Vijay Shekhar Sharma built Paytm around a straightforward idea: make digital payments easier for ordinary consumers and small businesses. QR codes and the Soundbox helped bring that idea into everyday retail.
His current focus includes using AI to improve Paytm's internal operations and developing services for external business customers through Paytm Intelligence.
Beyond Paytm, Sharma is encouraging Indian entrepreneurs to develop homegrown AI models and has offered personal financial support to founders pursuing that goal.
A small shopkeeper accepting payment through a QR code is now a familiar sight across India. Not long ago, cash was still the preferred option for many everyday purchases.
Paytm helped change that habit. From mobile recharges to payments at local shops, the company made digital transactions easier for people with little financial technology experience.
Behind this journey is Vijay Shekhar Sharma, Paytm's founder. Having helped bring digital payments into everyday life, he is now looking at another opportunity: artificial intelligence.
But this next step comes with a different challenge. Building useful AI products and persuading businesses to pay for them will require more than a good idea.
Paytm did not become popular overnight. It grew by solving everyday problems for customers and small businesses. QR codes gave shopkeepers a simple way to accept digital payments without investing in expensive equipment. Customers could scan a code and pay using their phones.
The company's Soundbox made the process even easier. Instead of checking a screen after every transaction, merchants could hear an announcement confirming payment. For busy shops, that small feature proved practical.
Paytm gradually expanded into consumer payments, merchant services, and financial products. In July 2026, it reported quarterly revenue of Rs. 2,448 crore and net profit of Rs. 220 crore for the quarter ending June. The results provide an update on the company's financial performance as it explores AI-related services. Now, Sharma wants to build on that foundation.
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For Paytm, AI is not just about launching another chatbot. The company sees opportunities to improve its existing operations and develop new services. AI tools can help employees answer routine customer questions, write and review code, and manage repetitive business tasks. These applications may reduce the time spent on everyday work.
Paytm is also exploring smaller AI models built using open-source technology. Sharma has discussed adapting these models for Indian languages and running them on the company's own infrastructure.
This approach could help in India, where customers speak different languages and businesses have varying levels of technical expertise. A tool that understands local languages and common merchant problems could make digital services easier to use.
The challenge is finding applications that work reliably outside controlled testing environments.
Using AI internally is one thing. Selling AI products to other companies is another. Paytm is developing AI services under its Paytm Intelligence initiative. These efforts include tools for customer engagement, sales, merchant operations, and other business activities.
The company's existing merchant network could help it find customers for these products. Many small businesses need better ways to manage customer queries, follow up on payments, and organize daily operations.
Paytm already understands some of these problems through its payments business. However, businesses will not adopt AI merely as the technology is new. They will want to see whether it saves time, reduces costs, or improves sales. Paytm must prove that its products deliver those benefits consistently.
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Sharma's ambitions extend beyond Paytm's own products. He has also encouraged Indian entrepreneurs to develop AI models suited to the country's needs. India's language diversity creates a particular opportunity. Models designed for local languages and business contexts could address needs that some existing AI tools do not fully meet.
But building competitive AI technology takes considerable investment, computing resources, and skilled researchers. Local models must also be accurate and dependable enough for everyday use. Paytm does not necessarily need to compete directly with every global AI company. It could focus on specific problems where its experience with payments and merchants offers an advantage. That would give the company a more practical starting point than trying to build technology for every possible use.
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Paytm's AI plans arrive with several challenges. Financial services depend on trust, reliable transactions, and careful handling of personal information. AI tools used in these areas must meet the same expectations. Competition is another concern. Established software companies and new AI startups are also targeting business customers.
Paytm must continue strengthening its core operations while finding ways to turn AI experiments into sustainable revenue. There is no guarantee that these new services will become a major source of growth.
Still, Sharma's approach reflects a logical next step for a company built around everyday transactions. Paytm first made digital payments easier for millions. Now, it wants to help businesses use AI in practical ways.
Whether it achieves the same reach remains to be seen. Ultimately, the company's success will depend on a familiar principle: solving real problems with products that people find useful enough to keep using.
Vijay Shekhar Sharma is the founder and CEO of Paytm, one of India's prominent digital payments and financial technology companies. He helped build the business from a mobile-recharge service into a broader platform serving consumers and merchants through digital payments and related financial products.
Paytm helped make digital payments more accessible to small merchants and consumers. QR codes gave shopkeepers a simple way to accept payments, while the Soundbox provided audible payment confirmations. These products helped make digital transactions more practical for everyday purchases.
Paytm is using AI across areas such as engineering, customer support, sales, merchant operations, and internal workflows. It is also developing specialised models and AI tools that could improve productivity and support new services for businesses.
Paytm Intelligence, also known as Pi, is the company's initiative to develop AI-powered services for businesses. Its focus includes areas such as sales, customer service, and operations. The aim is to turn capabilities developed within Paytm into products that other organisations can use.
Paytm has discussed adapting open-source models for specific business tasks and Indian languages. Smaller, specialised models can be more practical to run for targeted applications. Their usefulness depends on accuracy, operating costs, and how well they handle the language and task involved.