Innovating AI solutions with’s Prashant Natarajan’s Vice President of Strategy and Products, Prashant Natarajan on the company, his passion for AI and the books he co-authored for the industry

Tell me about your role at What do you enjoy? What are the biggest challenges?

As Vice President of Strategy and Products, my role is to help our customers develop products based 100% on their business and market strategy. Our customers are evolving what they think their future needs might be, and we’re helping them by democratising AI for the enterprise. What H2O means by that is we’re giving them tools to deal with the immense volumes of data, helping them convert that into not just smart insights, but enable action and create value.

So, my role is to understand the business market and societal trends around healthcare, sciences, insurance, banking, and other verticals. I work with customer executives and leaders--not just in business and operations, but also in data science and technology. My mission is to bring people together by helping them innovate AI-enhanced solutions that will create value for humans. Those humans, by the way, range from leaders themselves, the teams they lead, their employees, and most importantly of all, the customers they serve. I’d like to think the H2O platform, combined with my expertise, allows me the opportunity to bring all those together to create fulfilling products that our customers can use to generate value.

I’ve been at H2O for about 18 months, and this is actually my second stint here; I was previously on board in 2018. I was working in financial services, but then when COVID hit: my CEO, Sri Ambati, very soon after called me and said, we’re seeing the pandemic as an opportunity as a company to contribute to helping the world with AI, analytics, and data to craft solutions to address the challenges. And I think you should be part of that.

That was such a huge moment for me, and I couldn’t wait to get back to do what the planet needed, which is to focus on COVID and health-facing technology solutions for people.

What interests you about AI? How did you end up in the industry?

There are three reasons why I'm interested in AI. One, I'm a student of history and technology, and the history of technology tells us that we have always, as a species, wanted intelligent machines that will make our lives better faster and easier, like everybody else. I also grew up a massive Science Fiction fan, and it's been awesome to see a lot of that come to life in terms of devices; I’d love to see the AI we’ve seen in the best SF over the last 70 years also come to mind. Thirdly, working in the intersection of business and technology. The last few years has been a ‘perfect storm,’ and in a very good way, as various things coming together that will make AI give us truly augmented systems and amplified, practical intelligence.

I have degrees in Chemical Engineering and Technical Communication & Linguistics. As a result, my work has spanned all three areas over the last 20 years. However, this wasn’t the original plan! My parents raised me in the classical liberal spirit of education, which was you go out and gain as much knowledge as possible and you don't focus on specialisation, but instead focus on gaining knowledge and then apply yourself and learn what fits your needs best at that point in time. 

I started off working on data in all its forms in business; 15 years ago, I was all about creating data warehouses and marts and building various transactional systems to capture data. What I found was to put that data to work, businesses had to figure out cheaper, faster, scalable ways to get it to work for them--and I was soon seeing AI, and especially Auto ML, as the most promising ways of putting that data to work, as opposed to us working on the data all the time. 

Now at, we are seeing global brands, the public sector and non-profits looking at cloud and AI to increase revenue growth, optimise operations, mitigate risk and personalise customer experiences. They are using AI technologies to drive such transformation. And the use of world-class automated feature engineering, machine learning (autoML), MLOps, and low-code business applications framework from us means innovation from initial idea to real-world impact gets to happen so much quicker.

Talk me through your books. Why did you decide to write them? What was the biggest lesson you learned when writing?

I have co-authored, or been the lead author, on five books, so far. And every one of those books has coincided with a question that I had at a point that I was in my career where I went out and tried to find answers to key questions. I always ended up thinking it would be good to find the answer and share it with people who care.

My first book was not about AI at all. It’s about intercultural communication and software management, about how people from different cultures and different proficiencies in English use language, and could work better together in international software development settings. In the late 90s and early 2000s, despite all the fuss about offshoring, there was not much work on that. The second book was on Business Intelligence, which was still relatively new in the late 2010s, and the pattern repeats, I guess: find a problem and try to help people answer it.

Being a writer also shapes my daily practice, quite significantly. I read a lot, because I think a big part of being a writer is also being a reader of different perspectives, especially perspectives that you don't agree with and using that to inform yourself. I also try to speak to a lot of people and will reach out to somebody who can teach me something. Sometimes that can be a challenge with everyone’s schedule, but I have always been a very early riser, so I make it work. I really want to keep that outreach up, too, as that's how I keep myself challenged and fresh.

My latest book, for which I was a lead co-author, is entitled: Demystifying AI for the Enterprise: A Playbook for Business Value & Digital Transformation and covers machine learning, chat-bots, robots, agents, and so on, and how they are increasingly being seen as core components of enterprise business workflow and information management systems. 

My previous book was Demystifying Big Data and Machine Learning for Healthcare.

What are your biggest strengths? How do you apply these in your work?

I'd say my biggest strength is I don't take myself seriously. I call that a strength, because it allows me to break the ice with people; it allows me to talk about serious topics in a lighter vein. It's a great icebreaker on Zoom calls and most importantly, if people don't remember me for my content, at least they'll remember me for my comedy.

I would also have to say that my great greatest weakness is that I don't take myself too seriously! Sometimes in certain settings, where you are expected to maintain something equivalent to the stiff British upper lip, I can struggle.

What’s next for you? What do you hope to achieve in the future?

Like I said, it’s been all hands-on deck for me and colleagues here at H2O around helping fight COVID and drive business value and transformational change for all our global clients. Now, we are starting to see that a lot of the work we’ve done in the commercial space and in the public health arena with COVID can also be applied in government settings at the local, regional, national, and international levels. That's shaping my 2022 and 2023 thinking a lot, because the technology is maturing, and AI is really starting to be valuable, useful but also trustworthy. 

Professionally, I would love to see more customers build more models and applications and put them into production so that more of their customers, users, and co-workers can benefit. And that's going to be the overriding goal for 2022--as it always is for me.


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