Hitachi Vantara Federal CTO Gary Hix on GovCon Data Trends & Challenges

Hitachi Vantara Federal CTO Gary Hix on GovCon Data Trends & Challenges - top government contractors - best government contracting event

Across the public and private sectors, organizations are taking in more data than ever before. Now, as federal and industry executives work to process, analyze and harness their data to drive decisions, technologies like artificial intelligence are making the process faster and more efficient. 

Executive Mosaic spoke with Gary Hix, chief technology officer of Hitachi Vantara Federal, to learn more about how agencies are deploying AI, the hurdles that remain in widespread adoption, the future of AI in data analytics and more. 

Hix has been with Hitachi Vantara Federal for nearly ten years and has spent the past three in the CTO role, giving him unique insight into the federal technology landscape and the trends that shape it. Read below for his full Executive Spotlight interview.

Tell me about the current state of the artificial intelligence market. Where are you seeing new opportunities in AI, and where do you think the market is heading?

We see an increased focus on how AI can improve services that can meet the mission. What we’re seeing is a lot more data being stored, but also needing higher speed access to that data. That’s an area where there are opportunities for parallel file system solutions and things that can scale up to really high speeds for data access and allow organizations to do data analytics around that data as well. There’s a lot of interest in that area, but a lot of these programs are nascent. Everyone has known that this is coming, but what they’re looking for is how to operationalize it or actually make all this data actionable now. We haven’t had a lot of ability to do that before, and there hasn’t been broad consensus buy-in like there is now.

What are some of the key barriers that remain in widespread federal AI adoption, and how do you think we can overcome them?

I think a lot of it is just getting the right people in, whether it’s in the government or in industry or in the integrator. It’s a challenging skillset to find at times, and there’s a finite number of people who can help with that. Those people are in high demand, and it’s similar in cyber — there’s a ton of interest, but not a lot of resources. So I think the first part of it is finding the right resources or industry partners to help adopt. 

It’s also then identifying and cataloging all that data, because there’s so much data resident in all these different programs and departments that people aren’t even aware exists. It’s understanding the data that’s out there and then allowing sharing of that data. What we don’t want is 1,500 copies of the same type of data in a single agency when we can just put in place the correct data governance and federation of that data in that environment to allow everyone to leverage that data. 

Ultimately those are the two big areas: knowledge of the data and access to that data, as well as the resource and skills gaps that exist in that area. Everyone has gotten away from the fear of AI and has started realizing that it’s a good technology — now it’s just finding the right people and tools to implement it. 

Data is often coming from multiple sources that organizations need to collect, analyze and understand in order to use it. What are some of the key challenges and opportunities you’re seeing emerge as organizations harness data and use it to drive decisions?

The speed to decision is improved and as we continue to leverage it, we’re seeing improvement of reliability. We’ve heard a lot about AI bias, but as the technology matures, people are getting to where they’re trusting it more and operationalizing it. So organizations are seeing that speed to action is improving every time they run this type of model or analytics in that space. But there are still very many groups and agencies that are wondering where to start with AI and curious how it can affect them. Not everyone has a workload or a mission they feel can handle AI improvements. 

What do you think is the most challenging aspect of digital modernization and why? How does Hitachi Vantara Federal help its customers overcome that challenge?

Some of the biggest challenges I see in digital modernization center around getting the right operational improvements in place to modernize the environment. That means not just moving to the same platform, but looking at what’s going to be much more flexible and open for the future as organizations go into new technologies. 

A lot of our customers have technologies that are frankly two to three generations older, and they’ve just been forced to maintain it because they couldn’t do technology refreshes. A lot of the areas that we see improvement in from Hitachi Vantara Federal are things like our storage virtualization, which is part of our virtual storage platform and assists our customers with minimizing the disruption associated with moving to new technologies. Basically what we do is virtualize a customer’s existing storage, regardless of whose it is, and very non-disruptively move it in the background and do that data migration. 

All the customer has to do is take a quick reboot and then they can continue their normal operations. There are also some other areas where we can help with solutions, such as our converged stack that’s partnered with VMware. Those are the main challenges that I see with digital modernization: getting the right technology in place and getting the appropriate outage windows to maintain it. 

Hitachi Vantara Federal also has the ability to integrate operational technology. We can help our customers with addressing things like edge intelligence and sensor data at the edge in limited communication environments. That’s one of the things that a lot of our customers don’t realize we have in our portfolio. Taking advantage of all that data at the edge and operational technology is a major priority for our customers, and we can help them with that. 

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Written by Summer Myatt

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