Tata Consultancy Services on Thursday reported a 13.9% year-on-year rise in June-quarter revenue to ₹72,275 crore, its fourth straight quarter of sequential growth, alongside $9.5 billion in fresh order bookings.
The country's largest IT services company also said annualised revenue from AI-led engagements crossed $2.6 billion, up 13.6% sequentially.
However, this is not the recurring revenue engine many think it is. Management says most AI engagements last only one or two quarters and must be continually replaced, rather than generating the steady annuity income typical of traditional IT outsourcing.
A pipeline, not an annuity
TCS added $75 million in AI revenue during the June quarter, nearly 40% lower than the $125 million added in the previous quarter. During the earnings call, chief executive officer K Krithivasan said AI engagements behave very differently from the rest of TCS's business.
Krithivasan said AI engagements are largely short-duration projects, typically lasting one or two quarters, which require TCS to repeatedly compete for new work rather than rely on long-term recurring contracts.
That distinction is important. Traditional IT outsourcing contracts typically generate predictable, multi-year annuity revenue. AI engagements, by contrast, resemble a rolling pipeline of short-term projects that must be replaced continuously. That also explains why quarterly additions can fluctuate significantly.
The Productivity Offset
Clients are beginning to realise measurable productivity gains after deploying AI within existing outsourcing contracts. Krithivasan said AI typically delivers productivity improvements of 10-15%, which are usually reflected during contract renewals.
In most cases, however, the resulting reduction in billed revenue is offset by clients awarding additional scope of work.
Krithivasan said TCS is still unable to quantify how much of its overall business has already undergone this AI-driven productivity transition. That remains one of the biggest unanswered questions for the industry. It will determine whether AI is expanding the IT services market or simply reducing traditional services revenue while creating new AI-related work.
Operating margin for the quarter came in at 24%, down 130 basis points sequentially. Chief Financial Officer Samir Seksaria attributed 170 basis points of that decline to the annual wage increment implemented during the quarter, Currency gains and operational efficiencies partly offset the impact.
The company said it continues to prioritise investments in AI capabilities, partnerships, platforms, and go-to-market capacity over near-term margin protection.
The FDE Way
TCS also plans to increase the share of employees working under a forward-deployed-engineer-style operating model, although chief operating officer Aarthi Subramanian said the company's approach differs from the model popularised by AI-native software firms.
She described TCS's ‘rapid-build engineer’ model as teams of multi-skilled specialists deployed in small squads to solve specific customer problems.
Subramanian said TCS is transitioning gradually to the new operating model and is already applying similar principles through its rapid-build methodology, with the framework expected to evolve over time. “At least 1% of our employee base, we would want to target to work in the new operating model,” she said.
Hiring Recovers, Headcount Still Lags
TCS added 9,279 employees during the quarter, its second consecutive quarter of net hiring. Total headcount stood at 593,798 as of June 30, still over 19,000 lower than a year ago.
Krithivasan said AI will reshape jobs rather than eliminate them.
“We do not believe that there would be a drastic reduction in employment. But people would be doing things differently,” He said.
The market responded positively, with all Nifty IT stocks trading higher after TCS announced its results. TCS shares gained over 4% in early trade on Friday.
The company has shown that AI can generate meaningful revenue at scale. What remains unproven is whether those revenues can eventually become as sticky and predictable as the annuity-driven outsourcing model that built India's IT services industry.
Until AI engagements evolve into long-term managed services rather than short implementation cycles, investors may view the business less as a recurring revenue engine and more as a pipeline that must be constantly replenished.