Federal Agencies Are Laying the Foundation for Artificial Intelligence

Published: April 12, 2017

Federal Market AnalysisBig DataCybersecurityInformation TechnologyInformation TechnologyOSDResearch and Development

Agencies are spending millions of dollars annually building the foundational elements of Artificial Intelligence.

Browsing through the media the last few weeks readers may have begun to notice more and more pieces on the potential benefits of Artificial Intelligence (AI) for federal agencies. Even Congress has been getting into the act. For example, during a session on March 22, 2017 titled, “The Promises and Perils of Emerging Technologies for Cybersecurity,” the Senate Committee on Commerce, Science and Transportation heard testimony from several industry specialists concerning AI, the blockchain, and the Internet of Things.

The hearing comes at a time when agencies are struggling to muster the funding and expertise required to modernize severely antiquated technology infrastructures. Given that agency technology is falling further behind the commercial world every day, the first thought that came to my mind regarding the federal government’s use of AI is “keep dreaming.” Agencies are having a difficult enough time determining how to adopt cloud computing and industry wants them to buy advanced technologies like AI? Maybe in 10 years.

It could be that my cynicism on this subject is misplaced, however, because the more I learn about AI the more I come to realize that its building blocks are already in place at many agencies. The two capabilities at the heart of what some call “narrow” AI – a capability with a narrowly defined objective –  are machine learning and autonomy. Use of these technologies is already growing at the Department of Defense, for instance. More importantly for the future, leaders across the DoD understand that in order to improve the department’s cyber posture they need to invest in automated capabilities that augment the personnel they have dedicated to cyber defense and warfare and this understanding generates calls for increased funding.

Select civilian agencies, like DHS, DOE, NASA, and others, use machine learning as well and they are exploring autonomy for things like self-driving cars and unmanned vehicles. Putting hard numbers behind the trend toward machine learning, I refer to the chart below, posted several weeks back in an article on big data analytics spending from fiscal 2014 to 2016.

It turns out that most if not all of these analytics solutions either possess machine learning capabilities or they have modules that can be adapted to interface with machine learning algorithms. In other words, as I noted in the article, in fiscal 2016 alone federal agencies spent $200M on big data analytics with machine learning capabilities, meaning that many agencies are already well on the way toward being able to make use of AI technology in one way or another.

As for spending on autonomy, I don’t have detailed figures. However, based on an analysis of forecast DoD Procurement and R&D programs with a big data-related component, meaning use of an algorithm or advanced analytics of some kind, I can say with some degree of confidence that the DoD intends to spend an average of approximately $780M per year from fiscal 2018 to 2020. Many of the programs captured in this analysis rely on technologies that enable autonomy and enhance man-machine interfaces for unmanned vehicles.

In sum, if machine learning and autonomy are properly considered the building blocks of narrow AI, the reality is that federal agencies are already spending millions of dollars per year establishing an AI foundation. Maybe a computer like Hal from the movie 2001 isn’t so far off after all.