AI in Federal Policy: Implications for Tribal Nations

Federal policy and directive around artificial intelligence (AI) has shifted considerably in recent years. In 2023, President Biden issued  EO 14110, Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence, which emphasized safety, equity, worker protections, and privacy in federal AI policy. In January 2025, it was rescinded by EO 14197, Removing Barriers to American Leadership in Artificial Intelligence, which in the name of innovation and global competitiveness, rolled back regulation efforts, prioritizing rapid development and global expansion. Following EO 14197, the White House released Winning the AI Race: America’s AI Action Plan, outlining more than 90 actions to accelerate AI adoption and strengthen U.S. global leadership. The Trump Administration has directed agencies to adopt AI in ways that expand infrastructure, streamline services, and increase interagency data sharing. As a result, AI initiatives are rapidly developing and span key sectors where federal and Tribal governments often work in close partnership. 

For Tribal Nations, these developments bring both opportunities and challenges, especially as agencies with government-to-government responsibilities begin defining their AI strategies. This blog examines these implications by exploring the AI strategies and initiatives of a few key federal departments that engage directly with Tribal Nations: the Departments of the Interior, Justice, Homeland Security, and Health and Human Services.

DOI and Tribal Engagement in AI

The Department of Interior (DOI) is the federal agency primarily responsible for managing the U.S.-Tribal Nations relationship and overseeing policies and governance related to Tribal affairs. The Bureau of Indian Affairs (BIA) acts as its operational arm and on behalf of the DOI and its federal trust responsibility, ensuring policies are implemented with Tribes. The DOI has been exploring AI in its internal operations, and is actively working with the BIA and other Tribal-affiliated agencies to examine the use of AI to enhance operational systems and clear backlogs for Tribal Nations.  

In one instance, the DOI partnered with Syncurrent to create a free, AI-powered searchable database for all 574 federally recognized Tribes. This online repository provides up-to-date information on federal funding opportunities, including grants, loans, and tax credits, from all federal agencies. The initiative aims to help Tribal governments, Native-owned businesses, and entrepreneurs access more funding. This support is especially critical given that, according to a Government Accountability Office (GAO) report last year, much of the funding approved by Congress to assist Tribal governments was likely not reaching them. Another priority for the DOI is exploring how AI can help reduce the BIA’s backlog of more than 48,000 unresolved probate cases on Tribal lands, a longstanding challenge for estate settlement in Tribal communities that has also contributed to housing shortages on reservations.

On one hand, this use of AI demonstrates its potential to improve government operations in ways that directly benefit Tribal communities. On the other, it raises concerns about data sovereignty. For example, applying AI to resolve probate cases could require uploading birth and death certificates or historical family records into a database, prompting questions about data sovereignty and who manages and owns the system, how the data is stored, and with whom it may be shared.

DOJ & DHS: AI in Law Enforcement

The Department of Justice (DOJ) and Department of Homeland Security (DHS) have each reported more than 200 AI use cases, many centered on law enforcement surveillance ranging from facial recognition and predictive analytics to interagency data-sharing platforms. Under the Freedom of Information Act (FOIA), these agencies are required to make public records of each initiative and the technology being used, creating a baseline of transparency about how AI is being deployed in law enforcement. Tribal Nations, however, are not subject to FOIA laws. This means Tribal police departments and agencies are not required to disclose how AI is integrated into their work, including their use of AI-powered equipment or funds provided through DOJ or DHS AI grants.

Many police departments are taking advantage of AI tools as a way to enhance workforce capabilities and lower costs. The majority of Tribal police agencies have fewer than 25 officers, and AI-powered surveillance tools such as body-worn cameras, automated license plate readers, drones and facial recognition technology can help stretch limited surveillance resources. Yet, without standardized reporting requirements, the public and Tribal communities may have limited visibility into how these technologies are used, or its impact on the community. This gap has real implications; on one hand expanded surveillance and interagency data-sharing can improve coordination on public safety threats, but on the other they raise concern about privacy, cultural sovereignty, and the risk of bias in algorithmic systems. 

Some Tribal agencies have proactively created their own AI policies or shared information on use cases, demonstrating pathways toward responsible governance. Establishing clear agreements on data-sharing, strengthening Tribal digital sovereignty and setting standards for accountability could help Tribal communities capture the benefits of AI in policing while mitigating risks. As federal policy continues to expand AI in law enforcement, Tribal Nations face the unique challenge and opportunity of defining their own approaches to transparency and oversight. 

HHS: AI in Health and Human Services

In its 2025 AI strategy, the Department of Health and Human Services (HHS) committed to partnering with state, local, and Tribal governments to ensure safe and equitable AI adoption in health, human services, and public health. Its plan offers guidance on selecting, procuring, and utilizing AI systems to deliver healthcare to Americans. HHS has emphasized tailoring AI to cultural contexts, especially in sensitive areas like benefit eligibility. Its Plan for the Responsible Use of AI in Public Benefits engaged Tribal Nations through consultations and advisory committees, with commitments to support Tribal oversight where resources allow.

Early AI rollouts included Indian Health Service (IHS), which serves 2.8 million American Indians and Alaska Natives and operates 600 facilities, which is beginning to roll out AI-driven system upgrades through an IT and data Modernization Initiative. This initiative was developed with Tribal leaders and the NIH AIM-AHEAD program, which supports Tribal health departments in conducting equity-focused research. These modernizations are meant to streamline data access across healthcare facilities, enhancing the experience of both patients and providers. 

This example of AI shows its potential to improve patient services and continuity of healthcare. However, questions remain around data sovereignty and ownership. The IHS IT Modernization Program states its commitment to working with Tribal communities on these developments and verifies that electronic health records are still managed by the healthcare facilities, but does not state whether these healthcare facilities own the data that is collected, or if there are limits to how data is shared. Strengthening Tribal authority over data and AI systems as they are integrated into Tribal communities will be key to ensuring equitable outcomes and protections for Tribal populations and their data sovereignty. 

Conclusion

Federal agencies are beginning to engage Tribal Nations in shaping AI strategies. While this technology offers opportunities to strengthen government-to-government relations by improving operations, communication, and access across sectors, it also raises unresolved concerns. Questions of digital sovereignty, oversight, ownership, data sharing, and accountability present unique challenges for Tribal communities. To balance innovation with equity, AI policies must respect government-to-government relationships, uphold Tribal sovereignty, and honor the federal trust responsibility as these technologies become more deeply integrated into government systems.