Overview

For equity investors, AI stocks in India fall into a narrow set of listed companies that earn revenue from AI-led products and services, rather than pure-play AI developers. This guide covers the ecosystem, an artificial intelligence stocks list of five companies with dated financial data and a note on how clearly each discloses AI’s contribution, the criteria used to assess them, and the risks. Lists of the best AI stocks rarely separate AI-led revenue from general technology revenue, which is why each profile here carries a disclosure label. 

AI Stocks List: Five Companies and How Each Monetises AI

Company	Market Cap (₹ crore)	P/E (TTM)	ROE	ROCE	Debt/Equity	Dividend Yield	1-Year Price Change
Bosch	1,29,918	55.1	19.4%	16.6%	0.01	0.61%	+14.5%
Persistent Systems	88,421	49.0	22.9%	28.0%	0.07	0.70%	-1.1%
OFSS	84,323	24.7	47.4%	61.1%	0.00	4.13%	+13.7%
LTTS	41,486	27.0	23.2%	24.4%	0.08	1.48%	-3.5%
Affle 3i	19,054	39.9	13.8%	14.5%	0.00	0.00%	-30.4%

*Source: Jainam stock pages, 26 October 2026. One-year changes are price only, run to the capture date, exclude dividends and can differ by a few points across pages. ROE and ROCE are trailing figures per the provider’s methodology, covering the 12 months to 30 September 2026, and can differ from company-reported or fiscal-year ratios. A 0.00% dividend yield means none in the provider’s measurement window, not necessarily that no dividend has ever been paid.

Indian artificial intelligence shares differ widely in how much revenue AI actually drives. Each profile below ends with an AI exposure and disclosure label, and the financial data is as reported on the dates stated.

Bosch Ltd

Business and AI focus: Bosch Ltd is predominantly an automotive supplier, with powertrain, braking, sensors and electronic control units. AI appears in driver assistance, safety and braking software, and manufacturing automation.

Monetisation and strategy: AI value is embedded in components and software sold to vehicle makers, so growth depends on automotive volumes. The company acquired Bosch Chassis Systems Private Limited and announced a joint venture with the TSF Group.

Latest results: For the quarter ended 30 June 2026, revenue was ₹5,842 crore, up about 22% year on year. Profit before tax was ₹939 crore and profit after tax ₹702 crore, per Bosch’s results release as cited in review.

AI exposure and disclosure: AI embedded in broader products; AI-specific revenue is not separately disclosed. Examples may reflect the wider Bosch Group, not only Bosch Ltd.

Persistent Systems Ltd

Business and AI focus: Persistent is a digital engineering firm offering generative AI, cloud and data services, with platforms such as SAS VA for AI-assisted software engineering and a GenAI Hub.

Monetisation and strategy: Revenue comes largely from multi-year engineering contracts, with AI increasingly part of scope. Management has stated a $2 billion revenue ambition, which depends on organic growth and acquisitions such as the proposed Nagarro deal.

Latest results: For the quarter ended 30 September 2026, with results released on 15 October, revenue was about $487.6 million, up about 20% year on year, with an EBIT margin near 15%. Profit after tax fell about 25% year on year, while operating profit after tax was reported to have grown about 5%.

AI exposure and disclosure: AI embedded in broader services; whether SASVA and GenAI Hub are separately monetised is not disclosed in the sources reviewed.

Oracle Financial Services Software Ltd (OFSS)

Business and AI focus: OFSS sells core banking and analytics software, led by the FLEXCUBE platform, with AI used in fraud detection and risk analytics.

Monetisation and strategy: Revenue is mostly product licences and cloud offerings, with a shift toward Oracle Cloud Infrastructure (OCI) deployments.

Latest results: For the quarter ended 30 June 2026, reported revenue was ₹3,125.2 crore (up about 68.7% year on year) and net profit ₹1,415.5 crore (up about 120.5%). The filing and management commentary explain the drivers.

AI exposure and disclosure: AI embedded in broader products; AI revenue is not separately disclosed, and named AI capabilities should be confirmed from company documents.

L&T Technology Services Ltd (LTTS)

Business and AI focus: LTTS provides engineering services across mobility, sustainable technology and medical devices, with AI-led Engineering Intelligence (EI) solutions such as the EIOne platform and an EI lab with NVIDIA for physical AI.

Monetisation and strategy: The company reports annualised EI-led revenue of about $120 million and a five-year aspiration of 13% to 15% revenue CAGR.

Latest results: For the quarter ended 30 September 2026, revenue was ₹3,040 crore, up 12.1% year on year, with an EBIT margin of 16.3%. Net income of ₹548.2 crore includes a ₹165 crore one-time gain from the divestment of its SWC business. Large-deal contract value exceeded $200 million, over half AI-related.

AI exposure and disclosure: AI-related deal value disclosed. The share of large-deal value is not recognised AI revenue, and the $120 million EI-led figure should not be read as pure AI revenue.

Affle 3i Ltd

Business and AI focus: Affle operates a consumer intelligence platform that uses AI to match mobile advertising with user intent, including connected TV tools.

Monetisation and strategy: Revenue follows a Cost Per Converted User (CPCU) model, where payment depends on completed actions such as installs rather than impressions.

Latest results: For the quarter ended 30 June 2026, revenue was ₹747.2 crore, up 20.4%, and profit after tax was ₹128.4 crore, up 21.7%. Converted users were 12.4 crore, and EBITDA margin was 22.4%.

AI exposure and disclosure: AI embedded in broader products. CPCU is a monetisation model, not an AI metric, and the AI role in targeting or conversion prediction should be read from company disclosures.

Indian AI Market Ecosystem and Macroeconomic Drivers

One third-party estimate in industry coverage projects India’s AI market growing from roughly $7 billion in 2026 to about $35 billion by 2032, a 29.9% compound annual growth rate (CAGR). The original research provider, market definition and methodology could not be independently confirmed, and other providers publish materially different estimates, so the figure is a directional signal only. The policy backdrop is firmer: the IndiaAI Mission has an outlay of ₹10,371.92 crore over five years, and India hosts more than 2,100 Global Capability Centres (GCCs), over 1,200 with AI and machine learning capabilities.

Government Initiatives

The IndiaAI Mission funds shared compute, datasets, skilling and startups, with more than 38,000 GPUs onboarded for subsidised common use. About ₹400 crore had been released as of 9 February 2026, according to reports. That figure reflects funds released, not total spending or money reaching listed companies, so announced allocations should not be read as company revenue.

Skill Concentration

A NASSCOM report ranks India first globally in AI skill penetration and talent concentration. The source reviewed does not detail the methodology, and such a ranking is not the same as a ranking of research output or AI adoption.

Startup and GCC Landscape

The NASSCOM-Zinnov report estimates 2,117 GCCs in India, employing over 2.3 million professionals. Multinationals increasingly use these centres for AI work, supporting demand for data, cloud and engineering vendors.

How to Evaluate AI Stocks in India?

1. R&D expenditure ratio

Research and development spend as a percentage of revenue shows whether a company invests enough to stay current. Persistently low or falling ratios can signal weak technology sustainability, though the ratio is more comparable for product companies than for IT services firms, which may record investment differently.

2. Monetisation mechanics

Companies that earn directly from AI, such as Affle through its CPCU model or Persistent through its GenAI offerings, differ from passive adopters that use AI for internal efficiency.

3. Financial thresholds

Screening heuristics include debt-to-equity below 0.5 and return on equity above 20%, along with stable or rising operating profit margins. These are illustrative starting filters, not universal rules. ROE can be affected by leverage and buybacks, ROCE is often more informative for capital-heavy businesses, and comparisons work best within similar business models. In the table above, Bosch and Affle fall below the ROE benchmark despite low debt.

Risks

• Artificial intelligence shares can carry high valuations, rapid technology change and competition from global firms. 
• Generative AI may also reduce demand for routine coding services, so it can be a risk as well as an opportunity for IT vendors. 
• One-time gains and exceptional items can distort quarterly figures, as several results above show.

Conclusion

AI stocks in India are mostly established technology, engineering and software companies that monetise AI to varying degrees, so careful reading of results and disclosures matters more than the label. The AI stocks list above is best treated as a research starting point, since businesses, valuations and policy support change over time. Rather than ranking the best stocks in AI, the more useful exercise is judging how much evidence each company gives that AI contributes to revenue and profit.

Final Key Takeaways

• Scope: Indian AI exposure sites mainly in IT services, engineering, banking software, automotive and ad-tech firms.
• Ecosystem: The IndiaAI Mission outlay and over 2,100 GCCs support demand, though disbursement is gradual.
• Evaluation: R&D ratio, true AI monetisation, ROE, debt and margins separate AI leaders from passive adopters.
• Data: One-time gains and acquisitions can distort quarterly results, so filings should be checked.
• Risk: Valuations, technology shifts and client concentration remain central.

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Related reading is available in Jainam’s guide to AI trading in India.