IV&V Process Accelerators through Generative AI Capabilities

Overview

Development stage

In development or acquisitionSource: a) Pre-deployment – The use case is in a development or acquisition status.

High-impact designation

Not high-impactSource: c) Not high-impact

Impact justification

Not reported

Start date

Not reported

Withheld from public reporting

NoSource: a) No

Mission

Topic area

Science

Operational functions

No function tag matched Derived by keyword rules; see methodology

Problem the AI is intended to solve

This project is a collection of utility tools that generated by personnel and early adopters at the NASA IV&V Program who have explored and prototyped generative AI applications that can streamline and enhance Independent Verification & Validation (IV&V) activities. Process accelerator efforts focus on automating common, high-effort tasks such as Technical Issue Memorandum (TIM) / formal IV&V issue generation, automated peer review support of technical issues, milestone review summaries, NASA program risk mapping to open IV&V issues, and automated assurance conclusion statements. Additional concepts include automated generation of value statements, status reports, sensitivity/content classification, Tier 1 security-related queries on NASA programs, and IV&V methods generation. These exploratory activities serve as feasibility studies, demonstrating how generative AI can reduce analyst workload, accelerate analysis and reporting, and provide a foundation for future funded capabilities. Insights gained from these concepts directly inform NASA IV&V’s broader AI strategy, guiding the maturation and adoption of advanced assurance tools.

Expected benefits

Results and positive outcomes from the NASA IV&V Process Accelerator efforts directly inform and strengthen larger, funded AI initiatives. These exploratory activities have demonstrated how generative AI can streamline traditionally resource and labor-intensive tasks. Even when lightly validated using synthetic or open-source data, these proofs of concept activities highlight that routine, high-effort activities can be effectively automated to a practical degree. This includes processing vast quantities of data in a deterministic manner and providing an end user product for human review and additional analysis, where needed. Collectively, these concepts showcase the potential of generative AI to enhance efficiency, reduce analyst workload, and provide a foundation for more advanced AI-driven capabilities in support of NASA's missions.

System outputs

Outputs on these concept development efforts span pre-processed spreadsheets, large generated Word Documents, and outputs driven to other tools for human review and assessment. Outputs inform feasibility of generative AI capabilities and further implementation plans.

Technology

AI classification

Generative AISource: Generative AI: AI that generates new or synthetic content (e.g., images, videos, audio, text, code).

System name(s)

Not reported

Custom-developed code

Not reported

Public source code

Not reported

Sourcing

How it was built

Not reported

Vendor (as reported)

Not reported

Vendors (standardized)

None on the standard list

A vendor is the supplier named by the agency. It does not identify the underlying model or AI technology.

Data and privacy

Involves PII

Not reported

Privacy Impact Assessment

Not reported

Authorization to Operate

Not reported

Demographic features

Not reported

Training and evaluation data

Not reported

Federal Data Catalog

Not reported

Governance

0 of 8 minimum-practice questions answered. A blank answer means the agency reported nothing; it does not mean the practice is absent.

Potential impacts and how they were identified

Not reported