Chapter 6: Technical Talent in Government

Following is a summary of Part I, Chapter 6 of the National Security Commission on Artificial Intelligence's final report. Use the below links to access a PDF version of the Chapter, Blueprint for Action, and the Commission's Full Report.

The artificial intelligence (AI) competition will not be won by the side with the best technology. It will be won by the side with the best, most diverse and tech-savvy talent.

The Department of Defense (DoD) and the Intelligence Community (IC) both face an alarming talent deficit. This problem is the greatest impediment to the U.S. being AI-ready by 2025.

The Current Model

Real obstacles impede recruiting and retaining AI practitioners and broader digital talent. The government does not compete with private-sector salaries and suffers from a cumbersome hiring process, and all reforms are hindered by a slow security clearance process.

We should not accept an undesirable status quo as the inevitable future. The government can compete with the private sector for talent. The government may not match private-sector salaries, but it does offer the opportunity to tackle national security challenges and to make a substantial contribution to society.

The biggest obstacle hindering the recruitment of digital talent is not compensation. It is the perception, and too often the reality, that it is difficult for digital talent in government to perform meaningful work, with modern computing tools, at the forefront of a rapidly changing field.1

“The Commission is not persuaded by the argument that the government should focus on project management and data collection and management, and outsource all development.”

Government strategies that do not develop a government technical workforce are short-sighted. Government agencies that rely solely on contractors for digital expertise will become incapable of understanding the underlying technology well enough to make successful acquisition decisions independent of contractors.3 This situation creates national security risks.

1. Organize

To generate and manage a proficient digital workforce at the scale required by the national security enterprise, the government needs to establish a talent management framework tailored to the task.


Departments and select agencies should create Digital Corps.

We propose that departments and select agencies should create Digital Corps that would recruit, train, and educate personnel; place people in and remove them from digital workforce billets; manage digital careers; and set standards for digital workforce qualifications. Departments and select agencies would create billets for members of these Digital Corps and provide guidance to members about the work they perform for the agencies.

The Digital Corps model is inspired by the Army’s Medical Corps, which organizes experts with specialized healthcare skills that do not fit into the Army’s traditional talent management framework. Like the Medical Corps, agency-specific Digital Corps should have specialized personnel policies, guidelines for promotion, training resources, and certifications to demonstrate proficiency in new digital areas.

2. Recruit

To fill these Digital Corps and to improve its broader digital workforce, the government needs to improve recruiting and the hiring process, accelerate security clearances, use temporary hiring vehicles such as the Intergovernmental Personnel Act, and build mechanisms for part-time civilian service.3

Establish a civilian National Reserve Digital Corps.

The government should tap into the pool of technologists willing to contribute part of their time to public service by creating a mechanism to hire them. While part-time employees are not a substitute for full-time employees, they can help improve AI education, perform data triage and acquisition, help guide projects and frame digital solutions, build bridges between the public and private sectors, and take on other important tasks.

To eliminate this recruitment gap, the government should establish a civilian National Reserve Digital Corps (NRDC) modeled after the military reserve’s commitments and incentive structure. Members of the NRDC would become civilian Special Government Employees in one of the agency Digital Corps and work at least 38 days each year as advisors, instructors, or developers across the government.

Streamline the hiring process and expand digital talent pipelines.

The government hiring system’s problems are well known: It moves too slowly, struggles to attract experts in a competitive market, and makes it difficult for experts who are young or do not have a degree to be hired, especially at a pay grade matching their level of expertise.

To clear this recruiting bottleneck, the government needs to expand science, technology, engineering, and mathematics (STEM) and AI talent pipelines from universities to government service, streamline the hiring process, and create agency- and military service–specific digital talent recruiting offices either for Digital Corps or agencies.

Standing Digital Corps will oversee government-wide progress and make recommendations to expand and improve digital talent hiring and pipelines.


3. Build

The government will not be able to recruit its way out of its technology workforce deficit. AI and digital talent are simply too scarce in the United States.

Establish a United States Digital Service Academy.

The United States Digital Service Academy (USDSA) would be an accredited, degree-granting university that receives both government and private funding, is managed by a purpose-built independent agency within the federal government, and meets the government’s needs for digital expertise––as determined by an interagency board, assisted by a Federal Advisory Committee composed of private-sector and academic technology leaders.

The USDSA should be modeled off of the five U.S. military service academies but produce trained and educated government civilians for all federal government departments and agencies.


4. Employ

Aligning expectations and experience for the digital workforce requires three changes: opportunity for technologists to spend an entire career focused on the field they are passionate about; well-informed leaders, some of whom are digitally proficient themselves; and access to tools, data sets, and infrastructure.

Establish new digital career fields.

f the military services create career fi elds for software developers and data scientists, this will almost inevitably change what it means to be a soldier, sailor, airman, or marine, much as the introduction of aviation did generations ago.

The government should create civilian occupational series for software development, software engineering, knowledge management, data science, and AI. The military services should create career fi elds in software development, data science, and AI, with both management and specialist tracks.

Expand access to tools, data sets, and infrastructure.

The digital workforce needs access to enterprise-level software capabilities on par with those found in the private sector. Capabilities include software engineering tools, access to software libraries, vetted open-source support, curated data sets, and infrastructure for large-scale collaboration.

All career fields need improved access to the latest open-source libraries and tools.4 Providing AI practitioners rich data sets across the physical and biological sciences, economics, and behavioral studies will let them focus on their areas of expertise rather than scraping obscure sources for data.

In 2020, there were


open computer science jobs



new computer scientists graduates from American universities each year.*

* (last accessed Jan. 11, 2021), See also Oren Etzioni, What Trump’s Executive Order on AI Is Missing: America Needs a Special Visa Program Aimed at Attracting More AI Experts and Specialists, Wired (Feb. 13, 2019),


1 NSCAI staff discussions with the Defense Innovation Board and Defense Digital Service (May 2019).

2 William A. LaPlante, Owning the Technical Baseline, Defense AT&L at 18-20 (July-Aug. 2015),

3 For more information on the Intergovernmental Personnel Act, see Intergovernmental Personnel Act, OPM (last accessed Feb. 1, 2021),

4 For the AI career field in particular, TensorFlow is one of the world’s most popular libraries for training neural networks and other machine learning (ML) algorithms. PyTorch is another open-source library that aids in transforming research prototypes to production-ready machine learning models.