Happiest Minds co-chairman & CEO Joseph Anantharaju and Managing Director Venkatraman Narayanan discuss how enterprise AI adoption is evolving in an interview with TNIE's Padmini Dhruvaraj. They talk about the growing demand for AI token optimisation, AI consulting and implementation projects, plans to disclose AI-led revenue, changes in hiring and workforce training, and the company's growth outlook for the rest of the financial year. Edited Excerpts
Why is AI token optimisation becoming important for enterprises?
Joseph Anantharaju: Token utilisation has become a much bigger conversation over the last month or month and a half. Some of our customers who were early adopters of AI have come back to us asking us to benchmark their usage and find ways to optimise token consumption. In one case, we were able to reduce token consumption by 75%. We have now developed best practices and guidelines based on that experience. Where customers use our productivity platform, we are embedding these practices into the platform. For others, we help them optimise using those best practices.
Is AI spending coming from fresh budgets or from existing technology spending?
Joseph Anantharaju: It is a mixture of both. Some customers have allocated fresh budgets for AI initiatives. Others are optimising the run part of their business using AI and productivity tools, and then using those savings to fund AI projects. If they do not have a separate AI budget, or if they have exhausted it, they are looking at ways to optimise existing spending to create room for AI.
Are AI consulting projects generating more business for Happiest Minds?
Joseph Anantharaju: We do not report consulting revenue separately for AI, but these engagements generally have better margins because the billing rates are higher. In most cases, once we complete the consulting engagement and proof of concept, we get the follow-up implementation project. There have been a few cases where customers have implemented it internally, but in most cases the consulting engagement leads to larger implementation work.
When will Happiest Minds begin reporting AI-led revenue?
Venkatraman Narayanan: We already have the number, but we want to stress-test it before we publish it. Once we disclose it, it is something we will continue reporting from then onwards. AI-led revenue is already a decent-sized business for us and it is only growing. We expect to start publishing that number in the coming quarters.
Has AI changed the way Happiest Minds hires?
Joseph Anantharaju: We are seeing productivity improvements and less effort is required to deliver the same amount of work. At the same time, customers are asking us to do more work, including projects that were on their wish list earlier. Hiring has therefore become much more dynamic. Instead of hiring first and deploying later, recruitment is becoming more specific to the skills required and the kind of projects we have.
Venkatraman Narayanan: Hiring has three parts — replacement hiring, hiring for new positions and hiring for the future. For future demand, our focus is on training the existing workforce through internal programmes to make them AI-ready, while bringing in people with AI skills when there is fresh demand. We are not hiring people first and then deciding where to deploy them.
Are AI projects leading to recurring business for Happiest Minds?
Joseph Anantharaju: At the company level, around 94-95% of our business is repeat business. We do not separately track whether AI engagements directly generate more AI work, but AI is expected to lead to additional business, including follow-on implementation and related opportunities. Once we begin reporting AI-led revenue, it will provide a clearer picture of how that part of the business is growing.
How is Happiest Minds adapting its workforce for AI demand?
Venkatraman Narayanan: Demand today is increasingly for people with AI skills. We are deploying forward deployed engineers where customers require them, while also training existing employees so they can transition into these roles. Rather than treating them as entirely different capabilities, we are helping our workforce build AI skills alongside their existing expertise.
Joseph Anantharaju: The technology landscape is changing very quickly. While we hire AI talent from the market, talent transformation within the company is equally important. Tools and platforms evolve rapidly, so training cannot be a one-time exercise. We are putting in place continuous learning mechanisms because skills acquired even a few months ago can become outdated as AI models and platforms evolve.
