Why migration debt is the hidden bottleneck in enterprise AI transformation For Global 2000 enterprises, the path to agentic AI is not blocked by a lack of ambition or investment — it is blocked by decades of accumulated technical debt sitting inside legacy systems. Millions of lines of proprietary SQL, ETL logic, and stored procedures embedded in platforms like Teradata and Netezza represent a conversion layer that must be addressed before any meaningful data migration and modernization can move forward. The scale of this challenge is larger than most project plans acknowledge: research shows that SQL dialect translation alone consumes between 20 and 40 percent of the total migration budget. Manual code conversion compounds the problem rather than solving it. Even subtle errors in a translated query — mishandled nested column aliases, imprecise data type conversions, or dialect-specific edge cases — can cascade into data quality failures that invalidate downstream AI model outputs.…