Agentic AI is Now On Mid-Sized Indian IT’s Mind
The era of agentic AI is upon us, and surprisingly, Indian IT is also ready for this revolution. What is even more surprising is the fact that mid-sized and small IT firms are also ready for adoption. As usual, they are taking the acquisition route to achieve these capabilities.The latest example is LTIMindtree. Last week, the IT firm announced that it has committed $6 million to Voicing AI, a US-based startup specialising in human-like AI voice agents. This investment aims to bring human-like voice capability across more than 20 languages with conversational, contextual, and emotional intelligence. Moreover, LTIMindtree has formed an alliance with GitHub for its Copilot coding tool to train its workforce on the GitHub ecosystem. Similarly, Mphasis has focused on conversational AI to boost user experiences. In July, the IT solutions provider launched NeoCrux, a tool for improving developer productivity by streamlining software developer cycles with AI agents and orchestrators. In October 2023, the company acquired Silverline, a New York-based Salesforce partner, for $132.5 million. During the announcement, Nitin Rakesh, CEO of Mphasis, said, “The acquisition aligns with our strategy to drive customer experience transformation, modernise contact centres, and enable conversational AI automation to meet evolving client needs.” It seems evident that Mphasis has decided to embrace AI and agentic AI for customer interactions as well. Though it is not clear whether the acquisition of Silverline increased Mphasis’s current capabilities, the impact is definitely visible. Persistent Systems, on the other hand, is addressing AI-related privacy challenges. In September, the company acquired Pune-based data privacy consultancy Arrka for ₹14.4 crore ($1.7 million). “Arrka’s mature frameworks and privacy management platform ensure a scalable and governance-driven approach, critical for successful AI implementations,” Persistent Systems CEO Sandeep Kalra said in a press release. The Approach Differs from the Big IT Meanwhile, bigger IT giants like TCS, Infosys, and Wipro have decided to develop a different strategy for building AI agents for their customers. In the latest quarterly results, TCS posted $1.5 billion in bookings with AI and Infosys has started building small language models and multi-agent frameworks for its clients. A similar situation was observed at Wipro, HCLTech, and Cognizant. TCS, India’s largest IT services exporter, launched a new AI-focused business unit, AI.Cloud, in May, by merging its cloud and AI divisions. Infosys, the second-largest IT firm, unveiled Topaz, an AI suite offering solutions and services. Notably, it has several clients in its portfolio. The mid-sized IT companies are, however, positioning themselves differently here. Speaking with AIM, Nachiket Deshpande, COO at LTIMindtree, said Indian IT firms often do not want to build these capabilities in-house. Commenting on the recent deal with Voicing AI, Deshpande added, “There are so many startups that are coming all around the world. We would want to leverage those startups for those technologies that are coming up.” Deshpande’s biggest reason for not building in-house models is that generative AI is so expensive that it doesn’t make sense to experiment with it while investing so much. “I don’t think the technology in generative AI would be the real differentiator because of the level and the speed of innovation that is happening, whatever technology you may develop will become obsolete within a few months, and you have to keep doing that,” Deshpande said, adding that it requires a lot of capital. Mohandas Pai, the founder of Aarin Capital and former CFO of Infosys, also told AIM that IT services companies are not built to invest disproportionate capital R&D. “Indian IT services companies are not product companies.” “Creating an LLM or a big AI model requires large capital, time, a huge computing facility, and a market. All of which India does not have,” Pai pointed out, adding that even though Infosys, TCS, and others might have the funds, their focus is to provide vertical solutions and not horizontal ones like ChatGPT. Why Is Everyone Bullish on Agentic AI? Similarly, Deshpande also said that the services companies’ P&L is structured differently than that of product companies. “They operate with 80% cross-market, and hence they have the ability to continue to do R&D, and we operate at 30-35% cross-market,” he explained. He believes that if a company invests and builds a particular technology, tomorrow it might become irrelevant. “I need to get 86,000 people to reimagine their work with AI, but I only need 2,000 people to build AI solutions.” “The differentiation of LTIMindtree will lie in terms of how we adopt AI, rather than saying I have another shiny toy which is better than somebody else. Because that differentiation is short-lived,” he added. Apart from the technological capabilities, Deshpande said it’s important that IT companies give startups the space they need to grow on their own. “Hence, acquisition was not the best way, but at a meaningful scale was a better way where we get to leverage the technology, we get to take them to the customer, but also provide those entrepreneurs space to continue their innovation,” he further said. With generative AI systems going autonomous and several big-tech firms announcing models like Devin and others, Indian IT is also ready to adopt that change quickly. Deshpande said that one of the biggest reasons for this is the outlook on productivity. “The idea of productivity outlook is persona-centric, and you have to look at each persona becoming more and more productive,” Deshpande said. Hence, he said that agentic systems, which do not examine a particular business process or task but the entire persona and try to automate large parts of those personas, are the way to adopt that productivity. That’s why agentic systems are becoming increasingly focused. Earlier this year, small IT firms were taking the acquisition route for building AI capabilities. Happiest Minds, Hexaware, Quest Global, Coforge, Sonata, and GlobalLogic have all announced acquisitions in this space. Now, the conversation has shifted to agentic AI.
The biggest reason for not building in-house models for Indian IT firms is that generative AI is too expensive to experiment with.
The biggest reason for not building in-house models for Indian IT firms is that generative AI is too expensive to experiment with.
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["AI", "ML", "generative AI", "agentic AI", "ChatGPT", "Aim", "small language models", "RAG", "R", "Go"]
Mohit writes about AI in simple, explainable, and often funny words. He's especially passionate about chatting with those building AI for Bharat, with the occasional detour into AGI.