By Haripriya Suresh
BENGALURU, July 14 (Reuters) – Indian software services firm LTM expects AI revenue to outpace its traditional services business, CEO Venu Lambu told Reuters, betting that enterprises will need IT companies to deploy powerful large language models from firms such as Anthropic and OpenAI.
Investor worries that increasingly capable AI models could disrupt the businesses of traditional IT services firms have led to India’s Nifty IT index falling more than 23% year-to-date, on course for its second-biggest loss since 2008.
LTM, which on Monday signed a partnership with Anthropic to deploy Claude to enterprise clients, is betting that these models will help create a new implementation market for IT firms “with the right context at the right costs”.
“Pretty much all” deals have an AI component to them, Lambu said, but expensive frontier models are not needed for every business scenario, he added.
Instead, the acceleration of AI adoption could see projects start off small and varied, “but once you deliver a proof point to the customer, it just multiplies with the same customers,” he said, adding he expects enterprise AI adoption to accelerate in the second half of fiscal year 2027.
LTM, which posted a 6.1% year-on-year rise in first-quarter revenue, disclosed its AI revenue for the first time — $150 million on a quarterly run-rate basis, or 12% of total revenue, across three AI-native businesses.
These are segments in which AI is designed as a core component from the ground up, while enterprise AI involves embedding AI into clients’ technology stacks and software processes. LTM does not count sales from enterprise AI in its AI revenue bucket.
Larger peer HCLTech reported so-called advanced AI revenue of $171 million in the June quarter, about 4.6% of overall revenue.
A “big concern” for clients is the token costs involved with using AI models, Lambu said, as AI firms are increasingly shifting to token-based pricing that charges customers based on usage. The focus is on helping companies establish governance frameworks to control usage and costs, he added.
(Reporting by Haripriya Suresh in Bengaluru; Editing by Janane Venkatraman)
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