“The Blueverse Credit is going to be our AI currency. It will allow customers to access AI skills from LTM, purchase outcome-based services, or buy defined blocks of effort such as modernisation or cloud migration,” said Venu Lambu, chief executive officer.
Speaking to Business Standard after the company’s fourth quarter FY26 results, Lambu said the framework combines human effort with digital labour. “What this AI currency does is redefine pricing by combining both human effort and digital employees — or agents — into a unified construct. That’s the core idea behind Blueverse Credit,” he added.
More details will be shared in the near term but underscored the need to rethink pricing. “It’s not just about pricing for outcomes anymore. The broader economy is moving towards a subscription-based model — everything is increasingly being consumed as a service,” Lambu noted.
He added that the company began work on the framework after introducing the concept of “digital employees”, assigned IDs and managed by human mentors. “These digital employees have a name and a face, with a full avatar. This will evolve based on the services we price using the new AI currency. We will not apply it across all services, but in select areas where agents and humans can work together to deliver outcomes priced through Blueverse Credit,” he said.
The proposed framework marks a shift from traditional effort- and capacity-based billing to a unified unit combining human effort with digital labour, or AI agents.
The move comes as enterprises increasingly experiment with AI-led workflows, where autonomous or semi-autonomous agents perform tasks ranging from basic automation to full-fledged functional roles. LTM’s model seeks to align pricing with this shift.
For Q4FY26, the company reported a 23.4 per cent rise in net profit to ₹1,392 crore and a 15.6 per cent increase in revenue to ₹11,292 crore year-on-year.
On client budgets for FY27, Lambu said each vertical is at a different stage of growth. “Most companies are allocating budgets towards AI technologies and adoption. The business case lies in net savings, either through productivity gains or indirect efficiencies. It is up to us which side we play,” he said.
He added that large-scale AI implementation across the industry is likely in the latter part of FY27.
Towards the end of 2025, L&T outlined a five-year blueprint, ‘Lakshya 3’, targeting double-digit growth. Asked whether LTM can achieve this, Lambu said it is possible.
“With regard to LTM’s aspirations under Lakshya 3.1, I would say it is possible if we tap new addressable markets,” Lambu said.
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