AI adoption is entering a more practical phase. For large organisations, the challenge is increasingly about how quickly an idea can move from a business requirement to something customers, employees or merchants can actually use.
New-age fintechs offer some useful lessons here. Their advantage comes from building AI directly into workflows, products and operating processes, allowing teams to remove friction at points where speed can have a measurable business impact.
PhonePe offers several examples. In February, the company introduced an AI-powered natural-language search experience that allows users to navigate the app through voice or text. A command such as “Pay Nikhil ₹20” can take the user directly to the relevant payment flow, while other requests can surface recharges, transaction information or support. The underlying shift is significant: the customer no longer needs to know where the function sits inside the application. AI interprets the intent and takes them there.
The same focus on speed extends to the merchant side. PhonePe’s AI Integration Agent can help businesses integrate its payment gateway through a conversational interface, reducing a process that could take weeks to minutes. The system interprets requirements, maps them to Application Programming Interface (APIs), generates integration logic and helps resolve errors. For smaller businesses with limited developer resources, reducing technical dependency can directly shorten the path to going live.
PhonePe has also introduced SmartPages , an AI-powered payment page creator that lets merchants describe what they are selling and have AI generate the copy, fields and a mobile-optimised page. The company says businesses can become payment-ready in under 10 minutes.
The lesson for larger enterprises is broader than any individual use case. AI creates business value when it removes a bottleneck. For one organisation, that may mean reducing integration time. For another, it could mean shortening a product cycle, simplifying customer service, automating compliance or helping an employee complete a complex task without moving across multiple systems.
This is where the conversation around enterprise AI is changing. Large organisations have the scale, data and established processes to create significant value, yet their size can also make experimentation slower. The opportunity lies in adopting the same bias towards speed while building the governance, security and reliability required at enterprise scale.
Where can large organisations learn from fintech's speed?
At the ET AI Business Transformation Masterclass & Awards 2026 , this question will move from theory to practice.
In his session, Srijon Biswas, CTO, PhonePe will explore “How the fastest fintech players are moving and what lessons large organisations can adopt from them.” His perspective comes from operating AI and technology at one of India's largest digital platforms, where speed has to coexist with scale, reliability and trust.
The conversation sits within a larger day at IIM Bangalore on 19 November 2026 , bringing together enterprise leaders working across AI, financial services, consumer businesses, payments, supply chains, physical AI and enterprise technology. The Masterclass is designed around the questions that come after experimentation: What should be scaled, how should it be implemented, and where can AI create measurable business impact?
The day will also culminate in the ET Most Innovative AI Product Awards 2026 , recognising AI products turning technological capability into meaningful business value.
For leaders looking to make AI faster, more practical and more accountable inside their organisations, the fintech playbook offers a useful place to start.
