Federal agencies and their Federal Systems Integrator (FSI) partners are considering how to tap into artificial intelligence (AI) to advance their missions. The National Security Commission on Artificial Intelligence is calling on Federal leaders to double research and development spending on AI, to $32 billion by Fiscal Year 2026. As with any new technology, there is uncertainty on the best way to move from pilot projects in the lab to fully implemented production solutions.

MeriTalk recently sat down with Bob Venero, CEO of Future Tech Enterprise, Inc., to talk about how agencies and FSI’s can overcome barriers to get AI programs up and running quickly, and contribute to mission success.

MeriTalk: We know Federal agencies are dipping their toes into using emerging technology including AI and machine learning (ML) to support a wide range of projects. A recent survey found that 60 percent of Federal IT decision makers say their agency has more than 10 AI pilots in the works. What are some potential use cases for government agencies to realize the benefits of this technology?

Venero: The possibilities really are endless when it comes to what AI and ML can do to support Federal agencies. Let’s talk about things that are top of mind for Federal agencies and Federal System Integrators (FSIs) right now. The Biden administration issued two significant executive orders since taking office. The first was the Executive Order on Improving the Nation’s Cybersecurity, known as the Cyber EO, the second was the Executive Order on Transforming Federal Customer Experience and Service Delivery to Rebuild Trust in Government, known as the CX EO. Artificial intelligence can help Federal agencies meet the mandates outlined in both orders – and quickly.

Looking at cybersecurity, AI can process massive amounts of data coming in from across the agency and do so much faster than cybersecurity teams. AI/ML technology can analyze trends and spot unusual behavior, alerting security teams who can act on that information. While it could take weeks or even months for security teams to detect unusual patterns of behavior, AI technology can cut that time down significantly, stopping potential breaches before they lead to significant data loss.

For the CX EO, AI can easily be incorporated into customer touchpoints, like Federal websites where constituents go to access their services. Simple tools like AI-powered chatbots can answer questions quickly and direct people to the information they need without waiting in long customer service phone queues. This type of service not only meets some of the EO recommendations, it also is something that the American people are demanding. Our partnerships with industry leaders like Dell Technologies and NVIDIA support AI/ML missions and specific regulatory and cybersecurity requirements, ensuring these demands are met.

MeriTalk: Some could argue that AI is the shiny new technology tool, and that agencies should focus their limited resources on other projects that have an immediate impact while taking a wait-and-see approach implementing AI use cases. Should agencies proceed with caution when investing in AI?

Venero: While it is true that technologists like to embrace new tools, there is merit in doing so. New technology also builds on existing capabilities. In terms of AI, the technology relies on fast connectivity and a solid infrastructure that supports big data use and manipulation. If agencies have waited on modernizing their infrastructures, they are behind in implementing AI use cases. It’s a domino effect. We have only scratched the surface of what AI can do, so not taking those first steps with using the technology and building that knowledge base within the organization now could set agencies back for any future advances. In the examples I gave, the technology is already proven; Taking a wait-and-see approach means that agencies will always be behind.  (And in cybersecurity, you can bet the adversaries are not waiting to adopt and deploy these new technologies.)

MeriTalk: As Federal agencies continue to work through their modernization roadmaps, what should they consider if they want to integrate AI capabilities now?

Venero: AI use cases are built on data. That data is coming in from any number of sources, including the edge. AI use cases often fall short because the underlying infrastructure can’t support all of that data for data scientists to manipulate. Plus, data scientists can be overwhelmed with the volume and velocity if the technology isn’t there to automate, sort, store, and process that data. Legacy technology isn’t built to keep up at that scale. Organizations that want to realize the full potential of AI can accelerate their modernization roadmaps, including moving away from legacy data centers and into the cloud and modern hybrid environments. They can also consider storage solutions that scale. Integrating automation and data science tools is critical. Another thing to consider is that data needs to move from one place to another, which requires improved connectivity through 5G. Building a solid foundation with modern technology will open the many possibilities AI can offer now and in the future.  Finally, new technologies such as NVIDIA’s EGX/DGX can vastly reduce the time it takes to get actionable intelligence from massive data lakes.

MeriTalk: That same survey of Federal technology leaders found that 71 percent say their agency struggles to move AI projects from the pilot phase to integration with broader IT operations. What are some of the reasons? What are the barriers holding Federal agencies back from realizing the full potential of AI?

Venero: There are a few things that stop AI pilots from becoming fully operational. One goes back to the fact that many organizations are dealing with legacy technology. While the pilot program may have been built with the proper foundation to support the technology through the pilot, moving into the much broader agency environment could be problematic if that environment still has legacy components that don’t scale. Another barrier is change management. Federal technology teams are stretched right now, especially with the tight job market. They are doing more with fewer resources. That ties into another barrier, which is a knowledge gap. This is new technology and teams may not have resources with the right skillset to fully realize the technology’s potential on a broader, agency-wide scale. The leadership team may be hesitant to implement AI simply because they don’t fully understand it and are thinking about compliance and regulatory issues which might be an issue. Then, of course there is budget, which seems to be a barrier for any new technology implementation.

MeriTalk: How can agencies overcome the barriers and accelerate their AI programs?

Venero: Federal technology teams aren’t in this alone. The potential for AI to make a real impact on so many things that affect missions – including cybersecurity, customer experience, research and development, and national defense – is significant. Agencies can look to industry partners who are experienced in working within Federal compliance regulations and also have a proven record of bringing AI use cases to production quickly. Partners can educate leadership teams and get them on board with exciting projects, starting small and building on success. They can also supplement existing resources, deliver technology that can integrate with existing infrastructures, and build the implementation roadmap from inception through pilot to full implementation to ensure the project’s success.

MeriTalk: How can Future Tech help Federal agencies and mission partners mature their AI capabilities?

Venero: As we’ve discussed, AI relies on data, and that is where Future Tech delivers significant benefits for agencies, their FSI partners, and other leading companies in various sectors. We are an award-winning IT solutions provider that supports agencies overwhelmed with data, with our Data Science Workstations, which integrates hardware and software computing power to help data scientists work through all that data, which can then be used to build AI use cases.

We offer a pre-configured, curated data science software stack that gets data scientists up and running quickly, speeding the time to implement AI applications.

We help embed data science best practices across the enterprise, ensuring that data management, collection, and insights are available for teams across the agency to use. We also provide AI professional development support – educating teams and leaders as they work to overcome AI barriers. We’ve found we can reduce end-to-end data science workflow timelines by up to 80%, helping teams work smarter, faster, and safer. This is why we were recently named Dell Technologies Transformational Partner of the Year and earned NVIDIA Partner Network’s (NPN) 2021 Americas Public Sector Partner of the Year. Wherever an organization is in their AI journey, Future Tech has been there and can help guide them to the next level.

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MeriTalk Staff