Venu Lambu, CEO of the Indian software services firm LTM, told Reuters that the company forecasts that revenue from artificial intelligence (AI) will grow faster than revenue from its traditional IT services business. He believes that enterprises will require assistance from IT companies in deploying powerful large language models from companies such as Anthropic and OpenAI.
Investor concerns that increasingly sophisticated AI models could disrupt the operations of traditional IT service firms have led to a decline of more than 23 percent in India's Nifty IT index since the beginning of the year, putting it on track for the second-largest drop since 2008.
LTM, which signed a partnership with Anthropic on Monday to implement Claude for corporate clients, anticipates that these models will help create a new implementation market for IT companies 'with the right context and at reasonable prices.' Lambu noted that 'almost all' deals include an AI component, but not every business scenario requires expensive advanced models.
According to him, the acceleration of AI adoption may lead to projects starting small and diverse, but after providing customers with proof of functionality, they will multiply among the same clients. He expects AI adoption in the corporate sector to accelerate in the second half of the 2027 fiscal year.
LTM, which demonstrated 6.1% year-on-year revenue growth in the first quarter, disclosed its AI revenue for the first time—$150 million on a quarterly run rate, accounting for 12% of total revenue—and this revenue comes from three AI-focused streams. These segments are distinguished by the fact that AI was initially conceived as a key element, whereas enterprise AI implies integrating AI into clients' technological stacks and software processes. However, LTM does not include sales related to enterprise AI in its AI revenue figure.
A larger competitor, HCLTech, reported so-called advanced AI revenue of $171 million in the June quarter, which accounted for about 4.6% of total revenue. Lambu also emphasized that the 'big problem' for clients is the cost of tokens when using AI models, as AI developer companies are increasingly moving towards token-based pricing, which charges clients for actual usage. He added that the main focus is on helping companies create management systems to control costs and usage.
