Application migrations are often viewed as a necessary evil, but they can be risky, time-consuming, and costly. According to a report, as much as 70% of software used at Fortune 5000 companies was developed over 20 years ago, making modernization a pressing concern. Fortunately, generative AI (genAI) tools can ease and accelerate many aspects of the migration process, making it more efficient and cost-effective.

There are several approaches to application modernization, summed up by the seven Rs of cloud migrations: retiring, replacing, relocating, re-platforming, reusing, refactoring, and rebuilding. GenAI can simplify and accelerate many of these processes, reducing the technical debt and costs associated with migration. For instance, code translators can help accelerate the process, reduce costs, or improve quality, especially in cases where major changes are needed.

One of the key benefits of genAI is its ability to simplify development workflows, including generating starter templates and conversion scripts that help developers maintain logic consistency while adapting to new paradigms. According to McKinsey, genAI can eliminate much of the manual work in app modernizations, leading to a 40% to 50% acceleration in timelines and a 40% reduction in costs.

When planning an application migration, it's essential to understand the workflow and change requirements. This involves reviewing existing documentation, interviewing subject matter experts, and developing a checklist of essential requirements. GenAI tools can aid in writing requirements and agile user stories, making it easier to communicate with end users and alleviate their concerns during the migration.

Another critical step is analyzing the architecture for dependencies, including performing a code review, diagraming the runtime infrastructure, conducting a data discovery, and analyzing log files or other observability artifacts. GenAI can simplify and accelerate this process, helping developers and architects answer questions quickly regarding architectural and deployment options for apps targeted for migration.

Reviewing someone else's code can be a daunting task, but genAI tools like OpenAI Codex and GitHub Copilot can accelerate tasks such as translating code into descriptions, extracting business rules, diagraming function call sequences, identifying data validations, and separating testing functions. This can help developers understand legacy code and application logic, particularly when knowledge has been lost due to time or engineer attrition.

GenAI can also aid in translating utility code to other languages, especially when reviewing an app for migration. Code translators can automate parts of this transition, optimizing performance and identifying errors during migration. Additionally, genAI can generate test cases on legacy code, enabling a test-driven migration approach that validates functional parity throughout the migration process.

Planning the data migration is another critical aspect of the process. GenAI can address both of the major pain points associated with app migration: extensive planning to account for various dependencies, and repetitive data migration with tedious checks to prevent data loss or corruption. AI can understand the requisite steps and trigger pre-built governed automations to execute the data migration, leveraging traditional automation technologies to mitigate the risks associated with generative AI touching potentially sensitive data.

However, experts warn that development teams should conduct detailed code and security reviews as part of testing, even if the application is undergoing minimal functional changes. The adoption of genAI tools in software development is driving unprecedented developer productivity, but it's essential to automate key manual application security controls, like security reviews or threat modeling, to mitigate potential risks.

In conclusion, genAI tools can significantly simplify and accelerate application migrations, making it easier to modernize legacy code and applications. By understanding the requirements, communicating with end users, selecting appropriate tools to aid migration, and developing a thorough testing program, enterprises can accelerate, reduce costs, and minimize risks associated with app migrations.