Manav Khurana holds a Bachelor of Science in Electrical and Computer Engineering from the University of Rochester and a Master of Business Administration from Santa Clara University. He joined New Relic as SVP and Product GM and implemented the company’s consumption business model. 

Before New Relic, he held product and marketing leadership roles at Twilio, Aruba (HPE), and Motorola. Manav Khurana brings deep experience in creating new technology categories and applying product-led growth principles.

INDIAai interviewed Manav Khurana to get his perspective on AI.

As a CPO of New Relic, can you give me some understanding of what New Relic is doing in the AI landscape? 

Artificial Intelligence (AI) has emerged as a transformative technology across numerous industries, and its impact on observability is no exception. AI is reshaping the observability landscape through three key areas: conversational interfaces, performance management of AI applications, and predictive automation.

New Relic’s introduction of New Relic AI in 2023 exemplifies this transformation. By leveraging generative AI, New Relic has democratized observability for engineers, IT professionals, and product teams. With its ChatGPT-like interface, users can interact with complex observability data through natural language queries, regardless of their technical expertise. This feature breaks down the complexity barrier, allowing professionals to ask questions like, "How is my system performing?" or "What is causing a poor user experience?", and receive answers in an easily-understandable format. This approach simplifies the data interpretation and enhances problem-solving by offering actionable insights.

Moreover, as AI continues to evolve, the potential for AI-driven automation and prediction in observability will further enhance software performance monitoring and future forecasting. AI’s integration into observability platforms like New Relic enables a much broader user base to harness its power, promoting a more efficient, informed, and proactive approach to managing digital environments. This shift underscores AI's role as a generational technology, driving significant advancements in how organizations monitor and optimize their software and business operations.

How do you integrate AI and machine learning (ML) into the product development strategy? How do these technologies enhance engineers' data-driven approach to optimize their workflows?

When engineers build AI-powered experiences for their customers, a lot of problems can occur. The AI may not be accurate. It may not be performant. It may take too much time. It may be too expensive. That doesn't make it commercially viable. There could be biases or prejudices in the model. So, how do you ensure your AI-powered application doesn't have those problems? To solve that, we introduced what we call AI monitoring, where our customers gain complete visibility into all AI-powered experiences and transactions, from prompt to response — and measure the accuracy. It helps businesses gain answers to questions like, ‘What is the performance? What is the cost? Are there any biases in the model?’ It compares different models against each other as that’s a great, data-driven way of ensuring that AI solves a customer problem.

Given your passion for empowering engineers with data-driven tools, how is New Relic incorporating AI to boost engineering efficiency? Are specific AI-driven features or innovations resonating with your engineering teams?

In addition to building AI-powered experiences for our customers, we have an internal project that offers several AI-powered tools for our engineering and development team.

In India, we have about 500 people. Globally, we have about 1,000 to 1,200 employees. Among them, about 20-30% of our people have already adopted those tools. Those who adopted these tools reported a 10% improvement in productivity. It’s too early for multiple use cases and there are a few obvious ones because the blinking cursor in the development environment is the enemy of progress in a developer's world. So, we see employees using AI to write your code or using it as a co-pilot to write code. And we're seeing more and more AI-powered code check-ins.

With AI's growing role in observability and product management, what steps is New Relic taking to ensure ethical and responsible AI deployment? How do you manage the balance between innovation and data privacy concerns?

With every major technology, ethics must be properly defined, the right tools must be adopted to ensure compliance with ethics, and the right governance mechanisms must be in place. The area that I am most focused on is making sure we have the right tools. For example, AI monitoring allows customers to measure AI's responsible and secure ethical use to build customer-facing experiences.

What is your long-term vision for AI's role in New Relic’s product offerings? How do you foresee AI shaping the future of observability and cloud-native applications?

Well, I imagine a completely AI-powered observability platform. I think we’re going to call it an intelligent observability platform. It's going to be the next generation of what observability is today. You'll see it will be easier for every user of New Relic to get value using AI. It will be possible for our customers to ensure AI-powered experiences are responsibly serving their customers and business needs. And we're going to go from reactive to preventive. 

What advice would you give to someone who wishes to join your team?

So, the first thing is that a level of AI and data literacy is required. I wish I were a student today to go back and play with all the existing options and see what I can build with the available tools. Tw2o to three decades ago, what we could do was very slow, and what’s possible today is incredible. Anybody can do anything. And I hope that inspires people to build unique software and product experiences. It requires people to dive in and get involved immediately, not just with AI tools that are the shiny object, but understand the whole software development lifecycle.