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Federal agencies should treat trusted access as a risk-managed system—not as a choice between buying an AI security product and requiring one authentication method everywhere. They need to establish who or what is requesting access, decide what that requester may do, evaluate the request in context, and govern any AI used to make identity decisions. NIST’s final digital identity guidelines and zero-trust implementation guidance provide distinct, complementary foundations for doing that.
What does trusted access mean for a federal agency?
Trusted access is the set of processes and controls an agency uses to let the right people reach the right resources, while limiting misuse and accounting for the risks created by the access system itself. It is broader than logging in: proving an identity, authenticating a returning user, authorizing an action, and deciding whether to trust an assertion from another organization are related but separate decisions.
AI makes this a governance issue as well as a technical one. An AI-enabled system might check identity evidence, compare biometrics, flag suspected fraud, or assist a user. Agencies need to understand how such a component affects both security and legitimate access—and ensure that relying organizations receive information needed to assess its reliability and privacy implications.
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These three layers address different questions. They should be designed to work together, not treated as interchangeable standards or a single product category.
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| Layer | What it addresses | Agency use |
|---|---|---|
| Digital identity | Identity proofing, authentication, and federation of identity assertions to relying services. NIST assigns separate assurance levels for identity proofing (IAL), authentication (AAL), and federation (FAL). | Use NIST SP 800-63-4 to select and manage identity controls for covered online services and user groups. |
| Zero-trust architecture | Access to distributed enterprise resources, informed by identity and other relevant context rather than trust in a network location alone. | Use NIST SP 1800-35 as a practical implementation guide aligned with SP 800-207, not as a single vendor blueprint. |
| AI governance | Oversight of agency AI use, with additional identity-specific transparency and privacy conditions when AI/ML is used in identity systems. | Apply government-wide AI policy where it covers the use case, and meet the more specific NIST conditions for AI/ML used in or relied on for identity processes. |
NIST SP 800-63-4, finalized July 31, 2025, covers federal online services used by the public, business partners, employees, and contractors. It excludes national security systems. Its guidelines address logical access, not the full physical-access process, and do not explicitly cover machine-to-machine authentication, IoT devices, or API access on behalf of subjects. Agencies therefore need other applicable controls for service identities and AI agents; SP 800-63-4 alone does not resolve non-human identity.
How should federal agencies verify identity when AI is involved?
Use AI only within a governed identity process
NIST identifies identity-system uses of AI/ML such as biometric matching, automated validation of evidence or attributes, fraud detection, and user assistance such as chatbots. The guidance does not prohibit these uses. It sets conditions for organizations that use AI/ML in identity systems, including systems they rely on.
NIST SP 800-63-4 says: “All uses of AI/ML SHALL be documented and communicated to organizations that rely on these systems.” Organizations must also provide information about the training methods and datasets, how often the system is updated, and completed testing. They must document privacy risk assessments for personal information and data processed by the system. NIST recommends evaluating these uses with its AI Risk Management Framework.
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Make the decision inspectable by relying parties
An agency relying on an identity provider should be able to understand where AI participates in the process and what evidence supports the system’s use. Documentation and disclosure help the relying agency evaluate the limits of an assertion, assess risks, and assign accountability; they do not by themselves prove a model is accurate or suitable. Agencies should connect testing evidence and update practices to the consequences of an incorrect match, a missed fraud signal, or an error that blocks a legitimate user.
What does zero trust mean for government access?
Zero trust is an architecture and access approach in which decisions are tied to the resource being requested and relevant identity and context, rather than assuming that a request is safe because it originates inside a trusted network. It is not the slogan “never trust anyone,” nor does it prescribe one universal product or configuration.
NIST SP 1800-35, published in June 2025, gives implementation models for secure, authorized access to distributed on-premises and multiple-cloud resources for a hybrid workforce and partners. NIST’s National Cybersecurity Center of Excellence developed the guide with 24 collaborators under cooperative research agreements. It describes 19 example implementations across common use cases. Those counts describe the guide’s development and examples; they are not measured proof that one architecture will be more secure or cost-effective for every agency.
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How should an agency decide what level of identity assurance a service needs?
Start with the risks of the service and the people who use it. NIST’s Digital Identity Risk Management process asks agencies to consider both the harm identity controls can help prevent and harms the identity system itself can introduce. Federal relying parties SHALL apply this risk-management process to all online services.
Assess both sides of identity risk
- Risks to the service: Consider impersonation, account takeover, or a compromised federation assertion, and the impact of unauthorized access or action.
- Risks from the identity system: Consider privacy exposure, fraud-control gaps, and barriers that prevent a legitimate person from enrolling or authenticating.
- Consequences: Weigh possible mission degradation, loss of public trust or reputation, unauthorized information access, financial loss or liability, and impacts to safety or health.
Choose controls against the actual impact
Select the IAL, AAL, and FAL appropriate to the use case rather than maximizing every assurance level by default. Compare candidate methods and providers across these dimensions:
- Assurance and threat resistance: What would impersonation or a compromised assertion enable, and which assurance levels address that risk?
- Privacy and data handling: What personal information is collected, retained, shared, or processed, and what minimization and assessment are needed?
- User access and usability: Can people complete proofing and authentication, including users facing device, accessibility, or process barriers?
- Interoperability and federation: Which identity providers, relying parties, and protocols are involved, and do agency-specific PIV requirements apply?
- Operational resilience and governance: Can the agency evaluate controls over time, exchange fraud and threat information, audit decisions, and identify who is accountable?
- AI transparency and assurance: If AI/ML is involved in identity, are its use, training information, update cadence, testing evidence, and privacy assessment documented and communicated?
For public-service federation, NIST says agencies operating online services SHOULD offer federation as an access option, subject to risk, legal, and regulatory constraints. The guidance maps initial FAL selections to service impact and calls for further analysis in high-impact situations; federation is not a universal requirement for every service.
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What is phishing-resistant authentication, and where does a security key fit?
Phishing-resistant authentication is an authentication approach designed to resist credential theft through phishing. NIST SP 800-63-4 updates the threat models and adds options for phishing-resistant authentication; it also addresses automated attacks against enrollment. A FIDO2-compatible hardware security key is one product category relevant to this discussion, but the guidelines do not endorse a brand or establish that a particular model is approved for agency procurement.
A key addresses an authentication factor, not identity proofing, authorization, federation risk, AI transparency, or the full zero-trust architecture. Its suitability depends on integration with the agency’s services and policy. Federal PIV requirements also extend the general guidelines for issuing and managing PIV cards and derived credentials.
What federal AI policy applies, and what is changing for public services?
Government-wide AI policy
OMB Memorandum M-25-21, dated April 3, 2025, rescinded and replaced M-24-10. It applies to executive departments and agencies, including independent regulatory agencies, and directs agencies to accelerate AI adoption under innovation, governance, and public-trust priorities while protecting privacy, civil rights, and civil liberties. It does not cover AI used as a component of a National Security System. This government-wide policy context is distinct from NIST’s technical identity requirements.
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The White House OMB memorandum index, accessed October 3, 2026, lists M-26-04, “Increasing Public Trust in Artificial Intelligence Through Unbiased AI Principles,” dated December 11, 2025; M-26-05, “Adopting a Risk-based Approach to Software and Hardware Security,” dated January 23, 2026; and M-26-18 on scaling Login.gov for universal sign-on, dated August 31, 2026. The index establishes these titles and dates, not their detailed operational requirements.
America.gov and Login.gov direction
An order signed September 29, 2026 directs GSA to establish America.gov as the single entry point for covered online federal services and integrate Login.gov as the authentication service. It calls for personal-information protection through data minimization, secure authentication, auditable authorization, and lawful disclosure practices.
The order defines covered services using a threshold of more than 100,000 users in a 12-month period for public-facing federal services that can be accessed or applied for online. This is a scope threshold, not a claim about total platform reach. The order excludes IRS tax filing, Department of War services, and Intelligence Community services. Agencies are directed to identify and integrate covered services securely and in a privacy-preserving manner, and an OMB implementation memorandum is due within 90 days. The direction is recent, with implementation still underway as of October 3, 2026; it should not be read as a completed government-wide migration.
Quick Recap
What should an agency do next?
- Map the service and its users. Identify the resources, user groups, identity providers, relying parties, and any relevant PIV obligations.
- Run identity risk management. Assess threats the controls should mitigate alongside privacy, usability, fraud, and resilience risks introduced by the identity system.
- Set separate assurance needs. Determine the service’s IAL, AAL, and FAL needs based on its impact and user context; consider risk-based tailoring and compensating measures.
- Connect identity decisions to resource access. Apply zero-trust principles across the relevant on-premises and cloud resources rather than relying on network location as the trust boundary.
- Govern AI in identity workflows. Document and communicate AI/ML use to relying organizations, provide training and update information and test results, and document privacy risk assessments.
- Plan for excluded cases and new direction. Use other applicable controls for machine identities and AI agents, distinguish national security systems from covered civilian services, and assess whether America.gov direction applies to a service.
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