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Introduction and Landscape

Computing has transformed and continues to transform all sectors of our society and economy. Its impacts on the U.S. economy, which are seen directly (the computing sector itself) and indirectly (all the other sectors that are powered by computing advances), continue to grow.

At its root, computing is the systematic process of using and manipulating data, typically through the use of computers and computational devices, to perform various tasks, solve problems, and achieve specific objectives. It encompasses a wide range of activities, including but not limited to data analysis, software development, algorithmic problem-solving, information processing, and system design. Computing involves both theoretical principles and practical applications, drawing on concepts from mathematics, logic, engineering, and other disciplines as well as encompassing elements of the arts, humanities, and social sciences.

“Computing” as used in this report denotes multiple computing-related disciplines, including computer science, information science, computational science, and computer engineering. Many fields outside of these core disciplines also engage in computing activities. Examples include data science, computational physical and biological sciences, and interdisciplinary applications of computing in the arts, humanities, social sciences, health sciences, business, economics, and more. In some cases, subdisciplines of computing, such as machine learning and robotics, have grown to form their own departments. Burgeoning fields such as artificial intelligence and quantum information science are further reshaping the computing landscape, driving advances across disciplines and prompting new educational and research initiatives. At the same time, many

universities have aggregated computing-related fields into schools or colleges of computing or information and computing sciences.

Over the past several decades, the production of undergraduates majoring in computing fields has grown dramatically. Between 2012 and 2022, the number of undergraduate computer and information science degrees awarded grew 129 percent, well above the 12 percent rate of increase for bachelor’s degrees overall (NCES 2024). Although the number of computing graduates has fluctuated cyclically (and indeed anecdotal reports suggest that another dip in hiring, which generally correlates with a future dip in undergraduate enrollment, may be under way as of the writing of this report), notably following the late 1990s “dot-com bubble,” the number of undergraduate degrees awarded has trended steadily upward (NASEM 2018a). Indeed, the lowest point in each cycle is generally higher than the peak in the previous cycle. Computing’s pervasive integration into the economy suggests an upward trending demand for talent in the future.

One distinctive feature of the most recent upturn in undergraduate enrollment has been a sharp increase in demand from non-majors for upper division computing courses, reflecting the relevance and importance of computing in many disciplines (CRA 2017; Zweben and Bizot 2024, Table B9). The end result is a phenomenon unique to computing—departments not only support thriving computing degree programs but also have become major service units for their institutions. Despite the increase in undergraduate enrollment, faculty hiring has not kept pace with the growing demand for computing courses and research. Together, these create a high demand for both tenure track and teaching track faculty.

Demand for computing research talent—and thus doctorates in computing—is also high outside of academia. At the same time, many undergraduates opt for industry positions because, unlike other science, technology, engineering, and mathematics (STEM) fields where doctoral degrees are needed for advancement in the field, lucrative opportunities abound. Graduates with computing backgrounds are in high demand for their skills and expertise, and this expertise is also widely applicable outside of the computing industry. Thus, concerted efforts are needed to attract enough undergraduates to doctoral studies in computing to fill industry, government, and academic positions.

The high demand for talent in industry reduces the number of students who go on to doctoral studies. This phenomenon is akin to “eating the seed corn rather than planting it.” Industry may meet its immediate needs, but in doing so depletes the pool of academic talent needed to train the next generation of undergraduate and graduate students. This shortfall in advanced-degree holders poses a significant challenge not only to sustaining the nation’s research and innovation ecosystem but also to maintaining global competitiveness. In particular, the growing gap in STEM PhD production

has serious implications for national security, technological leadership, and economic strength (VAST Task Force 2025). China, the United States’ largest economic competitor and national security rival, is outpacing the United States in the production of science and engineering PhDs overall (Figure 1-1) and especially in computing and related fields (Figure 1-2). Thus, if the United States is to remain competitive in the computing arena, it will need to invest in growing its computing workforce overall and especially the number of doctorates in computing.

Any effort to address the supply of doctoral students must take into consideration the multiple financial, career, and personal factors that influence an individual’s decision to apply and matriculate into a computing doctoral program. These decisions are rarely made based on academic interest alone. Prospective students often weigh the long time horizon and opportunity costs of a PhD against immediate earning potential in industry, concerns about debt, and uncertainty about academic or research career paths. Additionally, factors such as access to research opportunities, mentorship, work–life balance, visa status for international students, and the perceived value of a PhD in different career sectors all play critical roles. Table 1-1 outlines a range of incentives and deterrents related to earning potential, career advancement, research opportunities, skill development, and personal considerations. Designing effective strategies to attract more students into doctoral programs will require addressing these complex trade-offs directly, through both policy and institutional reforms. This includes expanding financial support

mechanisms, increasing the visibility and value of non-academic career paths for PhDs, and fostering supportive environments that make advanced study more accessible and appealing to students from a variety of disciplines.

To address these challenges, the National Academies of Sciences, Engineering, and Medicine undertook this study, sponsored by the National Science Foundation’s Directorate for Computer and Information Science and Engineering. It assesses trends in supply and demand, pathways, and flows toward advanced degrees in computing and computing careers, the balance between doctoral degrees awarded to U.S. and international students, and areas of potential shortfall and their implications for the health of computer and information science and engineering disciplines and academic programs. It also considers the ways that colleges and universities, scientific and professional societies, and industry partners could help address anticipated shortfalls in doctoral degree production, as well as the additional data that might be required to better assess trends and impacts for the future.

The remaining chapters of this report explore current trends and potential interventions.

TABLE 1-1 Factors, Incentives, and Disincentives to Pursuing a Doctoral Degree Computing

Chapter 2 examines the past, current, and future supply and demand for computing PhDs using historical data, expert testimony, and supporting information on hiring trends and organizational responses of those receiving doctoral degrees in computing.

Chapter 3 further explores sector-specific hiring implications for computing doctorates in industry, academia, and national security and other government positions, concluding with recommendations concerning supply and demand.

Chapter 4 discusses how undergraduate research awareness, participation, and mentoring can encourage students to pursue doctoral degrees in computing, highlighting the need for targeted, context-specific interventions to boost domestic participation in these programs.

Chapter 5 considers approaches for enhancing recruitment efforts and increasing the retention and graduation rates of students in doctoral computing programs as well as how to build and sustain the faculty needed to train the next generation of PhDs in computing.

Chapter 6 turns to the expanding and evolving routes to doctoral degrees in computing, highlighting the various pathways, including traditional, non–computer science undergraduate backgrounds, alternative programs, and the importance of lifelong learning.