Three large modernisation contracts announced within days of each other have highlighted an emerging opportunity for India’s IT services industry: helping enterprises clean up years of accumulated technical debt before they can fully embrace artificial intelligence.
On June 8, Tata Consultancy Services secured a multi-year, multi-million euro modernisation contract from insurer Canada Life. Around the same time, Wipro signed a modernisation deal with financial services provider TruStage, while Infosys expanded an existing transformation programme with Norway’s DNB Bank.
While the contracts span different geographies and industries, they point to a common challenge confronting enterprises. Many companies eager to deploy AI are finding that decades-old technology systems, fragmented data and ageing software are limiting their ability to do so. For IT firms, that is creating a fresh wave of demand.
“Modernisation and software development life cycle is where the biggest opportunity lies for enterprises, and we are seeing good demand,” HCLTech CEO C Vijayakumar had said earlier this year. Financial services, telecom and healthcare firms, which rely heavily on custom software, are emerging as key areas of opportunity, he had said.
Legacy Constraint
The problem stems from what the technology industry calls technical debt — the cost of maintaining and working around outdated systems that were built years ago but never fundamentally redesigned. Over time, enterprises add new applications, processes and layers of software, creating increasingly complex technology estates that become expensive to maintain and difficult to upgrade.
The issue is no longer confined to IT departments. As companies move from AI pilots to enterprise-wide deployments, legacy systems are increasingly becoming a business constraint. Data often sits across disconnected platforms, applications struggle to communicate with one another and introducing new AI tools frequently requires significant re-engineering of existing systems.
“Tech debt isn’t just an IT challenge anymore, it has become a business imperative, especially for organisations that are scaling AI initiatives,” Veda Iyer, global chief marketing officer and head of hyperscalers and strategic partnerships at Mphasis, said.
“Historically, enterprise modernisation focused on cloud migration, ERP upgrades and cybersecurity. The rise of AI is expanding the scope of such projects into business functions ranging from customer engagement and underwriting to supply chain operations and payments, according to industry executives,” she added.
The urgency is growing. Research firm IDC said in a report earlier this year that organisations that fail to address technical debt could face significantly higher costs and failure rates in AI projects by 2027. At the same time, it found that companies investing in modernisation are generating substantially higher digital revenues than their peers.
BFSI Blitz
Banking and insurance are emerging as particularly active sectors. Both industries operate some of the largest legacy technology environments globally, even as regulators push for greater digitisation and customers increasingly expect digital-first experiences.
Industry estimates suggest that banks spend as much as 70% of their IT budgets maintaining existing systems, leaving less room for innovation. As AI adoption expands, enterprises are finding that modernising core systems is becoming a prerequisite rather than a choice.
“With India’s BFSI AI market projected to grow from approximately $830 million today to more than $8 billion by 2033, as per IMARC group, organisations have a significant opportunity ahead, but realizing that value requires modernizing the foundation first,” Iyer revealed.
Infosys in April launched a modernisation offering with enterprise transformation company Pega and its own platform, ILEAD. HCLTech has expanded its partnership with Pegasystems to accelerate legacy modernisation projects, while Mphasis is positioning its Front2Back framework as a way to reduce dependence on ageing core systems and prepare organisations for AI adoption.
The arrival of generative AI is also changing how these projects are executed. AI tools are increasingly being used to automate code migration, application upgrades and data modernisation efforts, helping reduce the time and cost involved in moving away from legacy systems.
“GenAI and AgenticAI have helped automate and simplify platform, code, application and data migration from legacy to modern platforms,” Vijay Gopalakrishnan, Partner at Deloitte India, said.