Bill clients by the hour, add more headcount, grow the business. AI-driven automation has broken this model completely. When tools can deliver the same work with 30% fewer people, charging by the hour becomes mathematically unsustainable.
The numbers tell the story. Cognizant reports 30% productivity improvements from AI implementation. Infosys achieves 20-40% efficiency gains in customer service programs. Tech Mahindra delivers 7% AI-led productivity improvements. In a traditional time-and-material (T&M) model, these gains directly reduce revenue—fewer hours billed means less income, even if costs decline proportionally. Fixed overhead and margin requirements make this a losing proposition.
BMO Capital Markets analyst Keith Bachman captured the existential threat: "It becomes increasingly difficult to sustain hours-based economics in a higher-productivity delivery environment." The solution? Shift pricing models to capture value from outputs rather than inputs.
This margin differential is transforming how IT services companies structure their business. Transcripts
Meanwhile, its T&M revenue declined 4% to $9.1 billion. Yet overall revenue grew 7% to $21.1 billion. The math works because fixed-price contracts allow vendors to capture AI productivity gains as margin rather than passing them to clients through lower billing rates.
Infosys tells a similar story. Fixed-price contracts grew to 54% of revenue ($10.4 billion) in FY25, while T&M revenue fell 1% to $8.87 billion. Overall revenue still grew 3.9% to $19.28 billion. The company achieved 3.6% year-over-year pricing improvement through its Project Maximus value-based selling initiative, contributing 30 basis points of margin expansion. Transcripts +1
The company's improving revenue growth trajectory—from -1.0% in Q1 FY26 to 2.4% in Q4—correlates directly with its increasing mix of fixed-price contracts. Transcripts
The real transformation lies beyond fixed-price contracts in outcome-based models, where vendors receive a percentage of cost savings delivered to clients. Sushovon Nayak, lead IT analyst at Anand Rathi Institutional Equities, articulated this shift: "If IT outsourcers are able to save costs for their clients, a percentage of those savings will be given to the tech vendors."
This structure creates perfect incentive alignment. Clients want maximum savings. Vendors want maximum savings because their compensation is tied to the results. AI makes this possible by delivering measurable, predictable cost reductions that can be objectively verified.
Infosys CEO Salil Parekh is explicitly prioritizing this direction. "There is lot of discussion now that can we look at some things, because the AI is transformative, that can we look at something which is outcome-based," he stated. The company already has 400 AI projects in progress with benefit-sharing frameworks in place. Transcripts
Cognizant is evolving from "software implementer to AI builder," with 3,500 early AI engagements providing the experience base for outcome-based contracts. The company's 30% productivity improvements and 8% year-over-year growth in revenue per employee demonstrate its ability to create measurable value.
Tech Mahindra has pioneered perhaps the most innovative approach with its "service token" pricing framework. Instead of billing by hours or deliverables, the company measures work in service tokens—specific units of work delivered. Each token transparently separates human labour contribution from digital labour (AI agents) contribution. Transcripts +1
This model is fundamentally designed for the AI era. When AI agents generate tokens without human hours, revenue decouples from headcount. The company has implemented this across accounts payable processes, modernization projects, network services, and infrastructure operations. Transcripts +1
HCL Tech faces a different challenge. The company acknowledges 2-3% net deflation from AI (3-5% in "AI disrupted" services). CEO C Vijayakumar noted the shift toward output-based pricing but admitted "nothing to report on the revenue impact" so far. The company has walked away from at least $1 billion in unprofitable deals and requires 25-30% more effort to convert deals to similar total contract value. Transcripts +1
The four companies are transitioning at markedly different paces, creating temporary competitive advantages and disadvantages.
Cognizant demonstrates the fastest transition velocity, moving from 43% to 47% fixed-price share over three years (+400 basis points) compared to Infosys's move from 53% to 54% (+100 basis points). Yet Infosys leads in current fixed-price share at 54% versus Cognizant's 47%. Cognizant's stronger overall growth (7% versus 3.9%) suggests transition velocity may matter more than current position.
Tech Mahindra's margin-first orientation and service token innovation could prove uniquely advantageous in the AI era where revenue growth becomes less correlated with headcount growth. The company's explicit focus on the 8% margin advantage on fixed-price projects provides clear strategic clarity. Transcripts
HCL Tech's selective approach—walking away from unprofitable deals while building AI native capabilities toward a 25-30% revenue target—represents strategic patience. The company's five-pillar AI strategy and partnership with OpenAI provide foundation for longer-term positioning. Transcripts +1
Transitioning to outcome-based models isn't easy. Clients resist fixed-price contracts when AI tools create uncertainty around project scope and delivery timelines. Scope becomes harder to define when AI capabilities evolve continuously. Timeline predictability suffers when actual AI impact is difficult to forecast.
Companies are managing this resistance through different approaches. Cognizant uses a phased transition with pilot programs and hybrid contracts. Infosys leverages its Project Maximus value-based selling foundation and established benefit-sharing culture. Tech Mahindra's service token framework provides transparency that builds trust. HCL Tech takes a selective approach, focusing on clients ready for outcome-based partnerships. Transcripts +1
The next 12-24 months will prove critical. Companies that successfully build outcome-based capabilities while maintaining revenue visibility will capture premium positions in the post-T&M era. Those that struggle with the transition may find themselves competing on price in a declining traditional services market.
The fundamental equation has changed. In the AI era, better AI equals more value equals higher margins. Growth is no longer limited by talent availability but by AI capabilities. Margins expand through value creation rather than cost arbitrage. The companies that master this new mathematics will define the future of IT services.
