Right, let’s get one thing straight. For the better part of a year, the tech world has been in the throes of a fever dream, and the word ‘AI’ is the mantra being chanted from every boardroom and conference stage. Every CEO, from Silicon Valley to Bangalore, has been falling over themselves to explain how Artificial Intelligence is going to “revolutionise” their workflow, “optimise” their efficiency, and generally make everything faster and cheaper. It’s been about cost-cutting and productivity, a narrative that’s useful, but frankly, a bit dull.
But what if that’s the wrong way to look at it? What if AI isn’t just the spanner you use to tighten the bolts on your existing machine, but the engine for a brand-new vehicle altogether? This is the question that should be keeping executives awake at night. It seems Vijay Shekhar Sharma, the ever-resilient chief of Paytm, has been pondering just that. In a move that’s part audacious and part a necessary roll of the dice, he’s declared that for Paytm, AI is no longer a tool. It’s a product. This shift marks a critical evolution in how businesses think about generating cash, moving beyond simple efficiencies to create entirely new AI revenue streams.
So, What Are AI Revenue Streams, Really?
Before we get carried away, let’s be precise about what this means. When most companies talk about AI, they’re talking about it as a cost-centre. They use AI to automate customer service, streamline logistics, or write marketing copy a bit faster. The return on investment is measured in saved salaries and reduced operational overheads. It’s an internal efficiency play, full stop.
AI revenue streams are something else entirely. This is about building and selling a product or service where the core value is the AI. The customer is paying directly for the AI’s capability. Think of it like this: using the internet for internal email in the 90s was a productivity tool. Building an entire business like Amazon or Netflix, where the internet is the foundational platform for revenue, was the real game-changer. The same transition is happening with AI. Companies are moving from using it behind the scenes to putting it front and centre on the invoice. It’s a fundamental change in strategy, turning a department’s budget line into a core business vertical.
Welcome to ‘AI-commerce’: The Newest Shop on the High Street
This brings us to the shiny new term being bandied about: AI-commerce. Is it just a clever rebranding of e-commerce with a bit of machine learning sprinkled on top? Not quite. AI-commerce represents a new category of services that businesses can sell. It’s about offering intelligent, automated capabilities as a paid-for product, creating entirely new business verticals that didn’t exist before.
Imagine you’re a small merchant. Your e-commerce platform today probably offers you a basic website and payment processing. In an AI-commerce model, that platform could offer a tiered subscription. The basic tier might give you sales analytics. A premium tier, however, could offer AI-powered dynamic pricing that adjusts in real-time based on competitor stock and local demand, automated inventory management that predicts what you’ll sell next week, or hyper-personalised marketing campaigns that write and target themselves. You’re not just selling online; you’re paying for an AI business partner.
A Case Study in the Making: Paytm’s Big Pivot
This is precisely the territory Paytm is charging into. According to a report from Moneycontrol, CEO Vijay Shekhar Sharma is not just talking theory. He’s piloting AI-powered subscription services for the millions of merchants on his platform. He was quoted saying, ‘AI isn’t just a productivity tool, it’s a revenue line item now’. This is more than just talk; he intends for these services to appear as a distinct line item in Paytm’s financial reports.
Let’s not be naive. This move doesn’t come from a vacuum. Paytm has had a tough time recently, particularly with the regulatory clampdown on its Payments Bank. A pivot towards a high-margin, recurring revenue model built on AI is a classic strategic response to pressure. It’s an attempt to build a new, more defensible fortress on fresh ground, away from the embattled territories of payments and banking. By leveraging its vast trove of merchant and transaction data, Paytm is in a unique position to create AI tools that are genuinely useful. The question is whether they can execute it.
Building the ‘AI Commerce Cloud’
The grand vision for this is something Sharma calls the ‘AI commerce cloud’. Forget the jargon for a moment and think about the strategy. A company like Paytm is, at its heart, an aggregator. It aggregates millions of merchants and hundreds of millions of users. It sits on a mountain of data about who buys what, when, where, and for how much.
A traditional platform business monetises this by taking a tiny slice of every transaction. It’s a volume game. The ‘AI commerce cloud’ model is a play to change the game entirely. Instead of just taking a slice, Paytm wants to sell the merchants shovels and pickaxes—in the form of AI services—so they can dig for gold more effectively themselves. This creates a powerful flywheel: better tools lead to more successful merchants, who in turn process more transactions and become more deeply embedded in the Paytm ecosystem, all whilst paying a recurring subscription fee for the privilege. It’s a move from a transaction-based model to a platform-and-subscription model, which investors and a-certain-journalist-who-will-remain-nameless typically love.
You Don’t Build an AI Empire Alone
Here’s the rub: declaring you’re an AI company is easy. Actually building the infrastructure to deliver powerful, real-time AI services at scale is monstrously difficult and expensive. You can’t just plug in ChatGPT and hope for the best. This requires serious, specialised hardware. And this is where the most intriguing part of Paytm’s announcement comes in: the Groq partnership.
A partnership with a relatively niche, though highly respected, AI hardware company like Groq says a lot about the type of AI Paytm is trying to build. You see, the AI world is broadly split into two camps: training and inference.
– Training is the heavyweight-boxing part of AI. It involves throwing colossal datasets at enormous models on thousands of power-hungry GPUs, usually from Nvidia. It’s how models like GPT-4 are born. It’s slow, ludicrously expensive, and done behind the scenes.
– Inference is the nimble, real-world application of that training. It’s when a user asks a question and the AI provides an answer. For business applications, particularly in commerce, inference needs to be two things: lightning fast and cheap to run. A customer won’t wait ten seconds for an AI chatbot to think of a reply.
Why the Groq Partnership Is More Than Just a Press Release
This is where Groq comes in. The company doesn’t make GPUs. It makes LPUs, or Language Processing Units. These chips are purpose-built for one thing: running AI models (inference) at incredible speeds with very low latency. Think of it this way: Nvidia’s GPUs are the giant, bespoke engines used to design and build a Formula 1 car in a factory. Groq’s LPUs are the hyper-efficient, mass-produced engines you put into every delivery van on the road to get its job done instantly.
By partnering with Groq, Paytm is signalling that its focus is on real-time, practical application. They are building for speed and cost-efficiency at scale, which is exactly what you need to service millions of merchants with things like instant fraud detection, real-time analytics, or conversational chatbots. As detailed in the Moneycontrol report, this strategic hardware choice underpins the entire ‘AI commerce cloud’ ambition. Without a cost-effective way to run inference at scale, the subscription model would never be profitable. The Groq partnership is the crucial, technical foundation upon which this new business vertical hopes to be built.
The Future Is a Line Item
So, where does this leave us? Paytm’s announcement is significant not just for Paytm, but as a potential bellwether for the entire tech and commerce industry. We are at an inflection point where the conversation is shifting from “How can AI make us more efficient?” to “What new things can we sell with AI?”.
The move to establish dedicated AI revenue streams is the next logical step in the commercialisation of artificial intelligence. It forces companies to be disciplined. When AI is a product with its own profit and loss statement, you can’t get away with vague promises and vanity projects. It either makes money, or it doesn’t. Full stop.
Will Paytm succeed? The jury is out. The path is fraught with technical challenges, competitive pressure, and the monumental task of convincing millions of merchants to pay for yet another subscription. But Sharma is making a clear, strategic bet that the future of his company lies not just in facilitating commerce, but in selling intelligence itself.
The bigger question is, who’s next? Which platform, sitting on its own mountain of proprietary data, will be the next to declare that AI is moving from the expense column to the revenue column? And how will they choose to build it?
What are your thoughts? Is Paytm’s move a brilliant strategic pivot or a desperate “Hail Mary” pass with a buzzword attached? Let me know in the comments below.
