Indian IT is Tearing Up Its Billing Manual, But Unsure What to Charge Next

LTM, the technology services giant formerly known as LTIMindtree, recently launched an AI-linked commercial framework called BlueVerse Currency to enable outcome-based pricing in the agentic AI era. It soon followed up with BlueVerse for iRun, an AI-native managed-services platform built to automate technology operations rather than staff them.

The model folds together fixed and variable fees, subscription and managed services, and a mix of people, reusable accelerators, AI agents, orchestration platforms, and token-based compute into what the company calls a ‘single commercial envelope’.

It was the most recent confirmation of a discussion that has been building across India's outsourcing industry for months: the per-hour, per-head billing model that built the sector over three decades is running out of road.

India's $315 billion IT services industry is beginning to rewrite the commercial model that powered its rise, as artificial intelligence erodes the link between effort and value and forces companies to rethink how they charge clients. Kotak Institutional Equities said in a recent report that clients were increasingly demanding that productivity gains from AI be reflected in pricing during contract renewals. It estimates a 3–3.5% revenue impact for the Indian IT services industry over the next two fiscal years.

However, industry experts and insiders AIM spoke to remain divided on what comes next.

Sanchit Vir Gogia, Founder and CEO of consulting firm Greyhound Research, notes that the effort-based billing is not being totally abolished. Rather, the way business outcomes are measured is being diversified as agentic workflows radically compress timelines.

“The dominant model will not wear a single label. It will be hybrid: a fixed fee for access, a usage layer for tooling, an assurance layer for governance, and an outcome layer where the result can be measured and owned,” he tells AIM.

Further, he notes that the LTM launch is being misread. On inspection, it's a hybrid structure of fixed and variable components, agents, and tokens in a single envelope. 

According to global research and advisory firm Gartner, by 2028, over half of all enterprises will stop paying for assistive intelligence such as copilots and smart advisors, and instead will favour platforms that commit to workflow results. In this emerging model, Gartner noted that humans will move from completing work with procedural software to supervising intelligent systems that execute on their behalf.

“In this environment, execution authority is not a product feature. It is an architectural position that spans control over identity, permissions, policy enforcement, system-of-record access, and auditability,” Alastair Woolcock, VP Analyst at Gartner, said in a blog post.

A Work in Progress

IT services companies are still weighing their options. 

Nitesh Mirchandani, Chief Business Officer at Mindsprint, the Olam Group's technology and business-solutions arm, which was acquired by IT services major Wipro, says outcome-based pricing remains a work in progress rather than an established norm. 

"We are working with customers across several pricing models—be it managed services, be it fixed price, in some cases standard material, in some cases outcome-based or ROI-based as well. They are evolving as we speak," he explains. 

On whether the broader IT services industry is ready to move to outcome-based contracts, Mirchandani declines to make a blanket call, hinting that the ecosystem is still maturing in the wake of rapid AI adoption. 

"It depends on the maturity level of both the partner from a delivery perspective and the customer from a scope and programme management perspective," he adds. "If you have the right level of maturity on both the customer and the partner side, with the right scoping and the right delivery mechanism, that's where the model is possible."

Sandeep Poojary, Partner at Deloitte and the firm's Global Delivery Head for large-scale SAP implementations and generative AI initiatives, frames the choice as a contest between two logics rather than a settled direction.

"It all depends upon whether it will be outcome-based or it will be token-based," he shares, noting that delivery organisations are weighing both constructs actively. Outcome-based pricing is far from being certain. 

"We will not be concluding that outcome-based pricing will be a future, because the way tokenisation is changing, it will also depend on that. In the future, it will depend more on how many tokens you consume rather than how much capacity you have." 

The harder problem, he says, is figuring out how an outcome-based commitment sits on top of a token budget and the pass-through economics of large language models and hyperscalers, while still sharing efficiency gains fairly between provider and client.

"Nobody has been able to crack this outcome-based pricing so far," he claims. "Every moment we come up with something, there is another thing that comes up in the market." He adds that 2026 is a pilot year for these commercial models, with broader maturity expected in 2027.

Srinivasa Kattuboina, VP and Head of the Data and Analytics Practice at EPAM Systems in India, sees token-based pricing being applied in two distinct scenarios.

Where an engagement is about generating new business value, like entering a market, changing how a company operates, or getting ahead of competitors, clients largely stay out of the token economics.

The calculus changes when the engagement is about rationalising existing delivery, such as replacing a hundred-person managed-services team with a smaller group of experts working alongside AI agents. In those cases, he observes that customers start asking providers to fold token cost directly into the value proposition, effectively demanding proof that the agent-led model is cheaper than the full-time-equivalent headcount it displaces.

But all of that remains a work in progress.

For an industry that built its scale on the predictability of the time-and-materials invoice, the next two years will be about experimenting with different pricing models through a series of pilots, hybrid structures, and renegotiations rather than a single new standard. 

As Poojary of Deloitte put it, this year is all about testing.