AI-powered modernization: transform your legacy with Artificial Intelligence 

AI-powered modernization is the strategic use of Artificial Intelligence to accelerate legacy system transformation, automate processes, and continuously generate business value. In practice, with AI support, squads gain greater agility and autonomy to extract intelligence from historical data, accelerate time to market, and replace legacy systems in a way that is more aligned with business demands. 

In today’s rapidly evolving competitive landscape—and with the fast rise of AI—modernization has become an urgent priority. However, updating legacy systems remains a complex challenge. In this context, AI helps overcome these hurdles with greater depth and lower risk, accelerating the understanding of existing systems, freeing time for more strategic decisions, and driving improvements in speed and quality. 

According to Gartner, 50% of CEOs are prioritizing integration, innovation, and modernization of enterprise applications and software by 2025. In large organizations, where legacy systems support critical operations, the challenge lies in innovating without compromising stability. A difficult but essential step for digital transformation. 

In this article, we explore how AI-powered modernization enables organizations to integrate analytics, automation, and intelligent decision-making without requiring disruptive system rebuilds. 

Why modernize with Artificial Intelligence? 

Companies are undergoing a paradigm shift: we’ve moved past the digitalization phase—focused on migrating processes to digital—and entered the era of intelligent automation, powered by Artificial Intelligence. This new phase demands speed, scalability, and the ability to innovate consistently. 

In this context, modernizing legacy systems is no longer a technical choice, but a strategic necessity. Outdated technologies bring risks due to lack of vendor support and qualified professionals, fail to meet user expectations, increase infrastructure costs, and hinder the adoption of innovations such as cloud, AI, and third-party APIs. 

Legacy code also directly impacts scalability and the speed of delivering new features. When applied to modernization efforts, Artificial Intelligence reduces manual effort and significantly accelerates the software delivery lifecycle. 

At SoftDesign, we leverage AI to accelerate deliveries across multiple fronts. On the back end, unit test generation is automated: developers only need to name the test, and Copilot completes the implementation based on context. We also migrate legacy code to modern standards, ensure compliance with architectural patterns, and accelerate scaffolding by automatically creating repositories, services, and endpoints. 

On the front end, Copilot assists in generating models and services from Swagger documentation, while also providing contextual suggestions for building interfaces with reusable components. In Quality Assurance, AI automatically generates end-to-end test cases with Cypress, increasing test coverage with less manual effort. 

For business leaders, this is a critical moment: digital transformation with AI is a matter of survival in increasingly dynamic markets. Organizations driving this modernization with AI-augmented squads release products faster, improve delivery quality, and reduce project costs. 

Benefits of AI-powered modernization 

According to Red Hat’s The State of Application Modernization report, 78% of organizations are using AI as part of their modernization efforts. Among them, 53% use AI to support application modernization processes, while 42% are adding AI to legacy systems to update them. 

At SoftDesign, we apply intelligent automation and advanced software engineering to modernize systems in a secure and effective way. Our process directly impacts speed, quality, and alignment with business strategy. 

Key benefits of AI-powered modernization include: 

• AI-assisted engineering: up to 60% faster coding, automated test coverage, and support throughout the development cycle. 
• Adoption of modern technology standards: user experience–focused interfaces, cloud-first architecture, and DevSecOps practices ensure scalability, security, and operational efficiency. 
• AI for data-driven decision-making: predictive models and advanced analytics enable faster, more accurate, and insight-driven decisions. 
• Strategic, phased alignment: our approach ensures modernization without disruption, with incremental deliveries aligned with business objectives. 

Use cases and real-world applications 

As shown, AI-powered modernization is already driving change across corporate environments. Some practical examples include: 

• Modernization of legacy systems with AI: companies are using algorithms to map dependencies, suggest refactorings, and identify critical issues in aging systems, reducing risks and accelerating digital transformation. 
• Machine Learning applied to legacy systems: predictive models are being used on historical ERP, CRM, and operational data to anticipate demand, optimize inventory, and improve customer service. 
• AI in the Software Development Life Cycle (SDLC): AI-powered tools optimize every stage of the software lifecycle—from requirements analysis to automated testing, continuous validation, and intelligent documentation. 
• Cloud-first infrastructure as a foundation for modernization: migrating to the cloud and embedding native AI services accelerates time to market, enhances scalability, and enables integrations with modern analytics and automation solutions. 
• AI-augmented engineering: software engineers now rely on AI copilots for code generation, automated security reviews, and continuous integration, boosting productivity while reducing errors. 

At SoftDesign, modernization involves applying AI strategically across every stage of the SDLC. In practice, we use Artificial Intelligence from prototyping and data analysis to MVP creation with low-code tools. 

Our AI agents also assist in backlog writing and prioritization, legacy code analysis, assisted coding, code review and refactoring, and automated test generation. 

Phases of an AI-powered modernization strategy 

Case study: modernizing with AI 

Spring Point, a U.S.-based company specializing in software for the electromechanical industry, modernized its legacy ERP system MotorBase—originally built in the 1990s with a client–server architecture. With SoftDesign’s support, the company developed the first version (MVP) of a new cloud-based SaaS solution, redesigned with a user experience–driven interface. 

• AI Augmented: AI was applied to convert Visual Basic code into .NET Core, generate automated tests, and document business rules, accelerating coding by up to 90%. 
• Lead time reduction: feature delivery cycles dropped from 4 days to 2, doubling development speed. 
• Results: ERP transformed into a SaaS platform, with easier access for global clients. The beta version is already being used by Spring Point’s three largest clients, with a commercial launch planned for 2025. 

According to Troy D. Locke, CEO and co-founder of Spring Point Solutions, integrating AI into software is highly strategic to improve predictability and optimize client operations. SoftDesign’s partnership drives this evolution through testing and experimentation with intelligent features. 

Challenges and risks in AI adoption 

Implementing Artificial Intelligence brings significant opportunities, but also requires attention to critical challenges to ensure sustainable and ethical results: 

• Technical debt and risks: integrating AI into legacy systems can be complex, requiring infrastructure investments, platform upgrades, and process reviews. Poor integration may lead to inefficiencies or even operational failures. 
• Security and compliance: AI-based solutions must strictly follow privacy regulations (such as GDPR or LGPD). Handling sensitive data demands strong protection mechanisms against leaks and misuse. Vendors must also ensure robust protection of source code and business rules. 
• AI and data governance: effective governance involves defining clear responsibilities, monitoring model performance, and ensuring transparency in automated decision-making. It is crucial to mitigate algorithmic bias and maintain continuous audits. 
• Team training and cultural change: AI adoption goes beyond technology. It requires workforce upskilling, leadership involvement, and a culture of experimentation that embraces continuous learning. 

Measuring the results of AI-powered modernization 

The adoption of AI in modernization must generate measurable impact. Some key metrics to track ROI include: 

• Operational cost reduction: automation of repetitive tasks and more efficient use of resources reduce expenses in maintenance, rework, and support. 
• Shorter lead time: AI-assisted code generation and intelligent testing shorten the cycle from conception to solution delivery. 
• Increased engineering efficiency: with AI-augmented tools, teams produce more with less effort, focusing on strategic challenges instead of manual tasks. 
• Faster innovation: AI integration accelerates experimentation, validation, and launches, strengthening organizational competitiveness. 

At SoftDesign, we transform legacy systems into modern platforms by combining intelligent automation with cutting-edge software engineering. By embedding AI into every stage of development, we accelerate coding by up to 60%, automate tests with wide coverage, and deliver scalable solutions with excellence in UX, cloud, and architecture. 

Building the future with Artificial Intelligence 

AI-powered modernization is a strategic path for companies seeking agility, efficiency, and continuous innovation. By combining intelligent automation, integration with legacy systems, and skilled teams, organizations can cut costs, accelerate time to market, and significantly increase productivity. 

SoftDesign is a global software development company that combines design, strategy, and Artificial Intelligence to build impactful digital products. We integrate AI agents across our entire SDLC, boosting squad productivity by up to 55%. 

If you’re ready to take the first steps in an AI-powered modernization plan, count on our expertise in app development, platforms, data solutions, intelligent agents, and Machine Learning models. 

Frequently asked questions on AI-powered modernization