the most persistent challenges in enterprise IT. Large organizations—banks with decades-old COBOL systems, utilities operating brittle billing engines, or government agencies tied to mainframe workflows—often run software with tens of thousands of interdependent modules. These systems power mission-critical business operations, yet their complexity, undocumented behaviors, and operational fragility make modernization slow, risky, and heavily dependent on scarce human expertise. This is the context in which agentic AI enters—not to replace engineers, but to reduce human bottlenecks, accelerate safe modernization decisions, and provide continuous guardrails throughout the transformation journey.