Enterprise Architecture Modernization Blueprint for Large-Scale IT A Unified Framework for Modernization in the Age of AI, Cloud, and Digital Acceleration

Large-scale IT modernization has become a strategic imperative for enterprises facing rising technical debt, fragmented legacy systems, regulatory pressure, and the accelerating adoption of cloud and AI technologies. Despite significant investment, modernization programs frequently fail due to siloed decision-making, inconsistent architectural practices, and the absence of a unified modernization blueprint. This paper introduces the Enterprise Architecture Modernization Blueprint (EAMB)-a structured, five-layer architectural model designed to guide modernization across infrastructure, applications, data, integration, and business capabilities. The paper integrates new original contributions including a Modernization Taxonomy, Modernization Decision Matrix, Legacy Complexity Index (LCI), Modernization Architecture Patterns, Modernization Anti-Patterns, and Future-of-Modernization Trends. These frameworks provide a repeatable, academically grounded, and practically applicable approach to modernization. Through diagram-rich models, a phased roadmap, and a case study from a large North American financial institution, the paper demonstrates how enterprise architecture can reduce modernization risk, accelerate delivery, and create a resilient digital foundation. The EAMB offers a scalable, citable framework for researchers and practitioners seeking to modernize legacy environments while enabling future-ready capabilities such as AI-driven decisioning, omnichannel experiences, and product-centric operating models. The primary original contribution of this paper is the formalization of large-scale IT modernization as an architecture-led discipline through the Enterprise Architecture Modernization Blueprint (EAMB). The paper introduces three original frameworks-the Legacy Complexity Index (LCI), the Modernization Taxonomy, and the Modernization Decision Matrix-which together provide a quantitative, repeatable method for assessing legacy complexity and objectively selecting modernization strategies. Unlike prior work that treats cloud migration, refactoring, or data modernization in isolation, this framework integrates business, data, application, integration, and operating-model dimensions into a unified decision system applicable across industries.