Political, military, and corporate leaders from around the world continue to highlight the significance of artificial intelligence (AI). After Canada became the first country to release its AI strategy in 2017, 18 countries have followed suit in some capacity—nine have fully funded strategies, and nine have produced guiding documents.1 The United States recently joined this group with the president signing an executive order that details a coordinated federal strategy regarding AI.2 Despite substantial discussion and attention to the topic, there is no universal agreement on the definition of “artificial intelligence”; however, commentators broadly agree that AI is the scientific field concerned with algorithms and that it consists of several sub-disciplines. Since AI has applications for an incredibly large and diverse amount of commercial, military, and intelligence missions, some researchers have narrowed their analysis of AI by categorizing it as an enabling technology and comparing it to the steam engine or electricity.3

Thinking about AI as an enabling technology is especially useful for assessing AI’s ability to enhance strategic situational awareness (strategic SA) missions and for understanding how enhanced strategic SA might affect strategic stability. At its core, the strategic SA mission requires collecting information and making sense of it. AI applications have the potential to significantly impact both of these key strategic SA mission components. In terms of collecting information, AI autonomy applications, such as autonomously operated platforms and sensors, are reshaping the nature and effectiveness of technical strategic SA collection tools. Meanwhile, AI applications for all-source data fusion, front-line analysis, and predictive analytics promise the potential to unlock new insights and effectively enhance strategic SA. While autonomous operations of platforms, sensors, and cyber SA collection assets have their own sets of risks and benefits, this primer focuses on the AI applications that enhance the strategic SA mission through improving analysis.

Due to the rapidly changing nature of the field, the meaning of the blanket term “artificial intelligence” is constantly evolving. Broadly speaking, AI is a field of study that encompasses several disciplines including machine learning, automated reasoning, natural language processing, knowledge representation, computer vision, and robotics.4

Much of AI’s impact on strategic SA occurs through advances in a subset of machine learning known as “deep learning,” Broadly speaking, any AI software application is comprised of a set of rules known as an algorithm. The software subsequently “runs” or employs the algorithm to process data. Advances in AI technology have moved beyond hardcoded “frozen” software to produce AI programs that can engage in deep learning with Artificial Neural Networks (ANNs) loosely inspired by mammalian neural networks.5 Frozen software is limited by human knowledge. For example, although the IBM computer Deep Blue defeated chess master Gary Kasparov in a 1997 match, the IBM computer’s software was hardcoded, and thus its victory occurred through “brute force.” Today, AI research focuses on deep learning and the ability to learn and evolve without the constraints of human knowledge. Deep learning is a type of machine learning that employs “deep” neural networks. These networks have many hidden layers that operate between the input and output layers of the network.6 They are a series of connections among artificial “neurons” that learn by adjusting the strength of the connections between the artificial neurons to “optimize the paths through the network to achieve a certain output.”7

  1. Tim Dutton, Brent Barron, and Gaga Boskovic, Building an AI World: Report on National and Regional AI Strategies (Toronto: Canadian Institute for Advanced Research, 2018),

  2. Darrell M. West, “Assessing Trump’s artificial intelligence executive order”, Brookings Institution, February 2019, 

  3. Michael Horowitz, Artificial Intelligence, International Competition, and the Balance of Power,” Texas National Security Review 1, issue 3 (May 2018): 36-57. 

  4. Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach (Upper Saddle River, New Jersey: Pearson Education Inc., 2010), 2-3. 

  5. Robert Warren, “Artificial Intelligence and the Military,” RAND Corporation, September 7, 2017,

  6. Paul Scharre and Michael C. Horowitz, Artificial Intelligence: What Every Policymaker Needs to Know (Washington, DC: Center for a New American Security, 2018),

  7. Ibid. 

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