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Our notes from meetings across India and Asia

Since we released our IT services sector upgrade (Time to buy the next cycle dated 24th Nov’25), we met a host of investors across India and Asia to discuss our investment thesis. In this note we list the key questions and debates: 1) Has the sector truly bottomed out, or is another leg of downward revisions still ahead? 2) If the GenAI services inflection is still 6-9 months away, why upgrade now? 3) Will GenAI drive deeper deflation than prior tech cycles, and can new services pools offset this? 4) Will the next leg of growth favor large caps, or can midcaps’ outperformance continue given the changing delivery model? 5) Is 3Q a genuine non-event, and when does the market get clearer signals for re-rating? As these points of discussion indicate, consensus remains unsure about the timing and the strength of recovery, and near-term data points continue to be limited. However, as argued in our note, traditional demand may remain soft in the next 3-4 months, but signs of an AI-services inflection at the enterprise level are already visible.

Cutting-edge LLM providers such as Claude and OpenAI are now beginning to open structured channel partnerships with system integrators, signaling that the services layer of AI is beginning to formalize. We believe this will pick up pace over the next six months, and we expect AI services demand to inflect in CY26.

Our top picks to play the next AI wave are HCLT and TechM in large-caps and Hexaware and Coforge in mid-caps.

Has the sector really bottomed out, or could earnings still see another leg down?

* Our View: Most of the negative news related to soft discretionary budgets, furloughs, and delayed pipelines is already baked into our estimates. Some downside is possible if demand does not turn around, but valuations at multiyear lows limit incremental risk unless macro conditions deteriorate materially from hereon.

If GenAI services inflect only in 6-9 months, why upgrade now?

* Our view: The sector could re-rate ahead of revenue inflection as deal announcements of AI services deals start taking shape. As shown in exhibit 4, our timelines for this turnaround are:

* 0-3 months (near-term): Furloughs and deal deferrals continue, with clients waiting for 2026 budgets to firm up. Little incremental demand is expected until Jan’26 when planning cycles reset.

* 3-9 months (2HCY26): Enterprises begin scaling AI services beyond pilots. Deal activity improves, with rising TCVs in application modernization, data engineering, and integration-led work. This marks the first tangible evidence of the transition from hardware to services.

* 2HFY27: AI-related deal conversion begins to show up in revenue. This is also when AI-linked productivity deflation begins to be offset by new AI services work. Large-cap revenue growth rates start improving toward the 6-7% range.

* FY28: AI services move into full deployment mode. Industry revenue growth rates materially accelerate to 8-9% (vs. 3–4% today) as AI modernization, data workloads, and enterprise integration scale up. This supports a sector-wide rerating as growth visibility improves.

* We see Mar-Apr’26 as the confirmation window, but think current levels offer a more favorable entry point.

Will GenAI compress revenue more sharply than cloud, making the 2016-18 analogy less relevant?

* Our view: GenAI is more disruptive and revenue deflation is unavoidable. However, the market may be underestimating the size of the new services pool, which will emerge from the implementation of GenAI.

* BPO and IMS in the cloud cycle were disrupted — cloud was a headwind early on, but it also unlocked new service lines such as data and cloud migration. We still expect sector growth to accelerate meaningfully during FY26-28E as these programs scale.

* We expect AI to have the highest deflationary impact across the ADM bucketas seen in exhibit 5, we expect 10-12% of revenue to be at risk over 3-4 years (2% hit to revenue each year). If the impact turns out to be higher than this estimate, it would be a risk.

Will large caps dominate execution again, or can midcaps take share?

* Our view: GenAI reduces delivery intensity and headcount dependence, which narrows the traditional scale advantage. With strong partnerships and domain capabilities, midcaps can compete more effectively than in previous cycles. However, large-scale implementation projects may still go to large caps with consulting strengths.

Is 3Q a non-event, and when do clearer signals emerge?

* Our view: 3Q is widely expected to be subdued, and we see limited incremental information coming through. More decisive signals should emerge in MarApr’26 as budgets reset, US banking commentary stabilizes and early AI implementation data points appear. This supports building positions ahead of that window rather than after it.

Valuation and View

* We believe we are at the bottom and the risks skew to the upside. Our analysis suggests outsized gains if this plays out, whereas the current levels already bake in the status quo (GenAI-led deflation, demand apathy).

* We have upgraded our growth estimates to factor in the anticipated recovery, which we expect to start reflecting in reported growth rates in 2HFY27 and take full shape in FY28 as enterprises move into full-scale AI deployments. We have also rolled over our target prices to FY28E EPS and increased our target multiples by ~20%.

* Our top picks to play the next AI wave: Hexaware and Coforge in mid-tier and HCLT and TECHM in large-caps.

Evidence of the AI services layer taking shape

* We note that major system integrators have begun announcing strategic partnerships with leading LLM providers such as OpenAI and Anthropic. These collaborations are expected to reshape delivery models and drive meaningful cost efficiencies.

* Recently, Accenture and OpenAI announced a collaboration under which Accenture professionals will be equipped with ChatGPT Enterprise to optimize operations and delivery execution while embedding ChatGPT across its consulting practices.

* Cognizant has signed a deep strategic partnership with Anthropic, rolling out Claude to 350,000 employees and embedding Claude to accelerate coding tasks, testing, documentation and DevOps workflows.

* We believe these developments are early signals that the AI services layer is beginning to take shape, and such partnerships are likely to deepen over time and expand across other system integrators as well.

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