Nomura has reaffirmed its 'Buy' rating on Tata Consultancy Services (TCS), setting a target price of Rs 2,630. This decision follows recent investor meetings in New York, Boston, and Chicago, where Nomura analysts met with TCS Chief Financial Officer Samir Seskaria and Head of Investor Relations Nehal Shah.
TCS's AI Revenue and Investment Strategy
During the meetings, TCS management disclosed that its annualised AI revenue has reached $3.1 billion, constituting approximately 10% of its total revenue. This AI segment has demonstrated robust growth, expanding at a compound quarterly rate of 15-20% over the past four quarters. TCS is actively investing around $1 billion annually in AI training, hiring, and infrastructure to capitalize on this burgeoning market.
Despite these significant investments, Nomura noted that margins in AI services are generally higher than those in traditional services. TCS prefers to manage overall portfolio margins rather than focusing on individual deals.
Enterprise AI Adoption and Challenges
While AI revenue shows strong momentum, Nomura highlighted that only about 5% of enterprises are currently mature enough to deploy frontier AI models at scale. The vast majority (95%) face substantial constraints, including inadequate data quality, lack of integrated infrastructure, and insufficient AI-ready applications.
Early Adopters and Lagging Sectors
- Early Adopters: Banking, financial services and insurance (BFSI), and technology sectors are leading in AI adoption due to better data maturity, stringent regulatory discipline, and earlier investments.
- Lagging Sectors: Healthcare, life sciences, energy, and telecommunications are trailing, primarily due to capital constraints and ongoing industry disruptions.
Deflation in Traditional Services and Future Outlook
Customer demands for higher productivity continue to drive deflation in traditional IT services. TCS has proactively addressed this by delivering productivity gains during contract renewals or by front-loading them in vendor consolidation deals. The company's top 200 clients, which account for 80-85% of its revenue, have largely completed one productivity cycle.
TCS management anticipates that incremental deflation will slow unless there are significant changes in frontier AI models. The overall impact on growth is expected to become more positive as this deflationary drag eases and net new AI revenue accelerates.
Emerging Opportunities: Core Banking Modernization and Small Language Models
TCS has identified the modernization of core banking systems as a significant emerging opportunity. Many large banks still rely on legacy COBOL systems, with a dwindling pool of experienced programmers. AI could drastically shorten these transformation cycles, potentially reducing them from three to four years to just six to eighteen months, by parsing code, generating technical specifications, and modularizing systems.
Enterprises, initially experimenting with frontier models at discounted rates, are now shifting towards smaller, more cost-effective, and domain-specific small language models (SLMs). These SLMs offer several advantages, including lower costs, on-premises deployment capabilities, reduced dependence on single model providers, and greater accuracy for specific tasks. TCS sees an opportunity to develop and deploy these domain-specific models, for example, in credit research.
Furthermore, AI governance, encompassing agent monitoring, guardrails, and identity provisioning, is viewed by TCS as a major potential revenue stream.
Beyond AI: Global Capability Centers
Beyond AI, TCS also foresees opportunities from a potential reversal in the expansion of global capability centers (GCCs) in India. Subscale captive centers with 500-2,000 employees may become economically unviable over time, potentially leading to increased outsourcing to large IT service providers like TCS.