Best AI Stocks in India for 2025: Top Companies to Watch

AI stocks in India are gaining attention in 2025 as companies across sectors adopt artificial intelligence to drive innovation and growth.

In this article, we will provide you with a list of AI stocks in which you can consider investing. If you’re only interested in the list, look at the table below. But we have also deep-dived into each of the companies mentioned in the table below, so you will probably want to stick around to read more about the companies you might choose to invest in. There’s a bonus strategy covered later on as well!

Best AI Stocks in India

The table below is a list of the best AI stocks in India for 2025.

We’ve chosen these companies based on a mix of their market capitalisation, analyst ratings, AI-driven initiatives, and relevance in the Indian context. The goal is to highlight businesses where AI is a key component of their core business strategy.

By the way, did you know that, as an Indian investor, you can invest in AI and other sectors in the USA as well? That’s right!

Through Appreciate, India’s best online trading app, you can invest in any US stocks of your choice, sitting right here in India. Download the Appreciate App today and learn more about the exciting opportunities!

Also Read: How to Invest in US Stocks from India

What is AI, and What are the Applications for It?

Artificial Intelligence (AI) is machines and software doing tasks that normally require human intelligence to perform well. The application prospects of AI are wide-ranging, from learning and problem-solving to speech recognition.

Globally as well as in India, AI is becoming a big part of everyday life through applications like virtual assistants, personalised e-commerce recommendations, and automated customer service chatbots. Across sectors, AI is being used to augment human capabilities. For example, in the agriculture industry, AI is able to provide farming advice with precision. In the healthcare industry, AI has been instrumental in making remote medical diagnosis possible.

The Indian government is pushing hard for AI innovation. The IndiaAI mission was launched under the Ministry of Electronics and is a flagship program with a budget of 10,300 crore (about $1.3 billion) to build AI infrastructure and skill ecosystems over five years. This mission aims to develop indigenous AI models (including vernacular language large language models), set up AI centers of excellence, and make high-performance computing (like thousands of gpus) accessible to startups and researchers. With such initiatives and a vibrant tech talent pool, India is poised to become a major player in the global ai race.

India’s AI industry has been growing exponentially. In 2018, the total spending in India on ai was around $665 million, and it is projected to reach nearly $11.8 billion by 2025. Industry reports suggest that AI could add over $950 billion to India’s economy by 2035. This is a reflection of just how transformative the technology could prove to be, especially in the mid to long term.

AI adoption is not limited to only tech companies, either. Banks, hospitals, retailers, and even government agencies are making use of AI to improve their efficiency, the productivity of their employees, and the services they offer. For example, Indian banks are using AI for fraud detection and credit scoring, and government programs use AI for language translation and agritech advisory. As the applications and use cases of AI increase, which looks only too likely to happen at the moment, the companies involved in building, maintaining and improving these technologies are expected to perform exceedingly well.

AI Industry Overview: Growth & Trends

Over the past decade, India’s AI industry has evolved from a nascent sector to a dynamic ecosystem of startups, IT services giants, and research institutions. A milestone was the 2018 National Strategy for AI released by NITI Aayog, which adopted the motto “AI for All” and identified priority areas like healthcare, agriculture, smart cities, and education for AI solutions. Since then, both the public and private sectors have increased their AI investments. Large IT companies such as TCS, Infosys, and Wipro have established strong AI divisions to build solutions for global clients, while a wave of startups is driving innovation in niche areas like computer vision, natural language processing (NLP), and generative AI.
In fact, India is now home to one of the world’s biggest startup ecosystems: over 3,600 deep-tech startups (which include AI ventures) are active, with 480 new deep-tech startups founded in 2023 alone​. This makes India the 3rd largest deep-tech startup hub globally, behind only the US and China. Crucially, India also leads in the talent arena – according to the Stanford AI Index 2024, India ranks #1 in AI skill penetration, with AI talent growing 263% since 2016​. This means a huge pool of engineers and data scientists are skilled in AI, providing the human capital needed for the industry’s growth.

Growth projections remain very optimistic. A joint report by NASSCOM and BCG estimates India’s AI market will grow at 25–35% annually, reaching around $17 billion by 2027. Enterprises are ramping up tech spending on AI/ML solutions, and demand for AI professionals is rising ~15% CAGR as organisations seek to implement AI in operations​.

We’re seeing AI being deployed in diverse Indian industries:

• Healthcare: AI tools for medical imaging diagnostics, predicting disease outbreaks, and telemedicine. For instance, AI-driven screening is used for diabetic retinopathy and tuberculosis in India’s hospitals.
• Finance: Banks use AI for fraud detection, algorithmic trading, credit risk analysis, and personalised customer service via chatbots. Insurance firms employ AI for faster claims processing.
• Education: EdTech platforms leverage AI tutors and adaptive learning to personalise education for students. AI-driven analytics also help identify learning gaps.
• Manufacturing & Logistics: Factories are adopting AI for predictive maintenance of machinery and quality control (using computer vision to detect defects). In logistics, AI optimizes route planning and demand forecasting for supply chains.
• Retail: Indian retailers and e-commerce companies use AI for inventory management, dynamic pricing, and recommendation engines to enhance customer experience.

Both startups and tech giants play complementary roles in this ecosystem. Startups focus on specialised AI products (analytics solutions, vision AI for retail, etc.), often partnering with bigger firms to scale their innovations. Meanwhile, the large IT service providers and global tech companies ensure AI gets integrated into enterprise solutions at scale.

It’s common to see collaborations – for example, mid-sized IT firms testing new generative AI tools internally before offering them to clients, or cloud providers like Google/Microsoft partnering with Indian companies to build AI competency centers.

Centers of Excellence (CoEs) for AI have been set up by the Government, and guidelines for ethical AI and data governance have also been developed. The aim of these initiatives is to be able to support innovation in AI, but at the same time, keep concerns like bias and privacy in check.

Overall, India’s AI industry is at an inflection point of high growth backed not only by strong government support and increased private investment, but also because of the availability of a rich talent pool.

Leading AI Stocks in India: A Detailed Overview

Analyst ratings provide insights into the potential growth and stability of a company based on comprehensive research and financial analysis. The following AI stocks in India have received high ratings from analysts in 2025, which makes them potentially attractive for investors looking to profit from the AI boom.

Affle India

Affle India is a mobile marketing and ad-tech (advertising technology) company that has put AI at the core of its platform. Affle operates a consumer intelligence platform that enables targeted mobile ads. In simple words, it helps marketers identify and acquire high-value users. The company’s use of AI is evident through its real-time predictive algorithms that analyse consumer data to deliver personalised ad recommendations.

According to a recent analysis, Affle uses its AI-driven platform with real-time predictive algorithms to target and convert users. This means the more data Affle’s platform gathers (e.g Users’ app usage patterns, clicks, installs etc), the smarter it gets at predicting which advertisement or app recommendation is likely to lead to a conversion (such as an install or purchase). For advertisers, this means a potentially higher ROI from their ad spend (we all love that as investors, don’t we?).

Affle has been expanding its capabilities through acquisitions and new product offerings. The intention behind these moves is mainly to boost its AI and machine learning prowess. Over the years, it acquired companies like Appnext, Mediasmart, and Jampp, and integrated their technologies into its own platform to improve ad targeting and fraud detection using AI.

The management’s strategic vision – dubbed Affle 2.0 – focuses on the two V’s – vernacular and verticalisation. Vernacular aims to create tailored content and ads in local languages (which is key in a multi-lingual country like India), and verticalisation means improving solutions for specific industry verticals by adding more depth to them. Both these thrusts rely on AI analytics to get deeper consumer insights across different segments, which Affle believes will positively impact its ROI.

For example, AI models analyse user behavior in tier-2 cities and can suggest vernacular language content that resonates better, or identify that a fintech app install ad performs best with a certain demographic.

Commentary from market analysts suggests that Affle’s strong focus on innovation in AI is a key reason it’s viewed as an attractive AI investment. A November 2024 stock coverage report highlighted Affles emphasis on non-walled garden advertising (outside big ecosystems like Google/Facebook), combined with expanding generative AI capabilities and OEM partnerships, positions the company to capture higher-value ad segments.

In practice, this could refer to Affle using generative AI to create better ad creatives or to dynamically personalise marketing content, as well as partnering with device manufacturers (oems) to embed its ad tech on devices. The company’s robust financial performance (double-digit revenue growth and healthy margins) further underscores its execution ability in this AI-driven advertising niche.

Overall, Affle India is a pioneer in AI-powered adtech in India its success will ride on continued innovation in machine learning algorithms, its ability to handle data responsibly, and scaling its platform globally (it already serves customers in over 20 countries).

Affle stands out for applying AI to digital marketing, which is a high-growth field as businesses continue to shift their advertising budgets online. These factors combine to make it one of the top AI stocks in India to watch in 2025.

The table below shows the financial performance of Affle India over the last 5 years (all figures in Millions INR):

Zensar Technologies

Zensar Technologies is a mid-tier IT services and solutions company that has embraced AI and automation as part of its digital transformation offerings. Headquartered in Pune, Zensar has traditionally helped global clients with software services, but in recent years it has developed specific AI-focused service lines.

The company now offers services in areas like advanced data analytics, intelligent automation, and generative AI. Zensar’s Data Engineering & Analytics segment explicitly includes offerings in AI/ML, automation, visualization, and even Generative AI services. This means Zensar helps companies build AI models, modernise their data platforms, and derive insights using techniques like machine learning.

For example, Zensar might implement an AI-based predictive maintenance system for a manufacturing client or a generative AI chatbot for a retail client’s customer service.

Zensar has also been proactive in building proprietary AI solutions. In September 2024, at the ISG AI Impact Summit in London, Zensar showcased a suite of in-house AI platforms​. These included:

• An Enterprise AI Engineering framework that leverages generative AI to modernise legacy systems
• a Multi-modal Generative AI capability to handle text, image, audio, and video data for decision-making
• a solution named ECHO (Enterprise Cognitive Hyper-Automated Operations) which integrates AI into business process automation​

The company also emphasises Responsible AI (ensuring AI outcomes are fair and transparent) as part of its offerings​. Showcasing these solutions underscores that “AI is central to our strategy for delivering transformative solutions,” as Zensar’s CEO put it in 2024​.

In practical terms, Zensar is blending AI with its expertise in cloud, application services, and IT infrastructure to help its clients become smarter enterprises. When it comes to partnerships, Zensar has aligned with major tech players, which strengthens its AI capabilities. It has strategic partnerships with the likes of Microsoft (Azure), AWS, Google Cloud, Adobe, etc., to jointly deliver solutions in cloud, customer experience, and data services​.

Many of these cloud platforms have AI and machine learning toolkits (for example, Azure ML or Google’s AI APIs), and Zensar, as a partner, can implement these for clients. Zensar’s collaboration with these giants suggests it stays at the cutting edge of AI trends (like adopting OpenAI’s services via Azure). The company has also been recognised in analyst reports for its innovation. It has a track record of partnerships and a focus on innovation, positioning Zensar for sustained growth in the AI landscape​.

In summary, Zensar Technologies serves as an integrator of AI into businesses, whether through custom solutions or leveraging third-party AI tools. Its role in India’s AI sector is that of an enabler, helping both local and global organisations adopt AI. As AI demand grows, Zensar’s ability to deliver end-to-end AI projects (from consulting to implementation and maintenance) will be a critical factor for its success. Investors view Zensar as a play on enterprise AI adoption – the more companies invest in AI/automation, the more Zensar stands to benefit by providing the expertise and services to execute those projects.

The table below shows the financial performance of Zensar Technologies over the last 5 years (all figures in Millions INR):

Persistent Systems

Persistent Systems is a well-known Indian IT company that specialises in software product development and digital engineering. It has a strong pedigree in building software for enterprise clients and has been aggressively expanding into the AI domain.

Persistent offers a broad range of services (cloud, data, security, etc.), and significantly it has developed a suite called Persistent.AI which provides AI solutions to its customers​. The goal of their AI offerings is to help clients automate processes, derive data-driven insights, reduce manual effort and enhance customer experiences​.

For instance, Persistent might implement an intelligent IT operations system for a client (they have something called Pi (Persistent Intelligent) Ops) to automate and predict IT issues, or use AI to optimise software testing and development workflows.

One notable initiative is that Persistent launched a Generative AI Hub in 2024. This hub is essentially an innovation center and platform aimed at accelerating development of generative AI applications for enterprises​.

The GenAI Hub allows Persistent to prototype solutions using large language models (LLMs) and integrate them into business use cases quickly. According to a report, the hub supports various cloud AI services and models, enabling domain-specific generative AI solutions and providing a “playground” for clients to experiment with LLMs​.

This forward-looking approach indicates that Persistent is positioning itself as a leader in helping companies adopt cutting-edge AI (like GPT-like models) safely and effectively. In addition, Persistent has been recognised by industry analysts (like ISG and HFS) as a leading provider in AI and generative AI services​, underlining its credibility in this space.

Persistent’s strategy also involves partnerships and acquisitions to bolster AI capabilities.

• In late 2024, Persistent partnered with CoRover.ai, a startup known for AI-based chat platforms, to develop multilingual conversational AI solutions for enterprises.
• This partnership is about combining CoRover’s chatbot and language AI expertise with Persistent’s integration and scale strengths – resulting in advanced AI chatbots that can cater to India’s diverse language landscape and beyond.
• On the acquisition front, Persistent acquired a few data and cloud companies in recent years (such as Data Glove and Sureline) to strengthen its cloud and data engineering practice, which complements its AI work by ensuring robust data pipelines and platforms for AI.

The company’s leadership has explicitly stated that the ongoing “AI revolution” will be a key growth driver for Persistent Systems going forward.

Overall, Persistent Systems stands out as one of India’s top AI service providers and a proxy for enterprise AI adoption globally. The company blends product development DNA with AI expertise, meaning it not only consults on AI but can also build and engineer AI-powered software products for clients.

With operations spanning the US, Europe, and Asia, Persistent also brings a global perspective to AI solutions. In India’s AI sector, Persistent’s relevance is significant – it is cultivating homegrown AI innovation (through its GenAI hub and partnerships) and exporting that expertise worldwide.

For investors, Persistent offers exposure to a company that is benefiting from the surge in demand for AI/ML implementation across industries, backed by a consistent track record of revenue growth and high return ratios​.

The table below shows the financial performance of Persistent Systems over the last 5 years (all figures in Millions INR):

Bosch

Bosch Ltd. is the Indian subsidiary of Robert Bosch GmbH (Germany), and is primarily known as a leading supplier of automotive and industrial technology.

At first glance, one might not associate this century-old automotive components maker with cutting-edge AI. However, Bosch (both globally and in India) has been a pioneer in adopting AI and Industry 4.0 practices in manufacturing.

The company has a global program called Bosch Center for AI and has even mandated AI upskilling for its engineers worldwide. In India, Bosch has leveraged AI to make its factories smarter and its products more intelligent. Here are 3 examples of the same:

• Bosch’s flagship plant in Bidadi, Karnataka implemented advanced analytics and artificial intelligence to detect manufacturing defects on the assembly line​. By analysing sensor data and images on production lines, AI algorithms can catch product defects in real-time, thus improving quality control and reducing rework.
• Another Bosch plant in Nashik uses AI-driven safety systems (behavioral analysis to prevent accidents), illustrating the breadth of use-cases from quality to safety.
• On the product side, Bosch is embedding AI in areas like automotive safety (think of driver-assistance systems), energy management, and consumer products (like appliances that optimise settings via AI).

A notable development in 2024 was when Bosch’s R&D arm in India, Bosch Engineering and Business Solutions, launched a product called Phantom Edge – an AIoT platform that combines AI and Internet of Things to monitor electrical energy usage in real time​. Phantom Edge uses machine learning algorithms on sensor data (current, voltage etc.) to create a “digital twin” of machines and appliances, providing insights into energy consumption, predictive maintenance, and even early warning of malfunctions​.

It’s deployed in industries like healthcare, agriculture, retail, and factories to save energy and improve uptime. This is a great example of Bosch India innovating an AI-driven product that caters to the Industry 4.0 trend.

Bosch globally has also committed to AI training and ethics – by 2025, Bosch aimed to train 20,000+ associates in AI and set guidelines for “safe and trusted AI”. Such global initiatives spill over into Bosch’s India operations, giving Bosch Ltd. an edge in know-how.

Moreover, Bosch is working on autonomous driving and smart mobility, where AI is crucial (for sensor fusion, vision, etc.). While Bosch Ltd. (the listed entity) mainly does automotive components manufacturing, it benefits from the Bosch Group’s global R&D (some of which is done in Bangalore).

As India moves toward connected cars and possibly autonomous features in future vehicles, Bosch’s AI-infused automotive solutions (like ADAS – Advanced Driver Assistance Systems) could find a large market.

In summary, Bosch may not be an “AI company” in the narrow sense, but it is deeply leveraging AI to transform manufacturing processes and product capabilities. It serves as a bridge between traditional industry and new technology in India.

For investors, Bosch Ltd. offers exposure to industrial AI and IoT applications in India. Its relevance in the AI sector is that of a practical implementer – showcasing how AI can drive tangible improvements in efficiency and quality in manufacturing, and delivering AI-enhanced products (like smarter factories, power tools, or automotive systems) to the market.

With strong support from its parent and a culture of innovation, Bosch is ensuring it won’t be left behind in the AI era even as it leads in its legacy businesses.

The table below shows the financial performance of Bosch over the last 5 years (all figures in Millions INR):

Oracle Financial Services Software (OFSS)

Oracle Financial Services Software is an India-based subsidiary of Oracle Corporation that focuses on providing software solutions to the financial services industry.

It is best known for its core banking platform “Oracle FLEXCUBE”, which is used by banks worldwide for everything from retail banking operations to online banking.

In recent years, OFSS has been infusing more AI and analytics into its product suite to help banks and financial institutions improve their decision-making and efficiency. For example, Oracle’s financial crime detection software now uses AI/ML to spot unusual transactions.

In March 2025, Oracle Financial Services announced it is “supercharging its Investigation Hub cloud service with AI agents and agentic workflows” to help banks fight financial crime​. These AI agents use techniques like generative AI and pattern recognition to automate large parts of investigating suspicious transactions (like anti-money laundering checks), which traditionally took analysts many hours. By augmenting human investigators, the AI can sift through vast datasets, flag complex patterns of fraud, and thus improve both the speed and accuracy of compliance processes​. This is crucial as banks face increasingly sophisticated fraud schemes and regulatory scrutiny.

OFSS is also integrating AI into its core banking and insurance products. The company has been promoting AI-based enhancements to its flagship core banking software (FLEXCUBE) for global expansion​.

In practice, this could mean features like:

• AI-driven customer service in banking apps
• AI algorithms for credit risk scoring built into the core system
• Using machine learning to optimise treasury operations

Oracle’s broader cloud offerings (OCI – Oracle Cloud Infrastructure) also have AI services, and OFSS can leverage those for its clients. It’s worth noting that Oracle was recognised as a #1 vendor for innovative AI technology for financial institutions in certain categories​, which likely includes contributions from OFSS’s products.

From a strategic perspective, Oracle Financial Services Software serves as a bridge between global cutting-edge tech and Indian IT talent. Many R&D and engineering tasks for Oracle’s fintech products happen in India through OFSS, which means the company is at the forefront of applying AI in banking contexts. It has also entered partnerships with local and regional banks in emerging markets, bringing AI solutions to those customers.

For instance, an Asia-Pacific bank implementing OFSS’s software can now automatically get fraud detection AI and digital assistant features built-in, thanks to OFSS’s updates. In India’s AI sector, OFSS is significant as a product company (as opposed to service provider) that exports financial software worldwide. It underscores how Indian engineers are building AI-powered financial software used by multinational banks.

For investors, OFSS offers exposure to the fintech side of AI – benefiting from global trends like digital banking, fintech adoption, and regulatory tech. The company is consistently profitable and pays dividends, indicating a stable financial footing even as it innovates.

Its relevance will continue as banks universally are looking to AI for better risk management, personalised banking (like AI-based recommendations to customers), and operational efficiency. As long as Oracle remains committed to leadership in AI for enterprise software, OFSS will remain a key asset in bringing those innovations to the financial domain.

The table below shows the financial performance of Oracle Financial Services Software over the last 5 years (all figures in Millions INR):

Tata Elxsi Ltd.

Tata Elxsi is a part of the Tata Group and is known for its work in design and technology services, especially in areas like automotive engineering, media & entertainment, communications, and healthcare. Tata Elxsi has been increasingly leveraging AI across all these sectors as an enabler of next-generation products and services. One of the marquee focus areas for Tata Elxsi is autonomous vehicles and automotive software.

In October 2024, Tata Elxsi signed a collaboration with Foresight (an Israeli tech company) to develop advanced driver-assistance and autonomous driving solutions using Foresight’s stereoscopic vision technology and Tata Elxsi’s system integration expertise​. In practical terms, Tata Elxsi will help integrate AI-based vision software (that detects obstacles, lane markings, etc. using cameras and neural networks) into vehicles – including vehicles made by Tata Motors. The initial projects involve enhancing ADAS features in passenger cars, heavy machinery, and agricultural vehicles, with plans to move towards semi-autonomous and fully autonomous systems over time​. This partnership highlights Tata Elxsi’s role in bringing AI to India’s automotive industry, which is a huge emerging opportunity as cars get smarter.

Another domain is communications and networking. Tata Elxsi has developed an AI-enabled platform called NEURON for telecom operators​. NEURON is essentially a telco cloud and network automation suite that uses AI/ML (and even GenAI) to enable autonomous network operations – for example, automating a 5G network’s operations center by predicting faults and healing the network, or optimising the deployment of network resources. NEURON was recognised for features like Telco Cloud and Dark NOC (network operations center automation) which are “powered by Gen AI, offering smart interactions and AI/ML algorithms for predictive intelligence”​. By integrating such AI capabilities, Tata Elxsi helps telecom clients manage complex networks with minimal human intervention, a big efficiency booster for the telecom sector.

Tata Elxsi is also active in media and healthcare verticals with AI.

• In media, it works on video analytics, personalised content recommendation engines, etc.
• In healthcare, Tata Elxsi has worked on AI for medical imaging and digital health platforms. The company’s design background also means they focus on human-centric AI design – ensuring UI/UX and AI work together (important in fields like automotive where AI decisions need to be interpretable to drivers).

Globally, Tata Elxsi frequently partners with technology providers to keep its edge. It has partnerships with semiconductor firms (for example, a collaboration with ARM in 2024 to develop software-defined vehicle technology) and with research institutions for AI. It also set up innovation labs like an XR (extended reality) and AI lab called “Coalesce” to combine AI with AR/VR for immersive experiences​.

In terms of commentary, Tata Elxsi is often cited as a unique mid-cap company that sits at the intersection of engineering and AI. It doesn’t market standalone AI products, but rather infuses AI into the solutions it creates for clients (e.g., an AI algorithm inside a car’s infotainment system or a set-top box UI). Its financial performance has been strong in recent years, partly due to the high demand in segments like automotive electronics and streaming (where it serves global clients). Tata Elxsi’s relevance to India’s AI sector is significant: it demonstrates homegrown innovation in high-tech fields and shows that Indian companies can contribute to frontier technologies like autonomous driving, 5G, and Industry 4.0 on the world stage.

For investors, Tata Elxsi provides exposure to a blend of AI, design, and engineering in multiple high-growth domains. However, the company must continuously invest in upskilling and R&D to stay ahead, as these fields are very competitive globally.

The table below shows the financial performance of Tata Elxsi Ltd. over the last 5 years (all figures in Millions INR):

Kellton Tech Solutions

Kellton Tech is a smaller, fast-growing IT company that is heavily focused on digital transformation and emerging technologies. While much smaller in market cap compared to names like Tata Elxsi or Persistent, Kellton has carved a niche in implementing solutions in AI, analytics, and enterprise software for clients in various industries. Kellton Tech’s services include things like software development, cloud migration, enterprise resource planning (ERP) implementation, and increasingly, AI & ML implementation for businesses​.

In essence, they help other companies leverage digital tools to transform their operations – for example, using AI to automate a customer support process, or integrating a machine learning model into an e-commerce platform to personalise user experience. One source describes Kellton Tech as an Indian company that helps businesses with digital transformation and AI/ML implementation, also offering SAP, outsourcing, and digital commerce services​. This highlights that Kellton often works at the convergence of AI with other enterprise systems like SAP (ERP software) or e-commerce platforms. For instance, Kellton might implement an AI-based demand forecasting module on top of a client’s SAP inventory system, or build a recommendation engine for a retailer’s online store.

With over 10 international offices and clients globally​, Kellton has a footprint beyond India which enables it to service companies in the US, Europe, etc., often at competitive cost with its India-based talent. Kellton Tech has shown commitment to staying on the cutting edge – they invest in innovation labs for AI and IoT, and have executed projects in areas like chatbots, predictive analytics, and blockchain.

In the last couple of years, they’ve been involved in developing AI-enabled mobile apps and analytics dashboards that incorporate machine learning. Kellton’s agility as a smaller firm allows it to experiment with new tech trends quickly, though it also means reliance on a few key clients (hence higher business risk).

While there might not be a lot of mainstream media commentary on Kellton (since it’s not a very large company), the company’s financials and growth are closely watched by tech-focused investors. It has delivered strong revenue growth rates, indicating demand for its services. Analysts note that Kellton is at the “forefront of pioneering advancements in AI technology”, and drives digital transformation through AI-based solutions​. Its strategy seems to be focusing on being a one-stop provider for mid-size enterprises looking to implement modern IT systems underlined by AI capabilities.

In India’s AI ecosystem, Kellton Tech represents the vibrant startup and mid-tier segment that directly works on AI projects. It shows that not only giant companies, but also relatively smaller firms, are contributing significantly by building practical AI solutions for businesses. For investors, Kellton Tech is a higher-risk, higher-reward play on AI – its smaller size means it could grow faster percentage-wise, but it also faces stiffer competition and must differentiate itself against both larger Indian IT firms and other startups.

Key factors for Kellton will be maintaining technical excellence (attracting skilled AI talent), scaling its client base, and possibly moving from purely service-based projects to developing its own AI platforms or products to improve margins.

The table below shows the financial performance of Kellton Tech Solutions Ltd. over the last 5 years (all figures in Millions INR):

Cyient Ltd.

Cyient is an engineering, manufacturing, and technology solutions company that has been undergoing a transformation to embed more digital and AI capabilities into its services. Historically known for engineering design and outsourcing (it was formerly Infotech Enterprises, providing drafting/design services to aerospace and telecom companies), Cyient now brands itself as a provider of “intelligent engineering” solutions. This implies using advanced technologies like AI, IoT, and data analytics to design, build, and maintain industrial products and infrastructure.

Cyient serves over 300 global customers across industries like aerospace & defense, rail transportation, telecommunications, utilities, and healthcare​. A good illustration of Cyient’s AI push is their development of an analytics platform and capabilities in data-driven decision making. The company has an innovation hub called CyientifIQ, and through it, they deliver AI solutions to clients, claiming to increase the speed and accuracy of systems with augmented analytics and intelligent automation​.

For example, Cyient might implement an AI-based predictive maintenance system for an airline (monitoring aircraft sensor data to predict component failures), or provide a telecom with AI algorithms to optimise network performance. Cyient was even recognised in 2023 for leadership in Data Analytics and AI, outpacing competitors in Generative AI in certain industry analyst rankings​.

Cyient has also been active in strategic partnerships and acquisitions to bolster its AI and high-tech offerings. It made news in late 2024 by acquiring a 27.3% stake in Azimuth AI, a semiconductor design company focusing on intelligent power solutions​. This move is aimed at strengthening Cyient’s capabilities in developing cutting-edge ASIC chips (Application-Specific Integrated Circuits) that could be used for AI and IoT applications​.

Essentially, Cyient is investing in the hardware side of AI to complement its software services – a notable strategy because it aligns with India’s push for domestic semiconductor and chip design expertise. Furthermore, Cyient signed a Letter of Intent with Thales, a global tech leader, to collaborate on advanced technologies (in 2024) – initially this was framed around sustainability and low-carbon solutions, but working closely with a company like Thales likely gives Cyient opportunities to work on AI projects in defense and aerospace domains​.

In terms of services, Cyient offers AI solutions like computer vision (e.g., automated inspection of infrastructure via drone images), natural language processing (for knowledge management), and data analytics platforms for industries. An interesting area is edge AI for industrial IoT – Cyient has discussed how organisations benefit from processing AI on the edge (closer to machines), which ties into their work with manufacturing and utilities​.

From a market standpoint, Cyient is viewed as an engineering stock with a digital twist. The commentary around it often highlights how it is successfully moving up the value chain from low-cost outsourcing to delivering high-value, IP-driven solutions using AI and digital tech. Cyient’s financials have improved as it shifted to this higher margin work (Digital and Mechanical engineering now form a big part of revenues).

Its relevance in India’s AI sector is notable because it exemplifies how traditional engineering firms are reinventing themselves through AI. It also contributes to sectors like defense and smart manufacturing which are priorities for India. For investors, Cyient provides exposure to themes like Industry 4.0, smart networks, and digital engineering, all underpinned by AI/ML.

The key for Cyient will be to continue integrating new technologies (like generative AI, 5G, etc.) into solutions for legacy industries, thereby staying ahead of the curve and relevant to clients looking to modernize.

The table below shows the financial performance of Cyient Ltd. over the last 5 years (all figures in Millions INR):

Saksoft Ltd.

Saksoft is an Indian IT company focusing on digital transformation, business intelligence (BI), and information management services. It primarily caters to mid-tier businesses and enterprises, helping them to harness their data and automate processes. Over the years, Saksoft has evolved from a pure play software testing and business intelligence provider into one that offers a wider array of digital solutions, including application development, cloud services, and increasingly, AI and machine learning solutions​.

Its sweet spot is combining data analytics with intelligent automation – essentially using AI/ML to derive insights and then embedding those insights into business workflows. The company emphasises improving the speed, accuracy, and predictability of IT systems for its clients using advanced tech.

A profile of Saksoft mentions that it “focuses on increasing the speed, accuracy, and predictability of IT systems using Enterprise Applications, Augmented Analytics, and Intelligent Automation,” and that their AI, Machine Learning, and Generative AI products are running in companies worldwide​. This is a strong statement underscoring that Saksoft has developed AI-driven products (or software platforms) and successfully deployed them globally, not just in India. For example, Saksoft might have a generative AI based report-generation tool for financial services or an AI-powered data analytics platform that it offers to clients as a product.

One of Saksoft’s growth strategies has been through acquisitions to add niche capabilities. In recent times, it acquired a company called Augmento Labs (specialised in digital engineering and cloud) and CEPTES Software (a Salesforce cloud expert)​. These acquisitions broaden Saksoft’s offerings in cloud and SaaS, which complements its AI and analytics services. By integrating acquired teams, Saksoft can deliver end-to-end digital solutions – for instance, building a cloud-based analytics solution where data is collected, processed (maybe by AI algorithms), and visualised for decision makers.

Saksoft operates in sectors like BFSI, healthcare, e-commerce, and government – areas where data-driven decision making is vital. A typical Saksoft project might be building a data warehouse for a bank and then layering AI models for fraud detection or customer segmentation on top of it. Or developing a dashboard for a hospital that predicts patient footfalls and optimises staffing (using historical data and ML). They also do a lot of work in software testing and quality assurance, which they are now augmenting with AI (like using AI tools to automatically generate test cases or detect anomalies in software behavior).

Financially, Saksoft has shown steady growth, and its return ratios (ROE ~17%​) indicate efficient management for a company its size. Market analysts and investor communities (even forums like Reddit) sometimes call Saksoft a “small-cap AI/ML & Data powerhouse”, reflecting its strong positioning in these high-demand tech segments​. Its future plans include scaling up in the digital transformation value chain – possibly offering more end-to-end solutions rather than point services, and expanding in Western markets.

In India’s AI landscape, Saksoft is emblematic of the small-cap innovators that quietly build and deploy AI solutions across the world. It may not have the name recognition of bigger firms, but it punches above its weight in delivering critical AI-powered systems (especially in BI and analytics). For an investor, Saksoft provides a more focused exposure to AI in enterprise data analytics. The company’s success will depend on staying ahead in technology (like adopting new AI techniques such as GPT-3/4 for enterprise use, which they appear to be doing with generative AI mentions) and continuing to win trust from medium-to-large clients in an extremely competitive market. If it executes well, Saksoft could ride the AI wave and potentially grow into a much larger entity.

Investment Strategies in AI Stocks

Investing in AI stocks, especially in a growing market like India, can be approached in several ways. Here are a few investment strategies to consider for exposure to the AI theme:

• Thematic Investing via Baskets: One convenient way to invest in a range of AI-focused companies is through thematic portfolios or baskets. For example, platforms like smallcase offer ready-made baskets of stocks (called smallcases) targeting specific themes – there are smallcase portfolios for Artificial Intelligence stocks that include a mix of companies involved in AI. Investing in such a basket gives you diversified exposure within the AI theme (spreading across software, hardware, large-cap, mid-cap etc.) without having to pick individual stocks. It also ensures you don’t miss out on segments of AI (for instance, a basket might include IT services, chipmakers, and internet companies together for a holistic play).
• Diversification and Sectoral Mix: While AI is a compelling growth theme, it’s important not to put all your eggs in one basket. Within an equity portfolio, maintain a diverse sectoral allocation. AI stocks mostly fall under tech sector (IT services, software) or industrials (for those like Bosch). Make sure you balance your portfolio with other sectors (finance, consumer, pharma, etc.) to cushion against any one sector downturn. Even within AI stocks, diversify across types of companies – e.g., hold a couple of large-cap tech firms that are heavy on AI (which may be more stable) along with some emerging mid-caps like the ones discussed (which have higher growth potential but also higher volatility).
• Long-Term Core vs Tactical Positions: Consider splitting your AI investments into core and tactical. Core holdings could be established companies you intend to hold for the long term (for instance, a top IT services company with strong AI capabilities, or a global tech player). Tactical positions could be smaller thematic bets like a fast-rising AI product company or a startup-like stock – these you might hold for shorter horizons to capitalise on specific news or product launches (say a company wins a big AI project or releases a breakthrough AI product). This approach ensures you benefit from long-term compounding of winners, while also taking advantage of shorter-term opportunities in the AI space.
• Global Exposure for a Complete Play: The AI revolution is global – many of the cutting-edge developments (advanced semiconductors, cloud AI services, etc.) come from companies in the US, Europe, or Asia ex-India. An investment strategy could be to combine Indian AI stocks with international AI leaders. For instance, you might pair Indian AI stock exposure with some US tech giants (like Nvidia, Microsoft, Alphabet) or Chinese AI players, to create an “AI super-portfolio.” Nowadays, Indian investors can easily invest in US stocks through global investment platforms. (A soft mention in this context: platforms like Appreciate allow Indian investors to invest in diversified portfolios across India and the US, including fractional shares of US tech stocks, enabling one to build a truly global AI-themed portfolio.) By doing this, you hedge your bets – if AI adoption in India takes longer, perhaps your US AI stocks will compensate, and vice versa.
• Use of Mutual Funds/ETFs: If picking stocks or thematic baskets feels too hands-on, one can opt for mutual funds or exchange-traded funds (ETFs) that cover technology and innovation. In India, there are a few tech sector funds, and globally, there are ETFs specifically focusing on Robotics & AI. While in India there isn’t yet an AI-dedicated mutual fund, investing in a Technology fund (which often has high allocation to companies doing AI) or an International fund with a theme like Nasdaq-100 (many Nasdaq companies are AI frontrunners) can be an indirect way to ride the AI wave with professional management.

In crafting your strategy, consider your risk tolerance and time horizon. AI as a theme will likely play out over many years – so a patient, long-term approach with periodic reviews generally works best. You might also take a phased investment approach (SIP/STS) instead of lump sum, to mitigate timing risk given these stocks can be volatile around news cycles.

Factors to Consider Before Investing in AI Stocks

Investing in AI-related companies requires the same diligence as any other stock, plus some additional considerations given the nature of the industry. Here are key factors a prudent investor should evaluate:

• Financial Strength and Fundamentals: Examine the company’s financial health – revenue and profit growth, margins, debt levels, and cash flow. Many AI companies (especially smaller ones or those heavily investing in R&D) might have volatile earnings. It’s important to ensure the company has a solid balance sheet to sustain heavy R&D or withstand periods of losses if they are in growth mode. For example, check if the company is consistently growing its top line (a sign of market adoption of its products/services) and whether it’s managing expenses well. Strong return ratios (like ROE and ROCE) are a bonus, as seen in some of the companies above, indicating they use capital efficiently in this high-tech business.
• Competitive Landscape and Moat: AI is a competitive field. Assess who the company’s competitors are and what differentiates this company. Does it have proprietary technology or patents? Is there a high barrier to entry in its niche? For instance, a small AI product company might be competing against giants like Google or IBM – in such cases, the smaller company should have a unique niche or first-mover advantage. Consider also competition from global players, since AI solutions can often cross borders easily (software isn’t constrained geographically). A strong moat could be in the form of specialised expertise, long-term contracts with clients, or integration into critical systems that make it hard for customers to switch providers.
• Market Leadership and Client Base: Within its segment, is the company a leader or a minor player? Market leaders often enjoy better pricing power and more resources to invest in innovation. Check the client base – a company serving large, reputable clients or governments on AI projects has credibility (and likely steady revenue streams), whereas one concentrated in a few startups might be riskier. Companies like TCS or Infosys (as large-caps) have diversified clients and are likely to be involved in many AI projects for big enterprises – they offer stability. On the other hand, a company that derived a large chunk of revenue from one or two AI projects could be high-risk if those projects end.
• Innovation and Talent: AI industry runs on innovation. The quality of talent (data scientists, AI researchers) a company has and its commitment to R&D are crucial. An investor can look at indicators like R&D spending as a percentage of revenue, partnerships with academia or tech labs, and how frequently the company launches new products or features. If possible, follow their announcements – e.g., are they keeping up with trends like generative AI, edge AI, etc.? A company that invested in AI five years ago but hasn’t evolved to current AI trends might fall behind. Also, consider if the company is attracting and retaining skilled personnel – high attrition of top engineers could be a red flag.
• Ethical AI Practices and Governance: AI carries ethical considerations – misuse of data, algorithmic bias, etc. Reputed companies tend to have frameworks for Responsible AI (for example, they might have an AI ethics board, or follow government guidelines like NITI Aayog’s principles for responsible AI). From an investment standpoint, companies that proactively address ethical AI and data privacy are less likely to face regulatory backlash or reputational damage. For instance, if a company’s AI algorithm was found to be discriminating unfairly, it could lead to lawsuits or loss of business. Check if the company has statements or policies on ethical AI usage, data protection compliance (especially relevant with India’s new Data Protection law and global regulations like GDPR), and how transparent they are about their AI systems. Strong governance in this area is a plus because it indicates the company is managing risks associated with AI.
• Regulatory Landscape: Keep an eye on the regulations and government policies related to AI. While currently India does not have restrictive AI regulations, this could change as AI becomes more prevalent. The IndiaAI Mission, for example, while mostly promotional, also indicates the government’s interest in safe AI. If down the line there are compliance requirements (say, mandatory audits of AI algorithms in sensitive sectors), companies will need to adapt. Also, consider sector-specific regulations: AI in healthcare or finance might be subject to more oversight (e.g., approvals needed for AI diagnostic tools). Companies operating in those areas must be capable of navigating regulatory hurdles. Additionally, export regulations (for those serving global clients) or import of technology (like chip import rules) can impact AI businesses. An investor should favor companies that show agility in their compliance and regulatory awareness – often reflected in management commentary during annual reports or investor calls.

In summary, before investing in an AI stock, do thorough homework: analyse financials, understand what exactly the company’s AI offering is and why it’s special, see how it stands against competition, and ensure it has robust practices to handle the fast-evolving tech and regulatory environment. Because AI is an evolving field, also be prepared to continuously monitor these factors – a company leading today could be overtaken if it misses a technological shift. Thus, staying updated is part of the investment process in AI stocks.

Conclusion

Investing in AI stocks has the potential to generate excellent returns over the next few years. But you need to be careful about the stocks you invest in, and be sure to invest for the long term. Just like the tech sector, of which AI is a subset, this is a rapidly evolving industry, so there are bound to be periods of extreme volatility. You will need to hold on during these periods to enjoy the periods of extreme growth.

To deal with the periods of extreme volatility, consider diversifying your portfolio, thematically as well as geographically, by investing in other industries in India, as well as in US stocks. This will help you with risk mitigation and optimise your portfolio for long term growth. Also understand the market trends using fundamental and technical analysis before investing.

Frequently Asked Questions about AI Stocks in India

However, this information does not constitute any investment advice. Please do your own research before buying any stocks.

Is it profitable to invest in AI stocks in India?

Investing in AI stocks in India can be profitable, especially given the strong growth outlook for the AI industry. Many Indian companies are reporting robust growth in revenue from their AI-driven services and products, reflecting heavy client demand. For example, mid-sized IT firms with AI expertise have seen their stock prices climb as they win new contracts. That said, profitability is not guaranteed – it depends on picking the right companies that execute well. Some AI companies may take time to turn profitable due to high R&D expenses or competition. It’s also important to have a long-term perspective: AI adoption is a multi-year trend. Investors who got in early on quality AI-driven businesses have seen significant gains, but one should be prepared for volatility.

Are AI and robotics the same?

No, AI (Artificial Intelligence) and robotics are related but not the same. Artificial Intelligence refers to the simulation of human intelligence in machines – basically, software algorithms that can learn, reason, and make decisions. AI can exist purely in software (for instance, a machine learning algorithm optimizing logistics). Robotics, on the other hand, involves physical machines (robots) that can perform tasks, often in the physical world. Robotics may or may not use AI.

Who should invest in AI shares in India?

AI shares in India are suitable for investors who:

• Have a long-term investment horizon.
• Are willing to accept higher volatility for potentially higher returns.
• Have a keen interest in technology and innovation.
• Are looking to diversify their investment portfolio with exposure to cutting-edge technologies.

Are AI-related stocks in India considered stable for long-term investment?

AI-related stocks, especially the smaller ones, are generally less stable than blue-chip stocks in defensive sectors. They operate in a fast-changing industry, which means their fortunes can swing with technological shifts or competitive moves. However, if you choose well-established companies that have diversified portfolios (for example, an IT services giant that does AI projects but also has other steady revenue services), those can be relatively stable and suitable for long-term holding. Among the companies discussed, something like Bosch or Oracle Financial Services might have more stability (because they have legacy businesses or parent support) compared to a pure-play small AI company which might see more earnings volatility.

Disclaimer

The information provided in this article is for educational and informational purposes only. It should not be considered as financial or investment advice. Investing in stocks involves risk, and it is important to conduct your own research and consult with a qualified financial advisor before making any investment decisions. The author and publisher are not responsible for any financial losses or gains that may result from the use of this information.

Want to learn more about the top stocks in other sectors in India? Check out the following articles:

Top Ethanol Stocks in India

Best Semiconductor Stocks in India

Best EV Stocks In India

Top Chemical Stocks in India

Top Renewable Energy Stocks in India

Best FMCG Companies In India

Top Green Hydrogen Stocks in India

Top Ethanol Stocks in India

Best ETFs in India: All You Need to Know

If you’re interested in buying the popular US Stocks, you can read the following articles:

How to Buy Apple Shares in India | Check Apple Share Price

How to Buy Amazon Shares from India | Check Amazon Share Price

How to Buy Google Shares from India | Check Google Share Price

How to Buy Microsoft Shares from India | Check Microsoft Share Price

How to Buy Tesla Shares in India | Check Tesla Share Price

How to Buy McDonald’s Shares in India