In the public sector, AI is seen as a mission-critical priority, starting in areas such as defense, cybersecurity and intelligence and expanding into broader citizen-facing use cases. With Executive Order 13859, signed on Feb. 11, 2019, the U.S. codified AI as a strategic imperative built on five pillars:
- Promote sustained AI R&D investment.
- Unleash federal AI resources.
- Remove barriers to AI innovation.
- Empower the American worker with AI-focused education and training opportunities.
- Promote an international environment that is supportive of AI innovation and its responsible use.
The Government Business Council (GBC) states that U.S. intelligence and defense agencies have been at the forefront of developing the next generation of AI tools focused on turning computers into “problem-solving partners.” Building on the success of AI in national security and intelligence is just the beginning. As noted by the GBC:
Government organizations are exploring other opportunities. Early efforts to introduce AI in citizen-facing web tools and various forms of electronic document processing by federal agencies were the foundation for testing early pilot programs. Other government agencies followed suit, with initial indicators pointing to a much larger role for AI in managing forms and documents as well as unstructured forms of data.
The question for decision-makers at federal agencies is not about whether AI is a priority but about how to modernize their technologies and operations to ensure AI success. As noted in the GBC survey, “Federal employees—including management staff as well as technical leaders—are ready for AI, but they see the technology as a strategic priority.”
The path to AI value in the federal government
As federal decision-makers seek to prioritize AI, there are several key technology features and capabilities that will optimize and accelerate their path to AI value. Here are infrastructure guidelines to consider for public-sector use cases.
In most federal agencies, today’s data infrastructure was built for applications such as data warehouses, enterprise resource planning and similar enterprise-type applications. While the infrastructure works fine for those applications, it is not capable of meeting the specific needs of AI use cases. In particular, AI requires:
- High-scale, massively parallel compute and analytics with the ability to deliver consistently high IOPS and metadata performance across every element of the data pipeline, including data integration, data cleansing and modeled results.
- Modern, state-of-the-art advances in server and storage technologies, including GPUs, high-performance file- and object- based storage, as well as latency-free connectivity to support the scale of analytics.
- Flexibility in deployment, with the ability to start small with pilot projects and then expand with linear scalability as compute and security requirements change and as the volume and variety of data increase exponentially.
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With the right platform in place, federal agencies have the opportunity to experiment with AI in a wide range of areas to serve public needs. One example is in dealing with the opioid epidemic, particularly in determining sources and trafficking. With the right edge-to-cloud-enabled AI platform and infrastructure empowered by unified management, AI can support:
- Collecting data at a massive scale.
- Coalescing and cleansing data from different sources, structured and unstructured.
- Processing the data and correlating it to sources to understand the problem.
- Leveraging intelligence garnered from machine learning and AI to take the right action at the right time.
- Building a sustainable model for government employees to maintain.
That’s just one example. Harvard Business Review cites a wide range of potential use cases, including making welfare and immigration decisions, detecting fraud, planning new infrastructure projects, answering citizen queries, adjudicating bail hearings and many more.
Are you ready to take the next step and move from AI priority to AI reality? FlashStack for AI from Cisco and Pure Storage can smooth your path to AI value in public-sector use cases. Please review the articles and resources on this TechTarget site, including this white paper on the use of AI and ML in the Department of Defense.
