Using Generative AI on AWS to Accelerate Application Modernization
For many enterprises, the most urgent generative AI opportunity is not a chatbot. It is the hard, expensive work of modernizing legacy applications.
Core systems often still run critical business processes, but they can also slow innovation, increase operating costs and make it harder to respond to changing customer expectations, regulatory demands and growth opportunities. Traditional modernization approaches have frequently struggled to deliver predictable results. They can run over budget, extend timelines and depend on scarce talent that understands both legacy and modern technology stacks.
This is where generative AI can create practical, measurable value quickly.
Publicis Sapient helps enterprises use generative AI on AWS to accelerate application modernization with a business-led, engineering-grounded approach. By combining Amazon Bedrock, Amazon CodeWhisperer and broader AWS capabilities with Sapient Slingshot, contextual knowledge, prompt libraries and human-in-the-loop delivery, we help organizations modernize faster, reduce defects, lower costs and improve long-term maintainability.
A practical early Gen AI investment
Many organizations are under pressure to prove that generative AI can move beyond experimentation and deliver enterprise value. Application modernization is one of the clearest places to do that.
Unlike more speculative use cases, modernization addresses problems leaders already understand well: rising technical debt, slow release cycles, aging platforms, expensive maintenance, cloud migration barriers and limited access to legacy skills. When generative AI is applied to these challenges in a disciplined way, it can help transform a large, complex migration into a more structured, traceable and efficient program.
Modernization becomes more than a technology exercise. It becomes a route to greater agility, improved software quality and a stronger foundation for future digital growth.
How Publicis Sapient applies Gen AI to modernization on AWS
Our approach uses large language models with human intervention to amplify engineering productivity across the modernization lifecycle.
We combine three critical inputs:
- **Code** to analyze, understand and convert
- **Context** to improve understanding of business logic, intent and target outcomes
- **Prompts** through pre-built libraries that help guide the models toward repeatable, high-value outputs
This combination allows teams to work more effectively across some of the most difficult parts of legacy transformation.
1. Understanding legacy code at scale
One of the biggest modernization challenges is simply understanding what legacy applications do. Documentation is often incomplete, outdated or missing altogether. Business logic may be buried across millions of lines of code.
Publicis Sapient uses generative AI, contextual knowledge and prompt libraries to help deconstruct legacy applications and make them intelligible. This can accelerate understanding of existing functionality and create a clearer baseline for modernization planning.
2. Generating feature summaries and specifications
Modernization programs often stall when teams cannot translate old code into clear functional understanding. Our AI-enabled approach helps generate feature summaries and functional specifications from existing systems, improving traceability between current-state logic and future-state design.
This matters because modernization is not just about rewriting code. It is about preserving what the business needs, identifying what should change and creating a trustworthy path from old architecture to new.
3. Creating test cases and improving validation
Testing is one of the most time-consuming and risk-sensitive parts of modernization. Publicis Sapient uses generative AI to generate test cases, unit tests and automation test scripts that help expand coverage, streamline validation and reduce manual effort.
By strengthening test design early, organizations can reduce downstream rework and move into refactoring and migration with greater confidence.
4. Supporting refactoring and target-state generation
Once teams understand the current state, generative AI can help accelerate refactoring and support the creation of target-state documentation and transformed architectures. Publicis Sapient applies AI to assist with code transition, optimized processes and modernization toward more scalable architectures on AWS.
This helps teams move away from brittle, high-maintenance legacy environments and toward platforms designed for agility, resilience and future change.
The role of Sapient Slingshot
Sapient Slingshot is a key differentiator in this approach. It is Publicis Sapient’s AI-powered platform for legacy modernization and software development lifecycle acceleration.
On AWS, Sapient Slingshot helps modernize legacy systems by turning existing code into verified specifications and generating modern software with full traceability. That traceability is critical for enterprise modernization, especially when organizations need to preserve important business logic, improve governance and give stakeholders confidence in the migration path.
In practical terms, this means modernization is not treated as a black box. Teams can connect current-state understanding, generated specifications, refactored outputs and testing assets in a way that supports quality, control and maintainability.
Human-in-the-loop delivery for enterprise trust
Generative AI can accelerate modernization, but enterprise transformation still requires experienced human judgment.
Publicis Sapient’s model is explicitly human-in-the-loop. Our engineers, architects and domain specialists guide context, validate outputs, refine prompts, assess tradeoffs and ensure the modernization effort aligns with business priorities, technical constraints and governance requirements.
This balance matters. Enterprises need the speed benefits of AI without sacrificing quality, accountability or architectural integrity. Human intervention helps turn AI-generated outputs into production-ready modernization assets.
Why AWS matters
AWS provides the foundation for this work at enterprise scale. Publicis Sapient uses AWS services such as Amazon Bedrock and Amazon CodeWhisperer as core enablers for generative AI-powered delivery, while broader AWS capabilities support secure, scalable modernization programs.
For clients, that means modernization and AI adoption do not have to be separate agendas. Organizations can modernize legacy applications while building on a cloud environment designed for scale, governance and future innovation.
Publicis Sapient’s partnership with AWS strengthens this approach with deep cloud, migration, engineering and security experience, along with proven methods for moving from experimentation to production.
Business outcomes that matter
Our application modernization approach is designed to improve both IT and business performance. Based on analysis across more than 100 end-to-end experiments using our generative AI modernization accelerators in combination with internal tools, models and AWS solutions, Publicis Sapient has seen the potential for:
- **More than 50% reduction in modernization costs**
- **50% fewer defects, with significantly expanded coverage of requirements and test cases**
- **50% increase in migration speed**
Actual results vary by client context, but the message is clear: when generative AI is applied to modernization in a structured way, the impact can be significant.
In one modernization effort for a leading benefits provider, Publicis Sapient designed a process for cloud developers to use private models and LLMs to deconstruct legacy mainframe applications. The effort helped achieve a migration that was three times faster, improved traceability through functional specifications and made the resulting code easier to maintain and enhance in a modern technology stack.
From stalled programs to scalable transformation
Many AI initiatives stall because they lack a clear path from prototype to production. Publicis Sapient addresses that challenge through its SPEED framework, which brings together Strategy, Product, Experience, Engineering, and Data & AI to align modernization work to business outcomes from the start.
For organizations beginning their journey, the AWS Gen AI Fast Track offers a structured way to assess readiness, prioritize use cases, build a prototype and define a roadmap for broader implementation. That can be especially valuable for CIOs, CTOs and engineering leaders who want to start with a use case that delivers measurable results quickly.
Modernization as a smarter first move in Gen AI
Enterprises do not need to treat generative AI as a separate innovation track. For many, one of the smartest first moves is to apply it to a problem they already need to solve: legacy transformation.
With Publicis Sapient and AWS, generative AI can help turn application modernization into a faster, more reliable and more economically compelling journey. By combining cloud-native foundations, AI-powered accelerators, contextual understanding and expert human delivery, we help organizations reduce technical debt and create modern software platforms that are easier to change, easier to maintain and better suited to the future.
If your business needs measurable IT and operational value from generative AI now, modernization may be the right place to start.