Mainframe Modernization using GenAI
Large-scale modernization of legacy mainframe systems is not only a technical challenge; it is a societal one. Many of the systems being transformed today underpin essential services across banking, trading, account servicing, operations, and other industries that citizens and institutions rely on every day. When modernization efforts fail during the transitional period, while legacy and cloud environments must operate together, the consequences can extend beyond project delays to service disruption, financial instability, reduced public trust, and increased operational risk. This article argues that the transition phase should be treated as a critical public-interest concern rather than merely an engineering bridge between old and new platforms. Drawing on evidence from two multiyear modernization programs, the study presents a framework for using AI-derived code intelligence to make transition planning more transparent, measurable, and resilient. Instead of focusing only on target-state efficiency, the framework prioritizes continuity of service, reduction of incidents, protection of sensitive operations, and safer sequencing of change. The paper also proposes a practical evaluation approach for assessing transitional health through indicators such as stability, recovery, compliance with operational windows, and containment of risk. By reframing modernization as a socio-technical responsibility, this work highlights how better transition design can help organizations protect customers, strengthen industry reliability, and support broader societal confidence in critical digital infrastructure. His work on https://solutionshub.epam.com/blog/post/cobol-code is also available.
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- Starts 18 April 2026 01:00 AM UTC
- Ends 07 May 2026 07:00 PM UTC
- No Admission Charge
Speakers
Ankur Kalohia of EPAM Systems
Biography:
Ankur Kalohia is a technology leader, researcher, and delivery executive with more than 20 years of experience leading large-scale digital transformation, modernization, and engineering programs across financial services and other enterprise domains. He currently serves as Director, Global Delivery Management at EPAM Systems, where he leads complex portfolios spanning legacy modernization, cloud transformation, AI-augmented software delivery, and large distributed engineering organizations.
His work focuses on the responsible application of artificial intelligence to software engineering challenges, particularly in mainframe modernization, reverse engineering, transitional-state architecture, and hybrid mainframe-to-cloud transformation. His research explores how AI-derived code intelligence can improve system understanding, reduce modernization risk, and strengthen resilience in critical digital infrastructure that supports businesses, institutions, and society at large.
Ankur has led multimillion-dollar portfolios, guided global teams across multiple geographies, and contributed thought leadership through industry publications and research papers on generative AI, legacy transformation, and modernization strategy. His interests lie at the intersection of technology innovation, operational reliability, and the broader social implications of deploying AI in enterprise systems.
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Agenda
Presentation:
45 minutes - 5.30 pm onwards (eastern time zone)
Q&A:
15 minutes - 6:15 pm to 6:30pm (eastern time zone)