Home → Blog → AI Modernization Sprints: Update your Software Without a Full Rewrite
To remain competitive on the market, companies need to stay tech-forward, placing technology at the core of their growth strategy. However, many large organizations still rely on legacy systems and outdated programming languages, which act as a heavy anchor, retraining innovation, limiting scalability, and draining resources.
The good news is that modernization doesn’t require a full system rewrite. Companies can improve their software through AI modernization sprints to reduce manual tasks, identify architectural bottlenecks and legacy code, and optimize software performance.
Reasons to modernize your legacy software with AI
According to Mckinsey research, 71 percent of the impact from business transformations depends on technology. Technology is the core of business productivity, enabling innovation, market entry, and the launch of new features.
As technologies are advancing at lightning speed, the more companies rely on outdated technology, the greater the total cost of recovery and modernization becomes. Here are the main reasons to start modernizing without a full rewrite.
Pay back the technical debt
Since most companies do not track the true cost of maintaining their software (which includes not only direct costs but also indirect costs such as downtime, data breaches, and delayed launches), the total amount of their tech debt can be shocking.
Here’s a great example of how a Fortune 500 company’s digital ecosystem audit revealed over $67M in accumulated technical debt. Moreover, building a modern platform from scratch would cost 2 times less than maintaining an old one and reduce operational costs by 52%.
Companies that delay cost-effective modernization compound their technical debt, multiply the effort required for modernization, and slow the growth of their business.
Update the legacy code and migrate to new technologies
Generative AI accelerates AI transformation for enterprises by automating tasks such as code translation, refactoring, testing, and documentation.
For example, Airbnb completed a large-scale code migration using frontier models and robust automation. The company migrated nearly 3,500 React component test files from Enzyme to React Testing Library and completed the migration in just six months, compared to an estimated 1.5 years if done manually.
Improve security and increase reliability
According to the Redhat software modernization report, security, reliability, and scalability are the primary reasons organizations choose to modernize their software. And this is for good reason: 58% of organizations modernizing their software have experienced rapid improvements in system security.
As legacy systems often lack security documentation, AI tools can identify unsafe libraries, hard-coded credentials, outdated software, and high-risk third-party tools that would otherwise remain unnoticed.
How to modernize your software and reduce rewrite costs with AI
AI is becoming an integral part of software modernization with around 78% of organizations using or planning to use AI to modernize their applications. Here’s how companies are using AI to modernize their software.
Simplify complex migration tasks with the help of generative AI agents
The deployment of generative AI agents helps automate modernization and reduce operational costs. Agents with specific roles and expertise can control the quality of the modernization process, analyze data, and run test cases under human oversight.
For example, a banking company deployed generative AI agents to modernize 20,000 lines of code and migrate components to another language. Initially, this migration was estimated to take around 800 hours; however, with the help of generative AI agents, the company reduced that estimate by 40 percent.
Recognize patterns and detect architectural problems during the system mapping process
One of the benefits of generative AI is that it understands code at a semantic level: how it works, how components interact, and what business logic it supports, not just the syntax.
Generative AI can create a map of module relationships, architectural and data flows, and business logic, and continuously update it. Also, it can detect architectural problems during your modernization process, find any architectural flaws before they become critical, and suggest the most effective refactoring strategies.
Help you understand the code you already have
The true advantage of using generative AI during software modernization is not just to feed legacy code into a generative AI tool and rewrite it, but to understand what and why you need to do to generate more business value.
Before using generative AI, companies need to understand what they need to improve to generate more business value, and then modernize the processes that will help them achieve it.
Step-By-Step AI Modernization Sprints
Before getting into AI modernization, companies have to prepare. Here is a step-by-step guide that will help organizations not just rewrite their legacy systems, but to improve the core business processes.
Analyze your current architecture
Start with a comprehensive analysis of your current architecture and answer the following questions:
- How do the components in the system correlate with each other?
- Is your system integrated with other resources?
- How qualitative is your data?
- Are there any flaws in the system performance?
- What do you need to modernize first to improve your business performance?
Choose a modernization strategy
There are several approaches to software modernization:
- Incorporating generative AI, AI agents, and reasoning models to reduce technical debt and improve tech processes
- Modernizing the digital core by rewriting the database and modernizing core features
- Identifying business processes that have to be changed and then incorporating AI to modernize them gradually
- Creating APIs for migrating data from the old software to the new one
- Choosing a hybrid approach and modernizing the core details while keeping the core functionality intact
Break down modernization process
Breaking down the modernization process into smaller steps leads to better results. Rather than using generative AI to improve multiple complex tasks, we recommend focusing on one specific task at a time, tracking results, and then scaling up.
Redhat recommends using 6Rs approach:
- Retire: Get rid of applications that no longer deliver business value.
- Retain : Keep critical applications unchanged until modernization becomes necessary.
- Rehost : Move applications to the cloud with minimal or no code changes (“lift and shift”).
- Replatform : Optimize applications for the cloud while keeping the core code largely unchanged.
- Refactor : Redesign applications to be cloud-native by restructuring code
- Repurchase: Replace on-premise or licensed software with a SaaS solution
Add modern layers around legacy systems
AI enables companies to introduce modern capabilities, such as APIs, monitoring and security layers, and cloud or microservice components around existing legacy systems, while keeping the core system operational. This approach improves flexibility, visibility, and security without disrupting critical business processes.
Real-life use cases of AI modernization sprints
Let’s review how AI helped companies modernize their architecture without a full rewrite.
- Amazon uses generative AI assistants to upgrade its applications, which helps them reduce time for an upgrade from 50 developer days to a few hours. In addition, it helped them improve security and reduce infrastructure costs, resulting in around US$260 million in efficiency gains.
- According to McKinsey, generative AI eliminates manual work, resulting in 40 to 50 percent reduction in time needed for tech modernization and a 40 percent reduction of the tech debt.
- With AI-driven insights, a Fortune-100 banking organization reduced modernization costs by more than 3x compared to manual decomposition.
Using generative AI in a phased modernization strategy is one of the best ways to pay down tech debt, improve system performance, save resources, and reduce manual work.
