Jeetu PatelPresident & Chief Product Officer

We're moving from a world of chatbots to a world of AI agents. These agents consume significantly more network resources than humans. In our studies, an agent consumed roughly 450% more bandwidth than a person performing the same task. As agents become widespread, networks will need to be completely reimagined.

Agents work around the clock. They continuously exchange information, access memory, communicate with models, and perform tasks without stopping. Unlike humans, they never sleep. When you multiply that across thousands of agents, the demand on networks, compute power, and energy becomes enormous.

We're seeing companies modernize their workplace infrastructure much faster than before. Historically, workplace networking grew only a few percentage points annually. Recently, we've seen growth rates many times higher because organizations are preparing for AI-driven workloads and agent-based computing.

We already have products where AI generated all the code and humans verified the results. By the end of next year, we expect a large percentage of our products to be fully written by AI. The role of humans will increasingly focus on judgment, validation, architecture, and customer engagement.

Their work will change significantly. Engineers will spend less time manually writing code and more time reviewing, validating, designing architectures, and helping customers succeed. Product intuition and decision-making will become more valuable than typing code itself.

I don't believe AI will reduce the need for talented people. Every time we automate one bottleneck, another bottleneck appears. The challenge shifts rather than disappears. What will matter is whether people become fluent in AI and learn how to work effectively alongside these technologies.

The productivity gap between someone who understands AI deeply and someone who doesn't could become enormous. It may eventually be as unusual as hiring someone today who doesn't know how to use the internet. AI fluency will become a basic requirement for many knowledge-based jobs.

Many organizations spend too much time experimenting and not enough time committing. The companies that move decisively and integrate AI into their operations are seeing the strongest results. At this point, AI adoption is becoming less of a choice and more of a necessity.

I don't believe so. We are still very early in the cycle. Only a tiny percentage of the world's population actively uses AI agents today. As adoption increases, demand for infrastructure, networking, compute power, and data centers will continue to grow significantly.

Most organizations are still learning how to use AI effectively. There is a difference between becoming familiar with AI, becoming skilled at it, and becoming efficient with it. Many companies are still in the early stages, where costs are high and productivity gains haven't fully materialized yet.

Companies need greater visibility into token consumption, infrastructure utilization, and AI efficiency. Not every task requires the most advanced model. Intelligent routing, smaller models, and better management systems will become increasingly important for controlling costs.

AI creates opportunities for people who can adapt quickly. The workforce will evolve, but new roles, industries, and responsibilities will emerge. The biggest opportunity lies in learning how to work alongside AI rather than competing against it.

I'm extremely optimistic. India has a tremendous demographic advantage with a large young workforce. Combined with strong entrepreneurship and increasing government support for innovation, India is positioned to play a major role in the global AI economy.

Physical AI and robotics are at the top of the list. We're also seeing advancements in spatial models, quantum computing, new energy solutions, and application-layer innovation. These technologies will reshape industries and create entirely new opportunities.

The pace of progress is accelerating exponentially. We're seeing self-improving systems, rapid innovation, and breakthroughs across multiple industries simultaneously. Healthcare, education, scientific discovery, and productivity all stand to benefit from these advancements over time.

Companies often fail because they hesitate. The organizations that succeed are usually the ones willing to commit early, move decisively, and adapt quickly. Waiting too long to embrace change can be far more dangerous than moving too fast.