When the most sophisticated technology on the planet is suddenly being given away for free, you know something big is happening. It’s a bit like finding a Rolex dealer handing out watches on Oxford Street. Your first instinct isn’t to marvel at their generosity; it’s to ask, “Right, what’s the catch?” That’s precisely the question we should be asking as OpenAI wades into India, offering a full year of its ChatGPT Go service for absolutely nothing. This isn’t an act of charity; it’s a calculated, aggressive move in what is rapidly becoming a multi-billion-dollar gold rush.
The battle for the future of artificial intelligence isn’t just being fought in the research labs of Silicon Valley. The real frontline is in places like India, Brazil, and Indonesia. This is the new global contest, and the prize is immense. A report from the Boston Consulting Group projects India’s AI market alone could balloon to an astonishing $17 billion by 2027. With numbers like that on the table, offering a free service isn’t a cost; it’s a down payment on market dominance.
What is ‘Emerging Market AI’ Anyway?
Let’s just pause for a moment and define our terms. When we talk about emerging market AI, we aren’t just talking about selling existing Silicon Valley products to a new audience. That’s a strategy doomed to fail. These markets are fundamentally different. They are defined by a few key characteristics: astronomical scale, a mobile-first population, and extreme price sensitivity. India, for instance, has more than 700 million smartphone users and is closing in on one billion internet subscribers. This isn’t just another market; it’s a market that operates on a completely different order of magnitude.
Think of it this way: in the West, AI development has largely been a desktop-first affair, driven by researchers and businesses with hefty budgets. In an emerging market, AI has to work flawlessly on a five-year-old, £100 Android phone with a patchy 4G connection. It needs to be useful to someone who might not be fluent in English and who has never paid for a digital subscription in their life. The players who understand this distinction are the ones who stand a chance of winning. The rest will simply be footnotes in a future business school case study.
The Great Indian Land Grab
So, why India? And why now? The numbers tell part of the story. According to a report highlighted by Artificial Intelligence News, downloads of ChatGPT in India have exploded, growing 587% year-on-year to 46.7 million. Its competitor, Perplexity, which also made a strategic free offering in the country, saw its downloads surge by 600%. The demand is clearly there, and it’s white-hot.
OpenAI’s decision to launch its free ChatGPT Go offer on 4 November, timed perfectly with its DevDay Exchange developer conference in Bangalore, is a masterclass in strategic execution. It’s not just about acquiring users; it’s about embedding themselves within the local developer ecosystem. They are telling every software engineer, start-up, and tech enthusiast in India: “Build with us. Our platform is your platform.”
This is a classic land grab playbook, reminiscent of the early days of ride-sharing or e-commerce. Remember when Uber and local rivals would burn through billions in venture capital to offer heavily subsidised rides? They weren’t selling taxi journeys; they were buying loyalty and market share. The goal was to become the default app on everyone’s phone. OpenAI, Google, and Perplexity are doing the exact same thing, but their product is intelligence itself. They are willing to sacrifice short-term revenue for the long-term prize: becoming the foundational AI layer for a nation of 1.4 billion people.
The Uncomfortable Economics of ‘Free’
This relentless focus on user acquisition is the central theme of the emerging market AI strategy. In a market where the average revenue per user is low, volume is the only game that matters. You can’t win by selling a premium £20-a-month subscription to a handful of elites. You win by getting your free, “good enough” product into the hands of 200 million people.
Once you have that scale, you have options. You build a powerful feedback loop: more users mean more data, which means a better model, which in turn attracts even more users. This creates a formidable competitive moat that becomes almost impossible for rivals to cross. Monetisation can come later, through advertising, enterprise services, or by upselling a small fraction of those millions of users to a premium tier. But first, you must own the user relationship.
This is a high-stakes bet. OpenAI is gambling that the cost of providing free services to millions of Indian users will be a rounding error compared to the strategic value of locking them into its ecosystem before Google fully mobilises its own vast resources in the country. It’s a race against time, and right now, speed and aggression are more valuable than profit margins.
The Billion-User Translation Problem
Of course, simply parachuting a generic AI into a new country is a recipe for disaster. This is where the profound difficulty of localization challenges comes into play. And I don’t just mean translating “Hello” into Hindi. True localization is about understanding culture, context, idioms, and the sheer diversity of a country like India, which has 22 official languages and hundreds of dialects.
An AI model trained primarily on Western internet data from sources like Reddit and Wikipedia will carry all the biases and cultural assumptions of its training ground. It won’t understand the nuances of a conversation about cricket, the complexities of a local political debate, or the context behind a query about a regional festival. As Professor Payal Arora of Utrecht University often points out, designing for the “next billion users” requires a radical rethinking of design, not just a simple translation layer.
The company that cracks this will have a monumental advantage. Imagine an AI that can seamlessly switch between Hinglish (a popular mix of Hindi and English), understand a query spoken in a thick Bengali accent, and provide a response that is not just factually correct but culturally relevant. That is the holy grail. It requires immense investment in collecting and training on local data sets, a challenge that is as much anthropological as it is technical.
Forging Digital Inclusion, One Prompt at a Time
Amidst the cold, hard calculus of market strategy, there is a genuinely positive potential here. For hundreds of millions of people, these AI tools could be a powerful engine for digital inclusion. For a farmer in a remote village, an AI assistant could provide real-time weather updates or advice on crop diseases in their native dialect. For a student without access to good libraries, it could be a personal tutor, capable of explaining complex subjects in simple terms.
By lowering the barrier to accessing and interacting with digital information, AI can act as a great equaliser. You no longer need to be literate in English or skilled at navigating complex websites to find the information you need. You can simply ask a question in your own language. This has the potential to unlock huge economic and social value, supporting education, small businesses, and access to essential services.
However, we must also be clear-eyed about the risks. The same tools that promote inclusion can also create new forms of dependency. If one company’s AI becomes the primary gateway to the internet for a generation, that company wields an immense amount of power. It controls the flow of information and shapes the digital experiences of millions. Is that a future we are comfortable with?
The race for the emerging market AI crown has only just begun. The current phase is all about aggressive user acquisition, with companies sacrificing profits today for a dominant position tomorrow. But the freebies won’t last forever. Eventually, the bill will come due. The ultimate winners will be those who not only conquer the market but also solve the deep and complex localization challenges inherent to these vibrant, diverse regions.
The big question that remains is this: as these powerful AI models become deeply integrated into the fabric of societies like India, who is truly setting the agenda? The users shaping it with their queries, or the distant companies who built the code? What do you think?
