After QR, Paytm’s next big leap is AI for merchants: Vijay Shekhar Sharma

New Delhi: At the AI Impact Summit in New Delhi, Vijay Shekhar Sharma, Founder and CEO of Paytm, positioned artificial intelligence as India’s next structural leap, one that could move beyond experimentation and into core business and economic transformation.

In an exclusive interaction on the sidelines of the summit, Sharma made it clear that Paytm’s AI focus will not be on competing with global consumer chatbots but on solving for India’s small merchants, the same segment that powered its QR revolution.

Responding to BestMediaInfo on what AI means for Paytm after digitising payments through QR codes, Sharma drew a sharp distinction between consumer and merchant opportunities.

On the consumer side, he acknowledged that large global AI labs already offer products with deep resources, often free of cost. Competing head-on in that segment, he suggested, may not be commercially viable.

The real gap, he said, lies on the merchant side. For instance, a street vendor deciding which vegetables to stock each morning currently relies on instinct and limited local knowledge. AI, Sharma suggested, could analyse weather forecasts, historical sales data and pricing trends to recommend what to buy, or avoid.

When asked how soon merchants could expect AI-enabled tools on Paytm’s platform, he responded succinctly: “Soon, very soon.”

The direction is clear: AI as decision-support infrastructure for small businesses.

On the regulatory front, Vijay addressed concerns around the RBI’s tighter scrutiny of fintechs, particularly after compliance actions in the sector. Without striking a confrontational note, he indicated that regulation is part of building a mature financial ecosystem. Strong oversight, he suggested, ultimately strengthens trust in digital finance. For fintech players like Paytm, alignment with the Reserve Bank of India is not optional but foundational, especially as AI and digital tools become more deeply embedded in financial services.

In his keynote address, Sharma argued that AI’s first phase was largely individual and experiential, chat interfaces, co-pilots, image edits and messaging support.

From 2026 onwards, he said, AI will shift into business workflows with greater commitment and confidence. The emphasis will move from novelty to productivity.

He likened the present moment to the early days of QR adoption. When digital payments were first introduced, there were doubts about whether ordinary citizens would understand them. Today, QR codes are visible in every corner of the country. In Sharma’s view, AI could follow a similar adoption curve.

On the question of dependence on foreign AI foundation models, Sharma adopted a balanced stance.

Speaking to BestMediaInfo, Sharma said, India must build its own foundation models, stressing that the capability and resources exist. It is not “rocket science” anymore once the path is known.

But he cautioned against reducing the AI race to foundation models alone. Using a mechanical analogy, he compared foundation models to engines. Engines are critical, but what ultimately matters is the vehicle built on top, whether it is a passenger car, bus or industrial truck.

For India, the larger opportunity lies in sector-specific AI systems, for finance, agriculture, healthcare and small enterprises. The fight, he argued, is about AI that works for a segment, solves a defined problem and functions as an agent within that sector.

Coming from the financial services ecosystem, Sharma emphasised credit as a major AI use case.

Access to credit creates wealth, he said, but expanding credit responsibly requires sharper insight into risk. AI can help financial institutions evaluate nuanced cases, determining where credit should flow and where caution is necessary.

If smartphones extended access to financial systems across the country, AI could deepen that access with better risk calibration. In Sharma’s framing, AI could make financial inclusion more intelligent, not just more widespread.

Sharma repeatedly returned to India’s scale advantage. With a large, young population and widespread smartphone penetration, he argued that India’s demographic dividend can evolve into a “demographic technology dividend.”

The more people use AI tools, the more capable they become. Adoption at scale accelerates capability. This, he suggested, is where India holds structural strength.

Addressing concerns about job displacement, Sharma reframed the debate.

Call centres, he acknowledged, are often cited as vulnerable to automation. But he argued that such infrastructure can evolve into higher-value services. For example, remote healthcare tracking for ageing populations in Europe could be managed from India, combining AI-driven insights with human verification.

The real question, he said, is whether individuals choose to ride the wave of change or feel overtaken by it.