As seasoned mainframe veterans head into retirement, a critical question looms for IT leaders across Asia Pacific: who will maintain the robust backbone of enterprise IT infrastructure?
While Gen Z talent is increasingly drawn to cutting-edge fields like artificial intelligence (AI), industries from banking and insurance to manufacturing still rely heavily on mainframes for their unmatched speed, stability, and capacity for real-time, high-volume data processing.
From fraud detection and instantaneous payment processing to complex supply chain operations, these legacy systems remain indispensable. The challenge is stark.
According to Deloitte, a significant 79% of IT organizations grapple with acquiring the right resources and skills for their mainframe operations. This persistent mainframe skills gap, while not new, now faces a powerful potential solution: Artificial Intelligence (AI).
In the Philippines, this transformative shift is already well underway, with 86% of Filipino white-collar workers actively using AI to “boost productivity, efficiency, and creativity,” and a resounding 89% of Filipino leaders convinced that AI adoption is essential for maintaining competitiveness.
To delve into this critical dilemma, we recently sat down with Praveen Kumar, Vice President for Asia Pacific at Rocket Software, a global leader in enterprise modernization. Kumar, a veteran of the Asia Pacific tech landscape since 1995, shared insights on how organizations in the region are leveraging AI to future-proof their legacy infrastructure and talent pipelines.
The enduring power of the mainframe
Despite the narrative of “new” technologies, the mainframe remains a strategic asset, especially for financial institutions. Kumar explained that while AI might simplify low-level coding and issue resolution, it doesn’t entirely “resolve the mainframe skills gap that continues to exist”.
According to Kumar, the challenge isn’t that AI cannot solve it, but rather that the investment in AI for traditional mainframe coding hasn’t matched that for distributed stacks, where “revenue opportunity and solutions can be a lot more”.
However, companies like Rocket Software are making mainframe integration seamless. “Companies like Rocket Software tend to provide integration opportunities between the mainframe and the distributed side using modern technologies like REST APIs,” Kumar elaborated.
They also offer data solutions for “replicating data live, both ways, between the mainframe and the distributed stack”. This capability allows financial institutions to offload much of the processing volume to distributed systems, where AI and generative AI are flourishing, significantly reducing the demand for deep mainframe coding and operational skills.
AI: The digital apprentice and beyond
AI is fundamentally reshaping the workforce, extending its impact beyond mere automation to enable smarter transformation. Kumar noted that basic, entry-level jobs, including much of coding and data entry, are increasingly being handled by AI tools.
“You can write a complete application using AI tools like ChatGPT… or Gemini and then put it on the cloud and run the app,” he said. This shift means that future tech professionals will need to develop higher-order skills.
“If the human beings start interpreting the machine as the sole source of truth… then they are not in a position to go to the next level,” Kumar warned. Instead, the focus for Gen Z should be on “interpreting and possibly ask the same question in three different ways,” analyzing multiple machine-generated answers to find the right solution. This elevated level of problem-solving is what excites younger talent, making traditional tech roles more appealing by empowering them to enhance capabilities and add volume to content creation.
Rocket Software’s solutions directly illustrate this. They’ve introduced “smart chat” into their content engine, allowing bank operators to instantly retrieve specific customer transaction data across “zillions of data elements and documents” by simply typing a question. This means operators “don’t need to build skills” for complex data retrieval; they just need to ask the right question.
Similarly, by enabling replication of mainframe data to the cloud in pockets, financial institutions can build generative AI applications on the cloud without direct mainframe access, leveraging existing data without needing to build new cloud-native capabilities from scratch.
Future-proofing talent pipelines
Leaders in the Asia Pacific region are strategically repositioning legacy infrastructure roles to attract and retain next-generation talent. By integrating AI with mainframe operations, companies can make these roles more appealing to younger Filipino tech professionals who gravitate towards newer technologies.
“The AI integration with the mainframe helps the younger people appreciate the power of the mainframe,” Kumar stated.
Instead of perceiving it as a “monolithic elephant that just never dies,” younger professionals can focus on optimizing it for transactional workloads, while identifying other processes that can be run on distributed cloud platforms with more generative AI capabilities. This approach helps “the companies innovate and build those modules”.
Kumar emphasized that Rocket Software’s model of “modernization without disruption” plays a crucial role in this talent strategy. By providing solutions that allow companies to evolve their systems without wholesale rewrites, they create an environment where Gen Z can engage with technologies they find futuristic while still interfacing with the core. This phased approach allows the skills gap to be gradually bridged, making the larger ecosystem “a lot more interesting” for new talent to join.
Rocket Software aims to help customers “bridge the skills gap, bridging the cost gap and bridging the technology gap”. By evolving wisely and ensuring stability supports digital progress, the Philippines can solidify its position as a robust digital economy and a leading fintech hub in the Asia-Pacific region.
