Mumbai: Blackstone-backed Mphasis said it invested approximately Rs 260 crore in building enterprise AI platforms during FY26 while maintaining its EBIT margins, as the company seeks to reposition itself for an AI-driven shift. The company on Wednesday unveiled Tria, an outcome-based enterprise AI platform aimed at bridging the gap between solution design and delivery, and helping enterprises deploy AI for business transformation.
Strategic investment in AI
Mphasis CEO Nitin Rakesh said FY27 would be a foundational year for the initiative, with the company expecting a gradual shift in its revenue mix over time. "The approach combines recurring platform revenue, implementation work, and large managed services engagements enhanced by AI and automation," Rakesh said at a press conference in Mumbai.
AI as a reset, not disruption
He argued that AI is fundamentally changing the economics of traditional IT services. "I do not view AI as a disruption anymore; I see it as a reset," he said. "Historically, our business model was based on effort and headcount, where revenue growth had a near-linear relationship with workforce expansion. AI changes that model, but it also creates entirely new investment pools and opportunities."
Outcome-led strategy
As part of its outcome-led strategy, Mphasis plans to use its Forward Deployed Engineering & Solutions (FDES) group to deliver proof-of-value initiatives through Tria under a unified operating structure. The company also expects to gradually move away from bespoke, effort-based engagements toward a platform-led model combining subscriptions and services.
Pricing tied to value
Rakesh said pricing would not be structured around labour costs versus agent costs. "Instead, it is tied to value and outcomes. There could be a base fee along with outcome-linked payments." He said the future opportunity for services firms lies increasingly in technology orchestration rather than labour arbitrage. While annual recurring revenue (ARR) streams are expected to grow over time, he said their contribution currently remains in the low-to-mid single digits.
Industry pressures and opportunities
Rakesh also acknowledged the structural pressures facing the IT services industry as AI adoption accelerates. Large language models are increasingly automating software development work that services firms traditionally billed by engineering hours, putting pressure on the economics of headcount-linked delivery models. However, he argued that even AI model companies increasingly recognise the need for engineering and integration layers. "AI is a hammer looking for a nail," he said.
Risk of inaction
Responding to questions on how its board is evaluating returns on AI investments, Rakesh said the company viewed inaction as a bigger risk. "Standing still is not an option, particularly in the technology business," he said. "The cost of writing software has fallen sharply, but enterprises still operate in complex environments, and that complexity cannot become the industry's defensive moat."
