Application migration: What a leading bank achieved with agentic AI

Summary

Sector: Banking

The challenge: As part of a major technology modernization program, a leading international bank wanted to accelerate the migration of applications from legacy technologies to its strategic technology stack. Existing migration activities required significant manual effort across code refactoring, translation and validation. This slowed progress towards reducing technical debt, delaying the benefits of the target architecture. The bank was looking for a faster, scalable approach that would maintain quality and governance while helping teams modernize applications more efficiently.

The solution: The bank recognized an opportunity to use AI to support this ambition and introduced an AI-powered capabilities across the migration lifecycle. Delivered through a small, but impactful AI Product Team of 3 (AI Product Owner, AI Engineer and Domain Expert), which focused on product ownership, domain expertise and AI engineering. The solution combined AI-enabled delivery with human oversight to accelerate application modernization at scale.

Key results:

Over 70% migration accuracy across initial use cases
Up to 8 hours of manual effort saved per migration
Increase in structured and scalable migration workflows
Strong foundations for future AI-enabled modernization initiatives

70% migration accuracy
8 hours manual effort saved per migration
3 AI Product Team members
1 scalable modernization model

The challenge

Accelerating modernization across a complex technology landscape

As a major international bank, our client was pursuing a large-scale technology modernization program designed to migrate applications from legacy technologies to a strategic technology stack. The objective was to create a more efficient technology landscape, reduce technical debt, and benefit from modern platforms across the organization. Like many global banks, our client faced the challenge of legacy application transformation while maintaining the security and reliability required for critical banking services.

Delivering this transformation at scale required significant effort across code refactoring, translation and validation activities. Application migrations were often requiring engineering teams to spend several hours analyzing applications, identifying required changes and validating migration outputs. As a result, the bank was looking for ways to accelerate migration activity while maintaining quality and transparency with appropriate governance throughout the process.

Our client wanted an approach that would enable faster delivery and support adoption across teams. It was important to create a scalable foundation for future transformation initiatives. The bank partnered with Wavestone to explore how AI driven application migration could simplify and accelerate application migrations while delivering measurable business value.

people surrounding a screen with blue network signals

The solution

Combining AI-powered delivery with human expertise

To accelerate application modernization across multiple migration paths, the bank introduced AI driven application migration capabilities with support from Wavestone to make application migrations faster and increase the bank’s ability to scale migration activity.

The work began with an assessment of applications and code repositories to identify migration requirements and opportunities for automation.

Two solutions were developed to support different audiences. Claude Code Plugins helped engineering teams address specific migration scenarios, while Code Transformation Services provided an AI-powered platform that automated migration activities and made them more accessible to application owners and business stakeholders. Together, they created a scalable approach to modernization across the bank.

Engineers remained responsible for reviewing and approving all proposed changes before implementation. This enabled the bank to benefit from AI while maintaining the security and reliability required for business-critical applications.

Adoption was supported through showcases and demonstrations that helped build awareness and encourage wider use across the organization.

Small teams, greater impact

A multidisciplinary team of three specialists accelerated modernization while maintaining governance and quality standards.

One of the program’s defining features was its delivery model. Rather than relying on a large delivery structure, the bank adopted a focused AI Product Team comprising an AI Product Owner, AI Engineers and a Domain Expert, supported by specialized AI tooling and custom-built accelerators. This brought business priorities, product ownership and technical expertise together within a single team.

Th bank now uses this model to develop AI-powered capabilities. It continues to demonstrate how focused teams can accelerate delivery while maintaining strong governance and human oversight.

Successful AI adoption is more than technology alone. When empowered with the right tools and a clear product vision, small multidisciplinary teams can move quickly and maintain close alignment with stakeholders. It ensures tangible outcomes in short timeframes.

Gonzalo Cabrera Gonzalo, Associate Partner, Wavestone

The results

Creating a scalable foundation for faster transformation

The bank established a more streamlined and scalable approach to application migration. AI-supported workflows helped accelerate code conversion activities while maintaining governance and quality controls throughout the process.

The program accelerated enterprise modernization, realizing benefits of 70% migration accuracy across initial migration use cases, while reducing manual migration effort by up to 8 hours per migration.

Beyond efficiency gains, the program demonstrated how a focused AI Product Team model can achieve significant outcomes at pace. By combining specialist expertise with AI-powered delivery, the bank accelerated its modernization agenda and created momentum across wider technology initiatives.

At the same time, the bank established a scalable foundation for future AI-enabled transformation and application modernization initiatives. AI-assisted migration capabilities improved consistency and quality while ensuring engineering teams retained full responsibility for reviewing and approving all proposed changes. The approach also created a pathway to reduce technical debt and long-term technology costs through the migration and eventual retirement of legacy platforms.

For this program, that meant bringing together product ownership, domain expertise, engineering excellence and human oversight to create a solution that goes beyond experimentation and focuses on business outcomes. The result is a practical example of how organizations can use AI to accelerate enterprise modernization, empower teams and deliver lasting value.