IT major Tech Mahindra is seeing increasing adoption of a pricing model that accounts for humans and AI agents working together, as the IT services company explores outcome-based contracts beyond traditional pricing arrangements like time-and-materials and fixed-price. "We had come out with a pricing mechanism which could price for both the human and agents working together," Chief Operating Officer Atul Soneja said during the company's Q2FY27 post-earnings call.
"There is a human in the loop and there is a human on the loop," he added, describing the model for work involving AI agents.
Soneja also said that the pricing model was being taken to clients as an outcome-based process and was seeing early traction. "We have seen some early successes where clients want to use that in specific portfolios," he said. The company has seen early successes in finance and accounting processes, where clients are exploring its vector squad-based pricing model to drive outcomes. Soneja also cited use cases in telecommunications and financial services. "These models and the pricing models of agent and humans working together is being adopted across multiple industry segments," he said.
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However, clients need to understand how the model works, including the cost of running AI agents. "This requires maturity also in our client organizations to understand how this will work, how will the token economics work," Soneja said. He added that Tech Mahindra also prices tokens as part of its agent-pricing approach.
The company did not disclose the revenue generated from the model or the proportion of its business covered by these contracts.
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Managing Director and Chief Executive Officer Mohit Joshi said the company's opportunity was not limited to delivering existing work more efficiently. "For us, the opportunity being enabled by our latest offerings is not simply to deliver existing work more efficiently, but to take on a wider scope of responsibility and help clients achieve better outcomes," Joshi said.
The company is developing AI toolchains for individual service lines, with productivity gains expected to benefit fixed-price and managed-services contracts. Joshi said these gains could help Tech Mahindra expand gross margins and grow revenue without a proportionate increase in headcount, as employees freed up from existing projects take on additional work.
"We expect that to fully play into the remainder of the year and beyond," he said.
Tech Mahindra's AI initiative, TechM Helix, includes more than 200 AI assets that are being rationalised into reusable blueprints, platforms and accelerators. The company completed 25 prioritised AI use cases during the quarter and was progressing more than 100 additional use cases. One example cited by Joshi was Collections Guru, developed with AWS and deployed at Target Group. According to the company, the solution delivers an approximately 40% efficiency gain in arrears management.
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