How NetApp is making enterprises AI ready

Artificial intelligence (AI) and GenAI have turned the world upside down for enterprises on how they view, analyse, and use their data. Amid these fast-paced changes, global storage technology company NetApp is keeping its innovation engine in top gear to address the various AI data requirements of enterprises, be it through newer products, strategies, or consulting.

In an interaction with EnterpriseStory, NetApp Chief Product Officer Syam Nair and Premalakshmi PR, Area Vice President, India & Saarc, NetApp, discussed the nuances of data management in the AI era and how the company is helping enterprises to bring about the transformation. They also highlighted the role of NetApp’s India engineering centre in advancing AI innovation.

“We are grounded by the realities of what customers want and tend not to chase the hype but we do innovate,” Nair said. Edited excerpts:

EnterpriseStory(ES): How are enterprises looking at data from the point of view of AI?

Syam Nair: Firstly, enterprises are looking at how they can optimise the overall cost of delivering value out of AI given that these are all really large capital expenditures. It is about how they can get the value out of it without much capital expenditure. Secondly, the value of AI is only as good as the access to the data. Today, it is much more complex, the pipeline in terms of preparing the data, the number of hoops people have to go through so that the data is accessible. They are asking for reducing the complexity and cost.

Third is the proliferation of data, because every workload needs this data. There is no single view of the entire data estate. When data proliferation happens, it's very hard to actually protect the data. What kind of policies are in place? So, these are the three things that we normally hear from enterprises.

ES: How can enterprises make their data AI ready?

Syam Nair: Until recently, before the Gen AI and the LLM models came along, it was structured or semi-structured data. Now we are talking about multi-model data that has a lot of meaning. Our data engine does not just provide the metadata about the data or the file. It actually goes into it and extracts attributes. So, by building a data engine that is sitting closer to storage is true power as data becomes knowledge to drive your business. As AI evolves, IP is no longer about anything other than your data. That is a huge opportunity for us.

ES: How does NetApp see the level of AI readiness in India?

Premalakshmi PR: If one looks at just the sheer number of investments, which is going into AI from an India standpoint, we're talking about around 35% growth annually. Every single enterprise is also putting that as part of their budget. We are looking at $9.3 billion investments by 2028. Indian enterprises are AI ready but are they able to take AI to scale is where the struggle is.

There are specific AI use cases which are getting implemented and India enterprises are evolving in terms of bringing AI into use. So, I do really appreciate and recognise that effort. But they are also grappling with the challenges on data quality. They are looking at partners who can really come and build this for them.

Today, enterprises have multiple data sets and integration becomes a really important concept. Then comes data architecture. We build that enterprise architecture with the ability to introduce the right data pipelines which can make them AI ready. This is the opportunity where NetApp is partnering with enterprises to see how we can continue to help them become successful at scale.

ES: What is NetApp’s approach to the data ecosystem as information no longer resides in just one enterprise or at a single place?

Syam Nair: There are three elements to it. Number one is how we integrate with the IT ecosystem. Number two is actually delivering value using these foundational models. The third one is being very open in terms of using the protocols for the integration of data.

We are trying to move up the stack in terms of providing value to the customers in the world of AI. This would mean data infrastructure growth, quality of data, and lastly protecting this data. We are bringing all of that. We are now seeing investments in AI on the compute front but the next will be on the data infrastructure side. We are well set up for that, leveraging our platform for that growth.

ES: What is your view on the talent scenario in India?

Syam Nair: One of the ways I assess talent is by looking at how long our engineers have been with the company. Second is how innovative they are in terms of driving change. The team in our Bengaluru office is not resting on the laurels of the past; they are actually driving innovation. We have built a really good engineering talent base in India that is designing complex systems to solve and simplify customers’ problems. Over time, we have built a very loyal and progressive talent base that can understand the market, customers, and technology.

Premalakshmi PR: Every single customer talks about the engineering partnership that NetApp provides them and that's clearly an undue advantage that we have. This would not have been possible without the right talent who are willing to co-innovate, co-create, and bring the right strategies for customers to evolve.

We also have a centre of excellence (CoE) set up within our engineering facility where our customers can partner with our engineering team to test, value, and then take it into production of any new product or solution. This also builds more trust and collaboration with our customers and partners in the market.