Happiest Minds sees net profit decline by 20%, unveils new AI strategy

Happiest Minds Technologies, a mid-tier IT services company, reported a 19.56% drop in net profit for the third quarter of FY26, impacted primarily by new labour code regulations, even as it announced a new artificial intelligence (AI) initiative.

Happiest Minds reported a net profit of Rs 40.3 crore for the third quarter. However, the company’s revenues grew by 10.6% on a year-on-year (YoY) basis to touch Rs 587.56 crore.

Commenting on the results, Ashok Soota, Chairman and Chief Mentor, said the company has launched AI First as its 11th strategic transformation, supported by 11 focused programmes.

He noted that the company has already made significant progress across multiple programmes, with momentum expected to accelerate growth. Soota also addressed recent AI-related developments that have caused volatility in global software markets, stating that such changes represent an opportunity rather than a threat for Happiest Minds and the broader IT services industry.

Sridhar Mantha, CEO of Generative AI Business Services (GBS), said a key pillar of the AI First journey is the company’s AI Services Delivery Platform, designed for speed, scale, and measurable value.

Mantha added that Happiest Minds currently has 32 Generative AI and Agentic AI use cases that have moved beyond prototypes, with several scaling into full projects that can be replicated across multiple accounts and sectors.

The platform integrates reusable components, frameworks, and intelligent agents to help enterprises transition AI initiatives from pilot stages to full-scale production. Already deployed with customers, the platform is delivering tangible outcomes, including reduced time-to-market and improved service delivery productivity, and is now being scaled across industry verticals.

Meanwhile, Joseph Anantharaju, Co-Chairman and CEO, said AI First aligns closely with clients’ shift toward embedding AI at the core of their business strategies. He emphasised the potential of an Agentic AI approach using a hybrid model of coding agents and human developers to modernise legacy applications, reduce technology debt, and deliver productivity gains in a cost-efficient and low-risk manner.