In a response to a question from FedScoop, Arati Prabhakar — who leads OSTP and serves as a science adviser to the president — said that funding for the national labs and other institutions involved with AI issues is an area of continued concern. Those comments come after a May report from her office focused on how aging facilities could threaten U.S. goals on emerging technology, including AI. 

“When you think ‘AI,’ you think about a lot of compute,” Prabhakar said. “Many of these applications live at the intersection of AI, information technology, and the real world….

To do this work well is going to require all the marvels of AI and it’s going to continue to require the laboratory research that’s been the foundation of so many of these different disciplines.” 

She continued: “The erosion of our facilities for federal R&D organizations, and for our national labs — which are federally funded — has been a longstanding challenge and one that we continue to be concerned about.”

In the May report, an OSTP subcommittee found that poor R&D infrastructure is hindering agencies’ ability to meet current mission objectives. The subcommittee called for an interagency working group for the exchange of information and a federal agency effort to revitalize infrastructure through evaluations and investments. 

The subcommittee said at the time that the U.S. does not have a “seat at the table” for setting international standards for R&D infrastructure, pointing to the appropriations process as standing in the way of allowing agencies to allocate funds in advance or excess of the allotment process. 

Prabhakar’s comments came in advance of a conference at Johns Hopkins Bloomberg Center in Washington, D.C., focused on potential applications for AI and the federal government. The event follows the Biden administration’s October executive order on artificial intelligence and as officials race to beef up the country’s capabilities with the new technology. It’s meant to raise awareness for a range of AI applications, including novel medicines, improved electrical grid technologies, and weather forecasting. 

“None of these aspirations can be accomplished by industry alone. Many of them require deep research that’s well beyond the reach of corporate product development,” Prabhakar said during the call. “Some require training AI models on data from more than one company. And every one of them requires the deliberate focus to deliver on a public mission, which is different from a market opportunity.” 

The White House seemed to bolster its AI vision applications Wednesday with the introduction of a new AI.gov section focused on “AI aspirations.”  

Madison Alder contributed to this article.

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Mangala Kuppa, who took over as DOL’s chief AI officer this week after previously serving as its deputy CAIO, believes the agency has even more to be confident about when it comes to its work on the technology, possessing a “leg up” on scaling AI quickly.

In an interview with FedScoop, Kuppa pointed to DOL’s previous efforts to modernize internal operations and customer-facing services as part of the department’s journey to implement emerging technologies like AI. Having foundational building blocks and existing infrastructure, along with existing AI applications, has made it “easier” for the agency to scale up, she said. 

“It’s not a ‘big bang’ approach,” said Kuppa, who also serves as DOL’s chief technology officer. “Another aspect that we take very seriously in modernizing is [to] take this opportunity to not just update the technology, but also take this opportunity to re-engineer the business process to help the public.” 

Kuppa pointed to an internal shared services initiative that designated the agency’s Office of the Chief Information Officer to be a “shared services provider for all Departmental IT services.”  That process, Kuppa said, has allowed the department to keep an inventory of all systems and technologies and understand where the legacy systems or opportunities for improvement might exist.

“Using that methodology, we’ve been looking at all high-risk systems, because maybe the technology is very legacy and outdated,” Kuppa said. “We’ve been using that methodology to start those modernization initiatives.”

By considering the age of the technology, the operations burden, security vulnerabilities, regulation compliance and other parameters, DOL came up with a methodology that scores each mission system to determine if it is a candidate for modernization. The agency then looks at the scores on a consistent basis and revises based on new information that becomes available.

These systems can be major: the DOL’s Employment and Training Administration, for example, which provides labor certifications when a company files for hiring an immigrant workforce, was scored for modernization.

“Being an immigrant, I wasn’t aware DOL had a hand in my immigration journey there,” Kuppa said. 

The Technology Modernization Fund has played an “instrumental” role in the department “finding the resources to modernize,” Kuppa said.

She gave the example of using TMF funds to expedite temporary visa applications, which is expected to save 45 days of cycle time for processing labor certification applications.

According to a case study on the TMF site, that project contributed to $1.9 million in annual cost savings, and a key part of the innovation allowed the application forms to auto-populate with the previous year’s information.

“Usually all immigrants eventually start filing for permanent visa applications,” Kuppa said. “Again, you have to repeat the process of labor certification, and so we had two different systems not communicating with each other.”

For Kuppa, modernization is ultimately an exercise in reimagining where new technologies can ultimately be most helpful.

“We have great partnership, we work very closely with our programs and then we have these dialogues every day, in terms of the system’s development lifecycle,” she said. “And that’s how we approach modernization.”

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In an interview with FedScoop, Charles Worthington, the VA’s CAIO and CTO, said the agency is engaged in targeted hiring for AI experts while also sustaining its existing modernization efforts. “I wish we could do more,” he said.

While Worthington wrestles with the proposed fiscal year 2025 funding reductions, the VA’s Office of Information and Technology also finds itself in the legislative crosshairs over modernization system upgrades, a supposed lack of AI disclosures and inadequate tech contractor sanctions and ongoing scrutiny over its electronic health record modernization initiative with Oracle Cerner. 

Worthington spoke to FedScoop about the VA’s embrace of AI, the status of its modernization push, how it is handling budget uncertainty and more.

Editor’s note: The transcript has been edited for clarity and length. 

FedScoop: I know that you’ve started your role as the chief AI officer at the Department of Veterans Affairs. And I wanted to circle back on some stuff that we’ve seen the VA engaged with this past year. The Office of Information and Technology has appeared before Congress, where legislators have voiced their concerns for AI disclosures, inadequate contractor sanctions, budgetary pitfalls in the fiscal year 2025 budget for VA OIT and the supply chain system upgrade. What is your response to them?

Charles Worthington: I think AI represents a really big opportunity for the VA and for every agency, because it really changes what our computing systems are going to be capable of. So I think we’re all going to have to work through what that means for our existing systems over the coming years, but I think really there’s hardly any part of VA’s software infrastructure that’s going to be untouched by this change in how computer systems work and what they’re capable of. So I think it’s obviously gonna be a big focus for us and for Congress over the next couple of years. 

FS: I want to take a step back and focus on the foundational infrastructure challenges that the VA has been facing. Do you attribute that to the emerging technologies’ need for more advanced computing power? What does that look like?

CW: I think overall, VA’s technical infrastructure is actually on a pretty good footing. We’ve spent a lot of time in the past 10 years with the migration to the cloud and with really leaning into using a lot of leading commercial products in the software-as-a-service model where that makes sense. So, by and large, I think we’ve done a good job of bringing our systems up to standard. I think it’s always a challenge in the VA and in government to balance the priorities of modernization and taking advantage of new capabilities with the priorities of running everything that you already have.

One of the unique challenges of this moment in time is that almost every aspect of the VA’s operations depends on technology in some way. There’s just a lot of stuff to maintain; I think we have nearly a thousand systems in operations. And then obviously, with something like AI, there’s a lot of new ideas about how we could do even more [to] use technology and even more ways to further our mission. 

FS: In light of these voiced concerns from legislators, as you progress into your role of chief AI officer, how do you anticipate the agency will be able to use emerging technologies like AI to its fullest extent?

CW: I think there’s really two priorities that we have with AI right now. One is, this represents an enormous opportunity to deliver services more effectively and provide great technology services to the VA staff, because these systems are so powerful and can do so many new things. One priority is to take advantage of these technologies, really to make sure that our operations are running as effectively as possible. 

On the other hand, I think this is such a new technology category that a lot of the existing processes we have around technology governance in government don’t apply in exactly the same ways to artificial intelligence. So in a lot of ways, there are novel concerns that AI brings. … With an AI system that is, instead, taking those inputs and then generating a best guess or generating some piece of content, the way that we need to make sure that those systems are working effectively, those are still being developed. At the same time, as we’re trying to take advantage of these new capabilities, we’re also trying to build a framework that will allow us to safely use and deploy these solutions to make sure that we’re upholding the trust that veterans put in us to manage their data securely. 

FS: In what ways is the agency prioritizing AI requirements, especially from the artificial intelligence executive order that we saw last October, and maintaining a competitive edge with the knowledge that the fiscal year 2025 budget has seen a significant clawback of funds?

CW: We are investing a lot in standing up, I would say, the AI operations and governance. We have four main priorities that we’re focused on right now. One is setting up that policy framework and the governance framework for how we’re going to manage these. We have already convened our first AI governance council meeting — we’ve actually had two of them — where we’re starting to discuss how the agency is going to approach managing our inventory of AI use cases and the policies that we’ll use. 

The second priority is really focused on our workforce. We need to make sure that our VA staff have the knowledge and the skills they need to be able to use these solutions effectively and understand what they’re capable of and also their limitations. We need to be able to bring in the right sort of talent to be able to buy and build these sorts of solutions. 

Third, we’re working on our infrastructure [to] make sure that we have the technical infrastructure in place for VA to actually either build or, in some cases, just buy and run AI solutions. 

Then, finally, we have a set of high-priority use cases that we’re really leaning into. This was one of the things that was specifically called out to the VA in the executive order, which was basically to run a couple of pilots — we call them tech sprints — on AI.

FS: I would definitely love to hear some insights from you personally about some challenges you’re anticipating with artificial intelligence, especially as you’ve referenced that the VA has already been using AI.

CW: I think one of the challenges right now is that most of the AI use cases are built in a very separate way from the rest of our computing systems. So if you take a predictive model, it maybe takes a set of inputs and then generates a prediction, which is typically a number. But how do you actually integrate that prediction into a system that somebody’s already using is a challenge that we see, I think, with most of these systems.

In my opinion, integrating AI with more traditional types of software is going to be one of the biggest challenges of the next 10 years. VA has got over a thousand systems and to really leverage these tools effectively, you’d ideally like to see these capabilities integrated tightly with those systems so that it’s all kind of one workflow, and it appears naturally as a way that can assist the person with the task they’re trying to achieve, as opposed to something that’s in a different window that they’ve got to flip back and forth between. 

I feel like right now, we’re in that awkward stage where most of these tools are a different window … where there’s a lot of flipping back and forth between tools and figuring out how best to integrate those AI tools with the more traditional systems. I think that’s just kind of a relatively unfigured-out problem. Especially, if you think of a place like VA, where we have a lot of legacy systems, things that have been built over the past number of decades, oftentimes updating those is not the easiest thing. So I think it really speaks to the importance of modernizing our software systems to make them easier to change, more flexible, so that we can add things like AI or just other enhancements.

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In a Thursday posting in the Federal Register, the Office of Science and Technology Policy said it is seeking information for the development of the Federal Evidence Agenda on Disability Equity. OSTP’s questions to the public pertain to informing data collection and public access, describing disparities as well as privacy, security and civil rights. 

Specific questions include the type of framework for “defining and measuring disability” or other considerations of which the Disability Data Interagency Working Group (DDIWG) within OSTP’s National Science and Technology Council Subcommittee on Equitable Data (SED) should be aware. The office also seeks to understand “what disparities faced by individuals with disabilities are not well-understood through existing federal statistics and data collection,” according to the posting. 

The notice also states: “Though previous work by the SED has identified how privacy, confidentiality and civil rights practices apply to other marginalized groups, OSTP seeks input on privacy, confidentiality and civil rights considerations that are unique to the disability community and/or are experienced differently by individuals with disabilities.”

OSTP’s RFI follows the Biden administration’s 2023 executive order on advancing racial equity and support for underserved communities through the federal government, which directed SED to “coordinate implementation of recommendations” from the Equitable Data Working Group. 

OSTP did not immediately respond to a request for comment.

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During the Workday Federal Forum, GSA Administrator Robin Carnahan teased that the agency is working on an open-source tool called “Gov CX Analyzer,” which uses artificial intelligence features to see how individuals are interacting with government websites.

“This is a way to go from a few thousand people filling out a survey, to actually knowing and seeing how people are interacting with your site,” Carnahan said. “It just completely unlocks the potential to know how you can better serve your customers, where the friction points are and how you can improve it.” 

Carnahan pointed to the U.S. Web Design System — an open-source tool that is free for agencies to use — as a shared system and tool that “makes a huge difference.” 

Similar efforts include an announcement from the Office of Management and Budget last year that detailed an analytics tool to track customer experience performance across agency sites. OMB reported leveraging the GSA’s site scanner program to use performance indicators in the tracking of agencies’ site developments.

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The principles focus on values like ensuring responsible use of workers’ data, supporting workers who might need to be upskilled because of artificial intelligence, and committing to using transparency when deploying AI. The principles appear to be voluntary and follow another set of non-binding commitments focused on artificial intelligence announced last July that included pledges from companies like OpenAI and Anthropic.

“Workers must be at the heart of our nation’s approach to AI technology development and use,” acting Labor Secretary Julie Su said in a statement. “These principles announced [Thursday] reflect the Biden-Harris administration’s belief that, in addition to complying with existing laws, artificial intelligence should also enhance the quality of work and life for all workers. As employers and developers implement these principles, we are determined to create a future where technology serves the needs of people above all.”

Microsoft and Indeed, the online job repository platform, have agreed to these principles, according to a press release shared by the White House. The administration seemed to be courting further support for the principles in a post, noting that it “welcomes additional commitments from other technology companies.” 

Notably, the White House recently hosted an event with senior officials from the Labor Department focused on the technology’s impact on workers, according to an IBM executive’s post on LinkedIn.

Neither the White House nor the Department of Labor responded to requests for comment. 

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TMF investments to the Departments of Education, Commerce and State total just under $50 million. 

The State Department received two investments: $18.2 million to increase diplomacy through generative AI and $13.1 million to transition its identity and access management systems to a zero-trust architecture model.

The AI investment is intended to “empower its widely dispersed team members to work more efficiently and improve access to enhanced information resources,” including diplomatic cables, media summaries and reports. On the zero trust investment, State said it is planning to expedite the creation of a comprehensive consolidated identity trust system, as well as centralizing workflows for the onboarding and offboarding process.

Clare Martorana, the federal CIO and TMF board chair, said in a statement that she’s “thrilled to see our catalytic funding stream powering the use of AI and improving security at the State Department.” 

State recently announced a chatbot for internal uses and revised its public AI use case inventory to remove nine items from the agency website. Additionally, the agency has started to encourage its workforce to use generative AI tools like ChatGPT. 

The Department of Education, meanwhile, is using a $5.9 million allocation to assist the Federal Student Aid office on a new StudentAid.gov feature called “My Activity” to centralize documents and data to track activities and status updates. The FSA is anticipating “a reduction in wait times and the need for customer care inquiries,” per the GSA release. 

Education also recently announced an RFI for cloud computing capabilities for the FSA office, a follow-on contract for its Next Generation Cloud. 

Finally, the Department of Commerce’s National Oceanic and Atmospheric Administration will put its $12 million TMF investment toward modernizing weather.gov through a redesign to “enhance information accessibility” and “establish a sustainable, mobile-first infrastructure.” NOAA reported plans to integrate translation capabilities for underserved communities’ benefit. 

The release noted that NOAA’s associated application programming interface “faces challenges, causing disruptions in accessing dependable weather information for the American public.”

Martorana said she was “equally excited about the TMF’s two other critical investments — with students getting more modern access to manage their education journeys and the public gaining access to life-saving weather information in an accessible manner for all.”

These investments come after a second appropriations package to fund the government for fiscal year 2024 threatened to claw back $100 million from the TMF. Both the GSA and the Office of Management and Budget have faced challenges in convincing lawmakers to meet funding levels proposed by the Biden administration.

Martorana recently called on Congress to fund the TMF, pointing to the funding vehicle as a way to improve service delivery for the public across the government.

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During a Tuesday hearing regarding the VA OIT’s budget justification, Chairman Matt Rosendale, R-Mont., and ranking member Sheila Cherfilus-McCormick, D-Fla., both questioned how the budget would affect operations. 

Kurt DelBene, the VA’s CIO and assistant secretary for IT, acknowledged that “it is a challenging budget for us,” forcing the agency to “be very focused on where we invest.” Modernization funds, he said, will have to be “judiciously” allocated “against the highest-priority projects” that the agency has. 

DelBene said that the agency’s original budget submission to the Biden administration did not reflect the same reduction to development efforts specifically for technology as the FY25 document ultimately did. 

The FY25 budget in brief, released by the VA, listed the following reductions across OIT:

• Development allocations at $960,000, a 99.2% reduction, or approximately a $125 million decrease. 
• Enhancement funds at $45 million, an 87.7% decrease, previously standing around $363 million.
• Modernization funds for FY25 are $267 million, a 66.5% cut, previously having allocated funds just under $800 million. 

As a result of the clawed-back funds for VA OIT, DelBene said that the agency is going to have to have a “very strict prioritization of the work that we do.” 

“I do think that we will be able to address the critical projects that we need to address in FY25 with this budget,” he added. “I think we’re making some trade-offs, which will not work well if we sustain those over multiple years.”

In response to a question from Cherfilus-McCormick, DeBene pointed to the need for increases in future years “because you can’t just continue to be at a lower level” for these funding allocations. 

DelBene also noted that the department is looking at a decreased budget for replacing technology, such as PCs, which he estimated to cost between $15-$20 million. 

“We will replace PCs less frequently as a result,” DelBene said. “That’s my point, is that we can’t continue to do that every year. But I feel especially with some of the funding we’ve got recently and the fact the fleet has been updated, we can do that for one year and make that through. But we’re going to have to be diligent about it in future years.”

DelBene said his goal is to not allow veteran care to be hampered as a result of budgetary pitfalls.

“There are difficult choices that have to be made across the entire administration so I respect the challenges of making those cuts,” DelBene said.

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“Frankly, there aren’t enough places for agencies to go across government when they have technical questions or need technical help, so we get a huge array of requests,” USDS Administrator Mina Hsiang said in an interview with FedScoop.  

Those requests, many of which are detailed in the 2024 impact report USDS released Thursday, can’t all be addressed. Hsiang said USDS works to fulfill “over a quarter” of the agency requests for partnership, with consultation but not full engagement provided on approximately 10% of those asks. 

“We do a lot of work to contemplate the size of the population impacted, the vulnerability of the population impacted, the change it will have on the service and how critical the service is for people’s livelihood,” she said.

In its report, USDS outlined progress on 10 different projects across agencies, covering topics including digital service accessibility, building veteran trust, federal benefits for families and more. 

A closer look at USDS projects

In its partnership with the Social Security Administration, USDS worked with the agency to “observe customers” and learn how the public engaged with SSA’s website. According to the report, the project would save an estimated $285 million over five years for infrastructure expenses. 

The partnership with SSA has “created momentum to improve service delivery” through transforming the agency’s static homepage, the report noted, replacing “complicated” policy language with a conversational eligibility screener and building development infrastructure that involves a content management system and more.

The USDS is currently working with the Department of Veterans Affairs’ Office of the Chief Technology Officer to develop software intended to improve the lives of veterans. In teaming with the agency on VA.gov, USDS aimed to build veterans’ trust in the VA. Per the report, veterans’ trust in the VA climbed from 70.4% in FY18 — the year of VA.gov’s relaunch — to 79.3% in FY23.

“The Veteran Experience Office does a very comprehensive work of engaging veterans and building an array of metrics together,” Hsiang said.

The impact report also touted USDS’s partnership with the Department of Health and Human Services to help modernize and implement services that support an interagency Life Experience Research Team, aiming for “simpler, more accessible and equitable” digital experiences. Specifically, the organization conducted research with a nationwide group of participants, documenting their experiences throughout pregnancy and childbirth along with any relevant interactions with the federal government. 

Working with an HHS Life Experience Research Team that included  representatives from the General Services Administration, the Department of Labor, the Department of Housing and Urban Development and others, USDS piloted three digital programs to support families, including a text message service called Notify.gov that allows government partners to send texts about benefits and support programs to the public.

“This is one of those places where we can partner very closely with an agency that’s building out a shared capability for more folks and give them direct feedback,” Hsiang said. “The team had a very good experience with it.”

Though not listed in the impact report, the USDS also worked “extremely closely” with the IRS on the implementation of its Direct File pilot program. Hsiang said the partnership was not included in the report due to a timing issue, but noted that USDS assisted in technical expertise, user research, product management and more. Direct File was utilized by over 140,000 taxpayers in its inaugural run, according to the IRS. 

“This pilot is only with 12 states, but obviously there’s real opportunities for growth there because building out that capability so that folks in every state can have this option will be important,” Hsiang said. “The tax code is huge and incredibly complex, so there were almost 20 million people who were eligible for this pilot, but it will be important to expand that capability to encompass more individuals.”

A busy year followed by more to come from USDS

For Hsiang, who has led USDS since September 2021, the release of the impact report represents what she views as “a year of launching things.”

“There’s a lot of programs here that are a demonstration of incredible value in themselves, but also a proof of concept of a new model working,” Hsiang said. 

USDS is investing in hiring both internally and with agency partnerships, Hsiang said, in an effort to capitalize on momentum to build long-term capacity within agencies. She confirmed that the USDS is working to support agencies in hiring more talent, including as part of efforts called out in the White House’s artificial intelligence executive order.

“I think there’s a lot of interest, but the talent moves quickly, gets hired quickly, looks for competitive salaries and opportunities,” Hsiang said. “That will definitely be a challenge, but one we’re excited to take on.”

Hsiang said her hope for this report is a “clear illustration” of what government talent is able to accomplish, and stressed the importance of USDS’s investment in technology-centered work.

“I think the report starts to give a real detailed window into the range of different types of work that we do and the short- and long-term impacts that it can have,” Hsiang said. “One of the things that we hear across government regularly is that technology ends up slowing people down instead of speeding them up, if it’s not implemented right. That is not what anyone intends and that’s not what we’re investing for.”

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While federal agencies have lagged commercial industry in recognizing AI’s potential impacts and adapting accordingly, the U.S. government is now rushing to catch up. On March 28, the White House Office of Management and Budget released its new AI governance memo as a follow-up to the October 2023 White House Executive Order on the Safe, Secure, and Trustworthy Use of Artificial Intelligence, and federal agencies have completed all required actions to date under the Executive Order on schedule.

As required by the executive order, all federal agencies must now designate a Chief AI Officer (CAIO) to coordinate their agency’s use of AI, promote AI innovation in their agency, and manage risks from their agency’s use of AI. As a consequence, the government is looking for 400 CAIOs and many federal departments and agencies have already named one.

The creation of CAIO positions is a significant step toward an AI-enabled federal government. However, it presents challenges akin to those faced in the private sector. To navigate these challenges successfully, CAIOs should take five immediate actions to set the stage for success:

Lead the Mission: CAIOs must articulate a clear vision for AI adoption within their agencies, ensuring alignment and serving as the focal point for implementing AI priorities. The Chief AI Officer should report directly to the department or agency head to demonstrate that they have their full-throated support.

Balance Innovation and Risk: Many government functions are considered no-fail missions—protecting the nation, providing uninterrupted financial and medical benefits, securing domestic and international travel, building weapon systems, and serving as the nation’s eyes and ears through intelligence collection and analysis. Even seemingly small error rates may be intolerable. Yet with AI, risk aversion offers a path to stagnation and obsolescence. CAIOs should fight to strike a balance between each agency’s legitimate concerns about risks, and the imperative to accelerate AI adoption and integration.

Quick Wins and Strategy: CAIOs should identify low-hanging fruit that, with focused senior-level attention and a burst of resources, can deliver demonstrable outcomes that are clearly AI-driven. This creates a virtuous cycle of success that opens the aperture for the more difficult and ambitious work to come. AI pilots can be chosen thoughtfully to demonstrate hypotheses that can then be affirmed in each department’s AI strategy. These quick wins can build momentum for broader AI strategy implementation.

Budgeting and Procurement: The budgets that CAIOs are working with now were likely built in early 2022 before large language models or generative AI were widely available. CAIOs should work with agency chief financial officers and department comptrollers to identify current-year funds for reprogramming. At the same time, they need to shape future year budgets in ways that reflect the required infusion of resources in support of the entire AI lifecycle.

Yet even when funds are identified, procurement processes often move slower than the pace of technology — a product on the cutting edge today may be on the path to obsolescence tomorrow. CAIOs should work with acquisition and contracting officials to take full advantage of extant authorities while seeking new and more flexible authorities to accelerate AI procurement.

Talent Acquisition: The scarcity of AI talent necessitates creative approaches to recruitment and retention within the public sector. CAIOs should push to hire AI experts directly, but to move faster they should also hire outside AI experts for temporary assignments through pathways such as fellowships from corporations, think tanks, and academia, or in excepted service or special government employee roles. CAIOs can pursue a strategy of establishing a centralized AI talent hub that the rest of the department or agency can access, or of placing talent in key directorates and offices that are leveraging AI. A blend of different human capital solutions will help accelerate AI adoption across the government.

These strategies are not only aimed at integrating AI into federal operations but also at leveraging its potential to enhance public service delivery. The CAIO’s role is pivotal in this process, requiring a blend of visionary leadership, strategic planning, and operational acumen.

The experiences of the Defense Department’s Joint AI Center and Chief Digital and AI Office and the Department of Homeland Security’s AI Task Force exemplify the multifaceted opportunities and challenges AI presents. These initiatives highlighted the necessity for a centralized strategy to provide direction, coupled with the flexibility to foster innovation and experimentation within a decentralized framework. Absent the proper balance between centralization and decentralization, one of two things will happen: AI will never scale beyond pilot projects — overly decentralized — or the end users’ needs will be marginalized to the point of failure — overly centralized. The balancing act between rapid technological adoption and the careful management of associated risks underscores the complex landscape that CAIOs navigate.

The decision to institutionalize the role of CAIOs demonstrates a clear acknowledgment of AI’s strategic significance. This action signifies a deeper commitment to keeping the United States at the forefront of technological innovation, emphasizing the use of AI to improve public service delivery, enhance operational efficiency, and safeguard national interests. As we navigate this still-uncharted territory, leadership, innovation, and responsible governance will be essential in realizing the full promise of AI within the federal realm. CAIOs will play an indispensable role in shaping the government’s AI-enhanced future.

Joel Meyer served as the Deputy Assistant Secretary of Homeland Security for Strategic Initiatives in the Biden Administration, where he drove the creation of DHS’s Artificial Intelligence Task Force and the Third Quadrennial Homeland Security Review. He has led public sector businesses at three artificial intelligence technology startups, including currently serving as President of Public Sector at Domino Data Lab, provider of the leading enterprise AI platform trusted by over 20% of the Fortune 100 and major government agencies.

Lieutenant General John (Jack) N.T. Shanahan, United States Air Force, Retired, retired in 2020 after a 36-year military career. Jack served in a variety of operational and staff positions in various fields including flying, intelligence, policy, and command and control. As the first Director of the Algorithmic Warfare Cross-Functional Team (Project Maven), Jack established and led DoD’s pathfinder AI fielding program charged with bringing AI capabilities to intelligence collection and analysis. In his final assignment, he served as the inaugural Director of the U.S. Department of Defense Joint Artificial Intelligence Center.

Both authors serve as Commissioners on the Atlantic Council’s Commission on Software-Defined Warfare.

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