Developing Over 100 New Gen AI Agents For Clients: Infosys CEO

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Developing Over 100 New Gen AI Agents For Clients: Infosys CEO
Infosys has developed four small language models for banking, IT operations, cybersecurity and broader enterprise use. These small language models, with 2.5 billion parameters, leverage some of the company’s proprietary datasets, according to Salil Parekh, CEO and MD of Infosys.

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Developing Small Language Models

“We are developing over 100 new generative AI agents for deployment within our clients. We are working closely with the generative AI partner ecosystem to develop joint solutions for our clients, several of them on the platforms of the partners,” Parekh added during the Q3 2025 earnings call on January 16, 2025.

Also Read: IBM and L’Oreal to Build AI Model for Creation of Sustainable Cosmetics

Real-World Applications of Generative AI

Explaining some examples of the work Infosys is doing for clients in the generative AI space, the CEO said the company has developed “a generative AI-powered research agent that generated comprehensive solutions within seconds for requests made for the product support teams of a large technology company.”

And for an audit agency, Infosys has “created three audit agents to intelligently automate multiple tasks for a professional services company,” Parekh said, adding, “With Infosys Topaz, our generative AI-powered services and solutions, we are deepening our enterprise AI capabilities.”

Strengthening Enterprise AI Capabilities

“We continue to strengthen our enterprise AI capabilities, particularly focusing on generative AI, which is witnessing increasing client traction,” said Salil Parekh in the earnings release.

“While the focus remains on cost optimisation, spending towards new growth areas like AI, cloud adoption, cyber security data and analytics is observed,” the company said.

Also Read: Infosys AI Announcements: 2024 Year in Review

Classification of Nature of Work

Responding to a question on the classification of the nature of work (on AI), Parekh said, “So today, AI is something where many clients are doing different, different programs. So it’s not like the traditional tech, which had that sort of a view and when industries were getting back, the discretionary was increasing and otherwise it was more cost. So today, we see the spend is broad based. The end outcome sometimes could be the cost for their own growth, but it’s not like that easily put into one of those buckets today at least. As it becomes more mainstream, we’ll be able to see how they use it. Today, there is a broader usage of AI within companies that is going on.”

Infosys CEO on AI Washing

Separately, during the company’s Q3 FY25 conference call with media, the CEO, responding to a question on AI Washing, said, “On generative AI, I think you mentioned the AI washing. So, I’m not aware of that within Infosys, but you may be aware of that outside with some other companies. We are very clear on what we’re doing with Generative AI.”

He continued explaining, “These small language models, just as an example. Today, we have several discussions with clients where they would like to use the small language modes that we have built. So, how are they built? They are built by using the proprietary data that we have, let’s say on banking or IT operations, and then use some very standard Industry, or in this case, horizontal data and then the client builds their own into that small language model.”

Real Generative AI Work

“Some clients are asking us to build a small language model of their own. So, for example, with a telco client, they want to build their own-let’s say, company X Telco-their own small language model, which we are helping them with because we have the platform for it. This is real generative AI work what we are doing. Then you look at agents. To give you some examples, we have built, for a client–this is actual work, not just a proof of concept–where we have built a research agent for a client, a large tech company, where they are now using that in their product area to support how queries are looked at, and where their own people and their own customers can use this agent.”

“We have built an agent for audit work for a professional services company–the three different agents–that are now helping that company to more efficiently and with fewer errors do what they are doing in their audit activity. So, the work we are doing in Generative AI, we feel, is leading in the industry. We are very clear in how it’s being used across because these are real projects with clients.”