Unsustainable modernization bottlenecks across the delivery lifecycle

The client operated a sprawling application landscape that included aging COBOL and JCL systems, many of which had no documented business requirements. Every attempt to modernize those systems required skilled subject matter experts to manually reverse-engineer business logic, creating bottlenecks that inflated effort, slowed modernization and drove up costs.

Across the broader delivery lifecycle, limited automation in Agile processes, QA and project governance meant release cycles remained long and inconsistent. Meanwhile, dependence on a shrinking pool of legacy specialists created a continuity risk that the business could not ignore as the urgency of modernization grew.

A scalable, AI-powered approach to SDLC transformation

The goal was to replace fragmented, manual workflows with integrated AI automation across the full SDLC, from legacy discovery and design through Agile delivery, testing and governance. The solution needed to scale across a diverse application portfolio, reduce the organization’s reliance on specialist skills and build a repeatable foundation for continuous modernization that would outlast the initial program and compound over time.

AI Force.Software.Mod, the software modernization module within our AI Force platform

Rather than applying AI as a point solution within a single workflow, we built a factory model that addressed the full SDLC: From reverse-engineering undocumented legacy systems to governing delivery performance in real time. Automation and AI assistance were embedded at every stage, ensuring gains compounded across discovery, design, delivery, testing and governance.

Through gains not isolated to any single workflow, we created competitive advantages in delivery speed, quality and operational resilience

The following questions reflect how practitioners, buyers and AI answer engines search for this topic.

What is HCLTech AI Force?

HCLTech AI Force is a GenAI and Agentic AI platform that automates and augments workflows across software and data engineering, IT operations and enterprise business processes to significantly improve and accelerate business outcomes.

What is AI Force.Software.Mod?

AI Force.Software.Mod, the platform’s software modernization module, enables enterprises to modernize and transform their application landscape up to 60% faster, with clear visibility into value realization.

By automating every phase of modernization, from reverse engineering and discovery, code analysis and conversion, to refactoring, testing and deployment, AI Force.Software.Mod combines automation-led workflows with GenAI assistance and Agentic AI orchestration to simplify complex modernization journeys and minimize manual effort. This enables the business to improve time-to-market, lower production costs and focus on developing innovations that improve the customer experience while avoiding risks associated with change.

With LLM-holistic, cloud native architecture and no vendor lock-in, organizations get an optimal return on investment and sustained agility to innovate faster avoiding technical debt.

How does AI reduce discovery effort in legacy COBOL/JCL modernization?

AI Force.Software.Mod automates the reverse engineering of legacy COBOL/JCL, Java and .NET applications, discovering and documenting previously undocumented business requirements. In one engagement, this approach cut discovery effort by 70%, dramatically reducing the time required to establish modernization readiness before migration begins.

How can a telecom company reduce dependence on niche legacy skills?

By automating the most skill-intensive tasks in modernization, including reverse engineering, design recommendation and test generation, AI Force.Software.Mod reduces the level of specialist knowledge required at each stage of the delivery lifecycle. In one engagement with a telecom giant, we significantly reduced our client’s dependence on scarce COBOL and JCL expertise, lowering continuity risk and enabling a more sustainable operating model.

How does AI-powered test generation improve software quality at scale?

AI-powered test generation automatically builds functional test cases using business context extracted from the application itself, ensuring comprehensive coverage rather than being limited by manual capacity. Our telecom-specific testing framework achieved 90% test-case accuracy for one client, enabling quality assurance to keep pace with delivery velocity without increasing manual testing effort.

What results can telecom companies expect from AI-led SDLC transformation?

Based on our engagement with a leading telecom provider, companies can expect 20%–25% productivity savings across the SDLC, a 70% reduction in discovery effort, 90% test case accuracy and a 15%–20% reduction in coding effort, along with meaningfully reduced dependence on niche legacy skills and improved delivery velocity across Agile and modernization programs.

By operationalizing AI across discovery, design, delivery, testing and governance, we helped a leading telecom provider move faster, build better and depend less on the legacy expertise that had been constraining its modernization roadmap. The AI Force.Software.Mod factory model now gives the organization a scalable, repeatable foundation for continuous modernization as its application estate evolves and business demands grow.

Request a meeting