AI as a product layer
At a time when artificial intelligence is moving from experimentation to deployment, Juspay's Ishan Sharma is making a clear case that AI agents will become more than a productivity tool. He sees them as a new product layer that can change how companies design, build, and operate software at scale. For India's technology sector, that argument carries particular weight: the country has long been a global delivery hub, but the next phase may depend on whether it can also become a source of original, exportable AI-led products.
Sharma's framing reflects a wider shift in the software industry. The conversation is no longer limited to large language models or chatbots. It is increasingly about autonomous or semi-autonomous agents that can take actions, coordinate tasks, and reduce the amount of manual intervention required across business processes. In payments, mobility, and other digitally intensive sectors, such systems could streamline customer support, fraud detection, reconciliation, onboarding, and operational decision-making. The implication is not merely faster software development, but a different operating model altogether.
For a company such as Juspay, which sits at the intersection of payments infrastructure and digital commerce, the relevance is immediate. Payments businesses depend on reliability, speed, and scale, but they also face constant pressure to improve user experience and reduce friction. AI agents, if deployed carefully, could help automate repetitive workflows and improve responsiveness without compromising control. That makes the technology especially attractive in sectors where milliseconds matter and operational errors can be costly.
India's global advantage
Sharma's broader point is that India is not starting from zero. The country already has deep engineering talent, a strong base of software services, and a growing ecosystem of product companies that understand how to build for complex, high-volume markets. What has often been missing is the confidence and infrastructure to convert that capability into globally competitive products. AI agents may narrow that gap by lowering the cost of experimentation and speeding up iteration.
That matters for the "build from India for the world" thesis. India's technology story has traditionally been defined by scale, cost efficiency, and delivery excellence. But the global AI cycle is creating room for a different kind of advantage: one based on speed of adaptation, domain expertise, and the ability to solve real operational problems. If Indian companies can combine engineering depth with product ambition, they may be able to compete not just as implementers of foreign technology, but as creators of systems that can be exported worldwide.
The opportunity is especially significant in sectors such as automotive, electric vehicles, and mobility, where software is becoming central to the customer and operational experience. From connected vehicles to charging networks and fleet management, the industry is increasingly shaped by digital infrastructure. AI agents could help manage these layers more intelligently, whether by automating support, optimizing workflows, or improving the way data is used across platforms. That convergence gives Indian firms a chance to build products with both domestic relevance and international appeal.
The execution test
Still, the promise of AI agents comes with clear constraints. Enterprises will not adopt them blindly, especially in regulated or mission-critical environments. Issues such as reliability, auditability, data governance, and human oversight will determine how quickly these systems move from pilot projects to production use. In payments and mobility alike, trust is not optional; it is the foundation of adoption.
That means the real test for companies like Juspay is not whether they can talk about AI in ambitious terms, but whether they can translate that ambition into dependable products. The winners in this cycle are likely to be those that pair technical sophistication with operational discipline. In practical terms, that means building systems that are transparent, controllable, and useful in the real world, not just impressive in demos.
Sharma's comments also reflect a broader strategic moment for India's tech sector. As global firms race to embed AI into every layer of their operations, Indian companies have an opening to define their own standards for how such systems should work. If they succeed, the country could move beyond being a low-cost execution center and emerge as a serious center of AI product innovation. That is the larger significance of the AI agents debate: not simply what the technology can do, but who gets to shape the next generation of digital infrastructure.
For now, the message from Juspay is clear. AI agents are not a distant concept. They are becoming part of the competitive logic of modern software, and India's ability to build them well may determine how far its technology companies can go in the global market.