OPINION | ChatGPT or DeepSeek? What should shape India's future?

India is at an inflection point. Artificial Intelligence is no longer a futuristic concept: it’s here, shaping how you work, learn, and live. In line with this, two leading AI models—ChatGPT from the US and DeepSeek from China—offer distinct approaches. Both influence how India defines its AI priorities. 

Businesses now face a critical choice. Should they rely on powerful but expensive global models or adopt leaner, locally-adaptable frameworks? Or should India build its own?

Why DeepSeek is relevant to India

DeepSeek is built for scale without relying on expensive hardware. This is especially useful for countries like India, where infrastructure is still catching up. One of its key strengths is cost-effective training. DeepSeek uses optimisation techniques that reduce the computing power required to build AI models. This makes foundational model development possible, even without large clusters of GPUs.

Secondly, it’s designed to run on less centralised infrastructure. That means businesses would not need top-tier data centres or high-end cloud services to deploy AI solutions, giving it a practical advantage for application in rural and semi-urban regions in India.

Thirdly, DeepSeek is built for multiple languages. India has over 20 officially recognised languages. Most global models are skewed toward English. DeepSeek’s multilingual capacity means AI tools can serve people in Tamil, Gujarati, Assamese, and more.

For instance, think of a healthcare assistant who can talk to patients in their native language or a farmer advisory tool that understands local dialects. DeepSeek enables these kinds of solutions.

Where ChatGPT already leads

ChatGPT, developed by OpenAI, has already proven its value in India across sectors. In customer service, companies are using ChatGPT-based bots to reduce response times. A fintech firm in Mumbai cut support costs by 30% after replacing live agents for FAQs and transaction queries.

In education, platforms are using ChatGPT to create dynamic quizzes, summarise lectures, and personalise learning paths. Students in Tier-2 cities are benefiting from better access to self-guided learning tools.

Indian IT firms, for instance, apply ChatGPT to speed up coding, debug software, and create documentation. One major consultancy reports a 25% reduction in development cycles on certain internal tools.

Such use cases show immediate value, as businesses don’t need to wait for government support or long development cycles.

However, there are challenges here. ChatGPT relies on expensive cloud infrastructure that is not fully under Indian control. It also has limited support for Indian languages and contexts.

India’s push for its own AI model

Under the IndiaAI mission, the government is funding the creation of an affordable, homegrown AI model. This effort includes subsidised access, which makes it easier for startups, academic institutions, and government bodies to use this model. It also includes partnerships to design domestic GPUs, reduce import dependence, and improve chip design capabilities.

Why does this matter to businesses and users?

When India controls both the models and the hardware, it controls the data and the direction. That’s essential for sectors like health, law, and education, where privacy and relevance are critical. Imagine AI tools trained on Indian court judgments, government schemes, and regional academic content. This is not just localisation—it’s purpose-built intelligence for Indian users.

What enterprises are doing

Some Indian firms are already bridging the gap between global models and local needs. IT services firms are building their own generative AI suites, designed to help enterprises automate tasks, plan projects, and analyse operations.

Such generative AI suites are designed to keep multiple sectors in mind. For instance, in the banking sector, such AI suites can speed up loan processing. In insurance, it can flag inconsistencies in claim documents. In manufacturing, it can track maintenance schedules and forecast delays.

This is AI at work—not in labs, but in daily business operations. Firms developing indigenous tools show that India doesn’t need to wait for a perfect model. Solutions can be tailored and scaled now.

What should India do?

There is no single answer. ChatGPT offers speed and maturity. DeepSeek offers flexibility and cost. However, IndiaAI aims for sovereignty and scale. The real opportunity lies in combining these approaches. ChatGPT is usually used for immediate value where infrastructure exists. On the other hand, DeepSeek can be employed to create leaner, multilingual AI systems. 

Businesses need to ask themselves a question: what problem can AI solve for you today? The key is in the hands of the enterprises to shape the future by deciding where to invest, what to build, and who benefits from it.

AI advancements will not wait. Neither should businesses.

 

Ryan Cox is the Global Head of Artificial Intelligence at Synechron, based in the UK.

Opinions expressed in this article are those of the author and do not purport to reflect the opinions or views of THE WEEK.

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