TCS and Infosys are taking opposite AI bets. Which one Wins?

Now, there are early signs the downturn may finally be bottoming out. Large deal pipelines remain healthy, client decision-making is improving, and most importantly, enterprise AI is beginning to move from pilot projects to production deployments.

But the next cycle won’t simply be about whether IT spending returns. It will depend on a more important question: how do enterprises choose to adopt AI? The answer could determine which IT companies emerge as the biggest winners over the next decade.

Tata Consultancy Services (TCS) and Infosys are both betting heavily on AI to revive growth. Yet they are pursuing fundamentally different strategies. One is investing across the AI infrastructure stack, aiming to become a long-term infrastructure partner for enterprises. The other is focusing on AI-native software transformation.

The market has yet to decide which approach deserves a higher valuation. In this article, we examine how TCS and Infosys are positioning themselves for the AI era, why their strategies differ, and what investors should watch as the next phase of India’s IT cycle unfolds.

Has the IT Downturn Really Bottomed Out?

There are growing signs that the worst is behind India’s IT industry. After the post-pandemic boom, the industry went through three difficult years as discretionary spending slowed and clients deferred technology investments. Revenue growth slowed sharply as companies struggled to convert healthy deal pipelines into faster execution.

Revenue Growth in Constant Currency Terms (in %)

Period	FY23 (YoY)	FY24 (YoY)	FY25 (YoY)	FY26 (YoY)	Q1FY27 (YoY)
TCS	13.7	3.4	4.2	-2.4	3.2
Infosys	15.4	1.4	4.2	3.1	2.4

Source: Company Presentation

After reporting a 2.4% decline in constant-currency revenue growth in FY26, TCS staged a strong recovery in Q1FY27, with revenue growing 3.2% year-on-year. Infosys, meanwhile, outperformed over the same period, delivering 3.1% constant-currency revenue growth in FY26, followed by a further 2.4% year-on-year increase in Q1FY27. While growth remains modest, it marks a clear improvement from the slowdown that defined much of the past three years.

Importantly, demand hasn’t disappeared. Large deal momentum has remained resilient despite the weak macro environment. TCS closed FY26 with total contracted value exceeding $40 billion and secured another $9.5 billion in Q1 FY27. Infosys signed a $14.9 billion deal in FY26 and $3.6 billion in large deals in Q1FY27, with nearly two-thirds of them net-new deals.

More importantly, profitability has held up far better than many expected. Despite slower revenue growth, both TCS and Infosys have consistently maintained their operating margins. Both companies have protected margins while continuing to invest in AI capabilities, putting them in a stronger position when demand normalises.

Steady Operating Margin Profile (in %)

Period	FY23	FY24	FY25	FY26
TCS	24.1	24.6	24.3	25.0
Infosys	21.0	20.7	21.1	21.0

Q1FY27 Profitability Snapshot (in %)

Period	Q1FY26	Q1FY27
TCS	24.5	24.0
Infosys	20.8	21.1

The tone of management commentary has shifted noticeably. Earlier calls were dominated by prolonged deal-closure cycles, deferred project starts, and cost optimisation. Today, both companies are talking about healthier deal pipelines, faster client decision-making and AI deployments moving from pilot programmes to production.

Why Revenue Growth is Sluggish Despite Large Deal Wins

One reason the recovery is proving gradual is that AI is changing the economics of traditional IT outsourcing. As legacy contracts come up for renewal, enterprises are increasingly demanding productivity-led price reductions because AI tools can automate routine coding, testing, and maintenance. In many cases, new AI projects are offsetting revenue lost from these legacy contracts rather than adding entirely new spending.

As a result, healthy deal pipelines are not yet translating into equally strong revenue growth. For both TCS and Infosys, the next phase of earnings recovery will depend not just on winning AI work, but on whether AI creates incremental technology spending rather than simply replacing existing IT budgets.

How TCS and Infosys Plan to Win the Next IT Cycle

While both companies agree that AI will define the next phase of growth for the IT industry, their earnings calls reveal two distinctly different approaches to monetising the opportunity.

TCS: Winning More From Existing Customers

Instead of limiting itself to being a software vendor, TCS is transforming itself into an industrial powerhouse. TCS is undertaking a broader approach by deploying a full-stack strategy dubbed “Infrastructure to Intelligence”.

Building the Power Grid of AI: HyperVault

Enterprise AI requires massive computing capacity. Rather than relying entirely on third-party cloud providers, TCS is investing directly in AI-ready infrastructure through a 1 GW HyperVault data centre. For the project, it has secured an investment commitment of $1 billion from private equity firm TPG.

It has also signed a multi-year deal with OpenAI to construct 100 MW of AI capacity (scalable to 1 GW) and partnered with AMD to bring its “Helios” rack-scale AI architecture to India.

Further, TCS is leveraging Tata Group synergies. It has partnered with Tata Power for clean energy, Tata Project (EPC construction), and Tata Communications (fibre network) to build data centres faster and greater capital-efficient.

This integrated ecosystem gives TCS a distinct advantage that few IT services companies can match. By combining AI infrastructure, energy, connectivity and software services under one umbrella, it is positioning itself as a long-term AI infrastructure partner rather than just an IT outsourcing vendor.

Turning AI into Earnings Growth

“Infrastructure to Intelligence” strategy is aimed at allowing TCS to defend its ground against software price compression. Traditional software contracts face 10-15% pricing pressure as AI tools automate routine coding. HyperVault provides multi-year, contract-backed infrastructural revenue that software automation cannot compress. Once built, HyperVault creates a steady and recurring cash-flow engine.

This is a capital-heavy bet that’s harder for smaller rivals to replicate at this scale. The strong margin discipline and cash flows also allow TCS to fund its own AI investments and offer competitive pricing during renewal negotiations.

Early signs are positive. TCS’s AI-linked business is running at an annualized revenue rate of roughly $2.6 billion, growing about 13.6% sequentially in Q1 FY27. Large and net-new transformation deals anchor this momentum. 

Infosys: Betting on AI-Native Software Work

While TCS is taking the physical AI infrastructure route, Infosys Ltd is taking a software-first approach. It is aggressively restructuring its services around pure-play AI software integration and legacy system modernization. In Q1FY27, the company’s pure-play AI services made up 8.2% of total revenue, compared to 5.5% in Q3FY26, showing the increasing velocity of AI services revenue.

Infosys’ strategy to capture the AI opportunity is built around two frameworks: Hexagon and Topaz Fabric.

The Hexagon AI Framework

Through Hexagon, Infosys has organised its AI offerings into six distinct service areas, ranging from preparing enterprise data and setting up AI governance frameworks to building AI agents for business functions. Importantly, Hexagon isn’t designed merely to automate existing outsourcing work. It is intended to help Infosys win entirely new AI transformation projects beyond legacy contracts.

The strategy is already gaining traction, helping Infosys to increase its revenue share of pure-play AI services.

The Topaz Fabric

Infosys management argues that enterprise AI models have outpaced corporations’ ability to safely deploy them. Most global banks, retailers, and healthcare majors run on fragile, decades-old code that cannot easily connect to modern AI tools. Using its Topaz Fabric platform, Infosys uses AI to automatically rewrite millions of lines of old code.

It has deployed over 80,000 developers who actively use advanced coding tools like Claude Code and Codex to rewrite legacy architectures. And, a specialized team of 6,000 frontier engineers skilled at integrating client business context with complex AI models.

Short-Term Challenges Remain

Despite the strong AI traction, Infosys faces near-term friction. It has revised down its FY27 constant currency revenue growth guidance to 1.5-3% from 1.5-3.5% due to cautious client spending, ongoing price compression on legacy renewals, and a one-off client termination in its Energy & Utilities vertical. Operating margin guidance, however, remains steady at 20-22%.

Infosys is also preparing for a leadership transition, with CEO Salil Parekh set to hand over the role to CEO-designate Ashiss Dash in April 2027. Investors will be watching whether the AI strategy maintains its execution momentum through the transition.

How the Market is Pricing In Each Strategy

Valuations: P/E and EV/EBITDA Trends

Name	P/E	5Y Median PE
TCS	16.3	29.9
Infosys	15.0	25.8

Both stocks are trading at steep discounts to their own five-year average valuation multiples. TCS currently trades at a price-to-earnings (P/E) ratio of 16.3x, around 45.5% below its five-year average. Infosys trades with its P/E multiple about 42% below the five-year average.

However, if we compare the valuations side-by-side, today the market is valuing TCS only modestly above Infosys despite their very different AI strategies. That suggests investors aren’t yet convinced infrastructure ownership deserves a significantly higher multiple than AI software integration.

So far, the market hasn’t chosen a winner. The market appears to be waiting for clearer evidence on which AI-led approach can translate into sustained revenue growth, margin expansion, and stronger earnings before assigning meaningfully higher valuation multiples.

The Verdict: Two AI Strategies, One Big Test

The next phase of growth for India’s IT industry will largely depend on one question: how enterprises choose to spend on AI.

If companies continue to modernise legacy systems and deploy AI within existing IT budgets, Infosys could have the edge. Its software-led approach and focus on AI agents and legacy code transformation position it well to capture this wave of demand.

However, if AI adoption drives a broader investment cycle in dedicated infrastructure, TCS could emerge as the bigger beneficiary. Its investments in AI infrastructure, combined with industry-leading margins and consistent execution, provide a strong platform to capture this opportunity.

The recovery in India’s IT sector is no longer just about when technology spending returns. It is increasingly about which AI strategy proves more durable. TCS is betting that owning AI infrastructure will create stickier, recurring revenue streams. Infosys believes the bigger opportunity lies in helping enterprises redesign their software around AI.

For now, however, the market isn’t declaring either strategy a winner. The next few quarters will therefore be crucial. Investors should watch whether TCS can scale its AI infrastructure into meaningful recurring revenue, and whether Infosys can win net-new AI transformation projects that expand its pure-play AI business. The company that demonstrates AI is creating new spending is likely to earn the market’s higher valuation premium. Add these stocks to your watchlist and monitor how they execute their growth plans.

Note: We have relied on data from www.Screener.in throughout this article. Only in cases where the data was not available, have we used an alternate, but widely used and accepted source of information.

The purpose of this article is only to share interesting charts, data points and thought-provoking opinions. It is NOT a recommendation. If you wish to consider an investment, you are strongly advised to consult your advisor. This article is strictly for educative purposes only. 

Deepan Datta has spent over a decade studying stocks and mutual funds. His passion is to uncover interesting stories in the financial markets and share them through his writings with investors at large. He is focused on delivering clear, easy to understand and research-backed insights. Deepan began his career as a Research Associate at S&P Global, where he developed a strong foundation in financial research and data analysis.

Disclosure: The writer and his dependents do not hold the stocks discussed in this article.

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