The stakes for the federal government surrounding its adoption of artificial intelligence (AI) are high. Beyond the scale, diversity, and criticality of its various missions, government is arguably the largest holder of data in the world. Get it right and the federal government could lead the world in using AI to improve health outcomes, solve the climate crisis, raise living standards, and much more.
How close are we to delivering on AI’s full potential? Let’s consider the current state of play:
- The advancement of AI over the last few years has been remarkable — we are truly in a golden age of development when it comes to AI.
- These advances have demonstrated the clear value that AI can offer businesses; soon, it will become an integral aspect of how most businesses operate.
- Federal agencies have been leaders in defining the responsible, ethical, and appropriate use of AI.
- But even as federal agencies make progress in their use of AI, truly embedding it within federal operations will require more flexible, integrated, and comprehensive approaches — from from rethinking how data is organized to who can perform AI and more.
Based on our work across the spectrum of federal missions — from civil services and health to defense and national security — we’ve identified four emerging building blocks that federal agencies can use to build a solid foundation for AI’s long-term success.
1. Data-Led Transformation
Across the federal government, tech ecosystems are becoming amorphous. Today, there is almost no clear separation between the applications and data that people use, making it more important than ever to have control over your data. And, to do that, you first need to gain control of the ecosystem, prioritizing data as a strategic asset that can be accessed, connected, and managed at scale. You also need to think about privacy concerns — that is, who should have access to what in an organization. Getting this right requires a comprehensive approach to data, from strategy and planning to implementation and operations. That’s what we call data-led transformation.
Data-led innovation is a critical piece of the AI puzzle because you need to make sure that when you create solutions to access your data, for the long term, you do so responsibly. So the first step in any responsible data-led transformation is to fully understand where your data sits and how you want to use it. It often requires modernizing some infrastructure to present it in a more responsible, managed, secure, and cheaper environment, allowing you to use the right data more easily at the right time and for the right use case . Typically, migrating workloads, or data structures, from legacy platforms such as mainframe to the cloud is an essential part of any data-led transformation.
2. Democratization of AI
More democratized AI can break down the barriers between the business and IT sides of an agency — thereby helping to close the implementation gap. In other words, getting AI into the hands of more people, faster, can significantly increase the speed and reduce the cost at which insights can empower decision makers and improve operations. of the mission.
Of course, in the past, if you wanted to use AI directly, you had to have a PhD and programming skills to manually program algorithms to generate the prediction and the pipeline you wanted. Now, with the advent of low-code environments and new data engineering techniques, citizen data scientists can work alongside classically trained data scientists and engineers, using AI pipelines that can be built with precision and drag-and-drop ease. This will help organizations overcome skills gaps and ultimately see more immediate and actionable value from AI.
3. Distributed Intelligence
Over the past five to 10 years, we’ve seen a tremendous increase in available computing power. Plus, with the addition of 5G and Wifi 6, the network speed has become even faster. Enabled with AI, this continuous distributed intelligence can give federal agencies powerful new capabilities. We are becoming faster at capturing data, querying data, making predictions, and gaining insights into the future, all outside the traditional IT perimeter.
The potential for these autonomous, intelligent systems is enormous — think robots, self-driving cars, drones, virtual agents, and wearables. For example, our population is aging rapidly, both in the US and around the world. However, we do not have enough caregivers to enable this entire population to continue to live independent, dignified, and fulfilling lives. Assistive robots and similar systems can fill this void, handling daily tasks and supporting mobility, proactively monitoring health and well-being, and even offering companionship. The combination of smarter, smaller, and more powerful computing — combined with faster communication protocols — enables systems that autonomously perceive, learn and respond with confidence.
4. Intelligent Platforms
These emerging trends in AI all bring a variety of new opportunities, but they also bring complications. For agencies to most effectively embrace them, we need intelligent platforms to bring them together. The government already uses many low-code AI development platforms, such as Salesforce, Pegasystems, and ServiceNow, all enabled by the rise of the cloud and containerization.
Platform-centric approaches increasingly enable agencies to narrow the skills gap between the various stakeholders involved in a process. They can marry procedural logic with declarative logic, or machine learning and predictive logic, increasing the ability to transact and execute decisions within the same platform.
The future of AI is agile and flexible and, in many ways, it’s already here. By exploring and implementing these four trends, federal agencies can receive greater value from their data and work toward harnessing the full potential of AI.
Interested in learning more about how AI will impact the future of government? Stay tuned for more content here from our team at Accenture Federal Services. In the coming weeks, we’ll be publishing in-depth articles on each of these four trends. I’d love to hear your questions and thoughts on what’s working well at your agency; please connect with me on LinkedIn.
Michael Scruggs – Managing Director, Accenture Federal Services, Applied Intelligence Lead