Reimagining Brownfield Application Modernization: Combining Deterministic Data and Agentic AI for Technical Debt Reduction
Reimagining Brownfield Application Modernization: Combining Deterministic Data and Agentic AI for Technical Debt Reduction
Brownfield application modernization must address growing technical debt—now a major barrier to stability, security, AI adoption, and ROI. IBM’s approach combines deterministic structural analysis with agentic AI to identify dead, duplicate, and low-value code, often reducing modernization scope by about 30% and lowering cost, risk, and timelines. Deterministic data provides accurate system baselines, dependency visibility, and validation, while AI automates refactoring, prioritizes debt hotspots, and resolves errors at scale. By embedding technical debt reduction directly into migration and cloud transformation, organizations can accelerate delivery, improve software quality, and achieve higher returns without separate remediation programs.
