Artificial Intelligence Test, Evaluation, Verification, and Validation (TEVV) Capability Request for Information (RFI)

Request for Information (RFI)

This RFI is issued by the Defense Intelligence Agency (DIA) for planning purposes only. It is not a solicitation for proposals or quotes. The DIA is seeking information to understand industry capabilities and best practices for developing, deploying, and operating Artificial Intelligence (AI) and AI-Enabled Capabilities (AIEC) Test, Evaluation, Verification, and Validation (TEVV) activities. The goal is to establish a mature, scalable, and sustainable AI TEVV capability within the Defense Intelligence Enterprise (DIE) to accelerate AI adoption and ensure trustworthiness.

• Nature of Request: This is an RFI, not a solicitation. Responses will not form a binding contract, and costs associated with responding will not be reimbursed.
• Response Deadline: Responses are due no later than 1700, 6 February 2026.
• Questions Deadline: Questions for clarification must be submitted by 1200, 23 January 2026, to ST_Proposal_INBOX@dodiis.mil.
• Submission Instructions: Unclassified responses should be submitted via email to ST_Proposal_INBOX@dodiis.mil with the subject "Artificial Intelligence TEVV RFI." Specific instructions are provided for CUI/FOUO and classified responses.
• Use of Information: Submitted information will be used solely for acquisition planning, capability assessment, and strategic roadmap development. It will not be used for intelligence collection or analysis.

The RFI includes detailed questions across several categories:

• Organization Experience: Facility clearance, AI/TEVV expertise, experience with the Defense Intelligence Agency (DIA) and Department of War (DoW)/Intelligence Community (IC), partnerships, certifications, and lessons learned.

• DIA's Mission: Understanding of DIA's mission and operational environment, and how it informs an AI TEVV approach for intelligence applications.

• Frameworks, Methodologies, and Best Practices: Recommended frameworks for AI TEVV implementation, best practices for testing environments, structuring TEVV activities across the AI lifecycle, organizational models, and integration with existing QA processes.

• TEVV Metrics: Recommended metrics for assessing AI system performance, reliability, safety, fairness, robustness, and security, and how these metrics differ across AI application types.

• TEVV Automation and Continuous Monitoring: Approaches to automated monitoring, test case generation, and integration of TEVV into AI development pipelines.

• Collaboration and Interoperability: Leveraging existing initiatives, ensuring interoperability, managing validation responsibilities across multiple organizations, and governance structures.

• Advanced TEVV Capabilities: Red-teaming, adversarial testing, research on emerging approaches, and TEVV for generative AI and other advanced paradigms.

• Implementation and Lessons Learned: Workforce skills, resource requirements, timelines, critical success factors, unanticipated challenges, and lessons learned from previous AI TEVV implementations.

• Respondents are encouraged to avoid sensitive, proprietary, or classified information. If necessary, clear marking instructions are provided.

• The Government reserves the right to select some, none, or all submissions for further information.

Questions & Answers / Clarifications

This document is a template for a Questions and Answers / Comment Matrix, intended to facilitate communication and clarification between potential bidders and the government regarding an opportunity. It appears to be an empty template, as no specific questions or responses are provided within the extracted text.

• The document is a template and does not contain specific questions or answers at this time.

• As this is a template, it does not currently impact the solicitation. It is intended to be populated with vendor questions and government responses to provide further clarification on the opportunity.