Every enterprise runs on legacy systems. The question isn't whether to modernize -- it's whether you can afford to get it wrong.

Trillions of dollars in daily transactions still flow through COBOL mainframes. Hundreds of billions of lines of legacy code power the world's banks, insurers, hospitals, and supply chains. Yet the talent that understands these systems is retiring, maintenance costs are compounding, and competitors who act with precision are pulling ahead.

AI Edge: Transform & Maintain is the strategic playbook for technology and business leaders navigating this inflection point. Written by practitioners who have led complex modernization engagements across financial services, insurance, and healthcare, this book bridges the gap between boardroom strategy and engineering execution.

What you'll learn:

How to frame legacy modernization as a capital allocation decision your board will fund. Why AI-driven code comprehension has crossed from experimental to production-grade -- and what that means for your 2027 roadmap. How to choose between big bang, phased, and incremental transformation approaches based on your organization's risk tolerance. Why most modernization projects fail, and the specific patterns that predict failure before budgets are committed. How to build a 100-day executive action plan that delivers measurable outcomes.

Grounded in open-source data, real-world engagement patterns, and the authors' combined 50+ years in enterprise technology, AI Edge delivers frameworks, decision tools, and checklists designed to be used -- not just read. From portfolio assessment matrices to pre-mortem failure checklists, every chapter equips you to act.

Whether you're a CTO evaluating a multi-year transformation, a CIO defending your modernization budget, or a business leader trying to understand what your technology team is telling you, this book gives you the language, the evidence, and the frameworks to lead with confidence.

Includes: 20 data tables and decision frameworks, 3 practical appendices (LegacyCodeBench benchmark data, Uniview software accelerator case studies, and a complete transformation readiness checklist), and an About the Authors section profiling the team behind Hexaview's "Understanding Before Modernization" methodology.

This is optimized for Amazon's format -- the bold opening hooks scanners, the "What you'll learn" section targets keyword searches, and the closing speaks directly to each buyer persona (CTO, CIO, business leader). It avoids bullet points since Amazon renders those poorly, and uses bold text which Amazon's detail page does support.

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• Business & InvestingIndustries & ProfessionsHigh-Tech

• Publication Date: April 3, 2026
• Text-to-Speech: Disabled
• Lending: Disabled
• Print Length: 257 Pages
• File Size: 13 KB