3 Steps to Meeting Government Artificial Intelligence Mandates

A solid interconnection strategy and platform are required

Could artificial intelligence (AI) redefine a country and give it a significant competitive advantage on the global stage? This is exactly what the U.S. Federal Government is counting on with its recent Executive Order on Maintaining American Leadership in Artificial Intelligence. The U.S. joins more than 20 countries, including Canada, China, the Europe Union, Japan, Mexico, Taiwan and South Korea, that have released guiding documents on their AI strategies. According to the February 11, 2019 White House Executive Order:

“Artificial Intelligence (AI) promises to drive growth of the United States economy, enhance our economic and national security, and improve our quality of life. The United States is the world leader in AI research and development (R&D) and deployment.  Continued American leadership in AI is of paramount importance to maintaining the economic and national security of the United States and to shaping the global evolution of AI in a manner consistent with our Nation’s values, policies, and priorities.”

Meeting the new AI mandate is a tall order for U.S. Federal Government agencies, with a lot at stake. It not only requires investment in AI and cognitive technologies, but a focused strategy on how to integrate them with other technologies (e.g., cloud, data management, analytics and cybersecurity) for governments to succeed in an increasingly digital world.

Why AI is critical to federal agencies

Seen as being one of the most transformative areas in the digital age, IDC estimates AI and cognitive technology spending will grow to $79.2 billion by 2022 and achieve a compound annual growth rate (CAGR) of 38% over the 2018-2022 forecast period.[i] According to IDC, federal and central government will be the fastest growing sector at a 44.3% CAGR.

The adoption of AI and related technologies such as machine learning (ML) and robotic process automation (RPA) supports a wealth of use cases in the government and public sector, including:

  • As the U.S. Government’s homeland security activities increasingly dominate the news, the focus on more efficient security and threat management and evaluation is also heightened. Collecting, processing and analyzing all the relative data that is required to assess and identify nationwide security risks requires higher-level AI and ML for fast and proactive threat migration and response.
  • Public well-being and safety require AI systems to effectively assess damage and respond during any type of disaster (natural or man-made), and are critical to enhancing existing frameworks, such as FEMA’s National Emergency Response System and the national AMBER Alert system.
  • Public services delivery and administration also require AI to accurately evaluate and meet citizen’s needs. AI enables the federal government to be more responsive to the public by quickly and accurately analyzing massive amounts of data across multiple agencies, and correlating it to develop better ways to serve and communicate with their constituents.
  • More than 23 U.S. defense and civilian agencies began using RPA in 2018 to gain greater efficiencies and savings by replacing manual-intensive tasks with robots. For example, the Defense Logistics Agency Information Operations automated parts of its onboarding process for an annual savings of $2 million and the General Services Administration uses six robots to shoulder work that took humans a combined 12,000 hours per year to complete.[ii]

 

By not following the recent AI Executive Order, government agencies run the risk of not executing their missions, losing critical funding, and not meeting the immediate and long-term needs of their employee and public constituents. Most importantly, the U.S. could lose a valuable competitive advantage as a world leader. Countries around the world are ramping up their AI initiatives to accelerate digital transformation in practically all areas of government. This is evidenced by their increased focus on AI research, skills training, ethics development and many other AI-related areas.[iii]

How to fully leverage all that AI and digital have to offer

Similar to the commercial sector, the market trends for the public sector are evolving. Workloads are shifting to cloud, creating new security and data distribution challenges that require increased spending in data management and cybersecurity within tight budgets. Meeting employee and public service expectations means providing a more enhanced user experience, while still maintaining changing security and compliance requirements.

To succeed in their digital transformation, Government agencies will need to deploy heterogeneous, end-to-end data sharing models that interconnect people, locations, clouds, data and things locally and globally. At the same time, they will need to integrate new capabilities, such as AI, ML and RPA, along with other digital technologies such as cloud, data management, analytics and security.

To accomplish all of this and more, Government agencies are moving from legacy centralized, siloed and static information infrastructures to distributed, integrated and dynamic platforms based on private interconnection at the digital edge. According to the Global Interconnection Index Volume 2, a market study published by Equinix, private Interconnection Bandwidth in the public sector will grow at a 66% CAGR between 2017 – 2021.[iv]

The following are three steps that government agencies can take to deploy an interconnected, digital edge strategy, roadmap and platform:

By following these steps, Government agencies can gain the following capabilities and benefits:

  • Global Coverage, Performance and Scalability: Globally distributed digital edge control points, located close to agencies, employees, partners, things, delivers high-performance, lower-latency connectivity and capacity scalability for a greater user experience.
  • Partner and Ecosystem Density: Direct and secure interconnection enables private information exchange with AI, ML and RPA partners and other digital ecosystems (networks, clouds, SaaS) to accelerate the deployment of next-generation digital IT infrastructures. Government agencies will also be able to scale compute, storage and applications with hybrid and multicloud via an as-a-service model to stay within more constrained budgets.
  • Integration and Control: Integrating digital and physical services via private interconnection, efficiently and cost-effectively provides greater control and optimizes security, data management, applications and multiple agency interactions, enabling real-time insights.

Leveraging transformative technologies such as AI on a globally distributed, interconnected platform will enable government agencies to future-proof their IT infrastructures to proactively meet evolving mission, policy and user requirements. Most importantly, the U.S. will be able to continue to advance its leadership position in an increasingly digital world.

To learn more about the specific steps that Government agencies can take to maintain a global competitive advantage as a digital government, read the U.S. Federal Government Digital Edge Playbook and Federal Government Blueprint.

[i] IDC, “Worldwide Semiannual Cognitive Artificial Intelligence Systems Spending Guide,” 2019.

[ii] NextGov, “How to Fund an Unfunded Artificial Intelligence Mandate,” 2018.

[iii] CIFAR, “Building an AI World: Report on National and Regional AI Strategies,” 2018.

[iv] Equinix, “Global Interconnection Index Volume 2,” 2018. 

 

 

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