Modernizing applications with AI comes naturally to companies striving to innovate, optimize processes, adopt safe practices, and speed up the software development cycle.
In the complex process of retiring and modernizing legacy systems, relying on artificial intelligence can be an excellent way to achieve these goals.
In this article, we’ve put together the top five advantages that modernizing AI applications can bring to a company. Read on!
What is application modernization?
Take “modernizing” literally: migrating an obsolete process to a newer one. When it comes to software, this means transitioning a monolithic application from a legacy system to microservices in the cloud.
In this way, modernization speeds up the delivery of new features, reduces technical debt, promotes scalability, improves performance, and offers other advantages that enhance the software development cycle.
But how can artificial intelligence help?
The tool significantly supports this challenging and complex process, facilitating modernization while maintaining application quality and meeting the necessary security requirements.
In short, AI can have a direct impact on the development cycle by:
- automating processes
- analyzing and identifying problems
- recommending improvements
- promoting innovation
- guiding migrations to new architectures and languages.
StackSpot is critical to modernization
StackSpot promotes the modernization of legacy systems, including their applications, with a robust platform that centralizes standards and offers a contextualized artificial intelligence tool.
The AI context comes from the potential of Retrieval Augmentation Generation (RAG), which combines the retrieval of knowledge sources, such as StackSpot AI’s Knowledge Sources, with high-quality AI model resources, resulting in richer, more comprehensive, and more relevant suggestions.
StackSpot AI is an AI code assistant that uses your context in software development, suggesting more assertive and higher-quality code than generic AI tools.
Want to know how AI-driven application modernization works in practice? Watch the video to see StackSpot in action.
How do I choose an AI tool?
There are now many artificial intelligence options, but the difference lies in one word: context.
Contextualized AI tools, fed with standards and security practices, offer more assertive codes suited to the company’s reality —unlike generic tools that offer unspecific solutions.
To choose the best artificial intelligence tool for coding, careful evaluation is key, including:
- integrations
- features
- the AI’s ability to learn
- speed and performance
- security and privacy plan.
After these requirements have been analyzed, considering that AI is contextualized, this is a good place to start modernizing your applications.
The advantages of AI-driven application modernization
Artificial intelligence brings multiple advantages to software development, especially in a complex and laborious process such as the modernization of legacy systems.
Below, we’ll discuss the top advantages of modernizing applications with AI.
1 – Accelerates the software development cycle
A survey by McKinsey confirmed a widespread assumption: AIs speed up the development cycle by up to 45%.
For example, a developer won’t need to work on all the processes to modernize an application. Contextualized AI, such as StackSpot AI, automates the generation of code snippets, offers advanced recommendations, and simplifies daily coding tasks.
Therefore, combining the AI tool with modern applications speeds up the development cycle, improves the quality and scalability of the applications, and eliminates the legacy system and its complications.
While modernizing legacy systems, it is essential to have an agile and efficient cycle to develop the updated application that will replace the legacy.
2 – Reduces cognitive load and improves the developer’s experience
One great thing about leveraging artificial intelligence in development is that it frees developers from manual and repetitive tasks.
Supported by AI, codes get ready faster, and developers’ time is optimized, allowing them to focus on more strategic and complex tasks. This results in more agile, innovative development that meets market standards.
In addition, the use of AI impacts developers’ experiences. Through assertive suggestions and task automation, AI reduces cognitive load, makes devs’ more productive and less prone to errors, thus improving their experience and satisfaction.
3 – Reduces technical debt
Another McKinsey study shows that technical debt is a direct consequence of obsolete systems and can represent 20% to 40% of a company’s total technological assets.
That said, legacy systems face technical debt points — such as older languages known by few available professionals or poorly documented changes that complicate system maintenance.
Less technical debt means more time to identify opportunities for improvement and work on the modernized system, increasing the efficiency and the overall quality of software development.
4 – Makes applications more secure and reliable
Artificial intelligence can ease tasks directly linked to application security, such as code review and testing.
AI can also work directly with software security analysis. StackSpot AI has been proven to efficiently detect vulnerabilities and correct code in various languages.
Leveraging context, AI offers customized parameters during remediation, such as the language itself, structure, standards, and security policies.
Want to improve your legacy modernization process? Read the article on legacy modernization challenges solved by contextualized AI.
5 – Facilitates migration
Finally, AI is a facilitating tool that impacts many aspects of development — from abandoning legacy and making room for the cloud to reviewing monoliths and preferring microservices.
Learn how AI works in the migration process:
Monoliths to microservices
When migrating from monoliths to microservices, AI can analyze the monolith and identify applications that need to be updated. Then, AI makes suggestions for microservices and generates the codes and APIs required to implement this distributed architecture.
AI can thus automate complex phases and identify potential risks for migration, speeding up and preserving this complex process.
Legacy in the cloud
A key AI feature is the ability to analyze, identify, and suggest improvements to cloud architectures.
The result is shorter migration time and lower costs, allowing for greater efficiency, security, and alignment with good software development practices.
Conclusion
Modernizing applications with AI is a step towards leaving the legacy system behind. Artificial intelligence supports this process, enabling a visible impact throughout the development cycle, making it faster, reducing errors, and enhancing security.
Therefore, the advantages also affect developers. Far from replacing human work, AI reduces the cognitive load and allows developers to focus on strategic activities rather than repetitive tasks.
These advantages propel the company to a higher level, with streamlined and modern processes that promote innovation alongside efficiency and security.
