What project AQ8 buys
This project matures and demonstrates data driven decision tools that help develop Situational Understanding (SU) for Commanders. It enhances decision-making and accurately assesses and integrates cross-warfighting functional area impacts with all the domains in Multi-Domain Operations (MDO), and thereby enhances mission effectiveness by improving decision cycles. This project matures and integrates methods to optimize the Army's Command and Control (C2) services and data architecture to strengthen data-driven decisions. Work in this project complements Program Element (PE) 0602146A (Network C3I Technology) / Project AQ7 (High Tempo Data Driven Decision Tools Technology). Work in this project is performed by the Command, Control, Computers, Communications, Cyber, Intelligence, Surveillance, and Reconnaissance (C5ISR) Center, Artificial Intelligence Integration Center (AI2C), and the Engineer Research and Development Center (ERDC).
Project AQ8 funding, FY2025–FY2031
Prior years are actuals, the budget year is the request, and the outyears are the FYDP plan. Estimate types are colored and never summed into one figure. Projects carry the full five-year plan; the activities inside them stop at the budget year.
| Fiscal Year | Estimate Type | Amount ($M) |
|---|---|---|
| FY2025 | Actual | 3.8 |
| FY2026 | Enacted | 18.2 |
| FY2027 | Request | 6.5 |
| FY2028 | Outyear | 8.7 |
| FY2029 | Outyear | 9.2 |
| FY2030 | Outyear | 10.3 |
| FY2031 | Outyear | 11.4 |
6 accomplishments / planned programs
The R-2A exhibit — the only level of the budget that describes work that has not happened yet. Activities carry the prior, current and budget year only, no five-year plan. Coverage is partial across the corpus, so count activities, never total them.
FY2027 planned work Will establish a modern software environment to assess and mature emerging command and control (C2) capabilities such as containerized microservices; mature core components that enable initial functionality of the environment, such as a common data layer; and demonstrate the performance of these emerging C2 capabilities and their readiness for integration into a full-stack implementation.
FY2026 to FY2027 change This is not a new start. FY 2027 funding increase reflects the consolidation of other ongoing efforts within this project from Unified Data Reference Architecture (UDRA) and Next Generation Battle Systems Architecture and Infrastructure.
FY2027 planned work Will mature and demonstrate AI-enabled common operating picture through enhancements that surface machine learning/artificial intelligence (ML/AI) insights from the Sustainment, Intelligence, Fires, Protection, Movement and Maneuver, and Information Advantage warfighting functions. Develop and demonstrate AI/ML models and tools to validate a distributed architecture for natural language processing; operationalize the use AI/ML modeling techniques to validate autonomous data fusion to support command post efforts at echelon, inform risk and support the commanders decision making process in contested and non-contested environments.
FY2026 to FY2027 change This is not a new start effort. Funding restructured from Program Element (PE) 0603040A (Artificial Intelligence and Machine Learning Advanced Technologies) / Project DA7 (AI-Enabled Command and Coordination Adv Tech) to consolidate data driven decision tools and related activities into one project.
FY2025 accomplishments Integrate Development, Security, and Operations (DevSecOps) technologies onto mission command and intel platforms, such as NGC2, coexisting with Innovation requirements efforts; mature DEVSECOPS processes to identify application vulnerabilities and deploy software patches; develop adaptive threat order of battle, optimize strategies using digitized plans, and prioritization with real time battle damage assessment.
FY2026 to FY2027 change Funding decrease reflects realignment to Command and Control Agile Software (C2AS) Adv Tech within this project to continue the transformation of data reference architectures to maximize modular reuse.
FY2026 plans — current year Will mature Software and Data reference architectures, reference implementations, design patterns, and frameworks for implementing digital platforms (design and runtime), data / AI solutions, and other common components; mature solutions development and maximize modular reuse (by abstracting common architectures, design patterns, and frameworks and promoting shared services).
FY2026 to FY2027 change Funding decrease reflects realignment to Command and Control Agile Software (C2AS) Adv Tech within this project to continue the transformation of software delivery and optimization of common services.
FY2026 plans — current year Will mature and develop Innovative Requirements techniques and Development, Security, and Operations (DevSecOps) technologies onto existing mission command and intel platforms; mature and develop a scalable, modular software framework that incorporates application, data, and platform layers to "plug-and-play" applications using modern software development practices; demonstrate initial functionalities, such as establishment and visualization of dynamic and real-time common operations picture, common intel picture, and common logistics picture, support for coordination and communication of offensive and defensive fires, and tools to enable commanders to communicate and collaborate in real…
FY2026 to FY2027 change Funding decrease reflects the strategic reallocation of resources to support evolving priorities and objectives.
FY2026 plans — current year Will provide a library of models, threats and integrated mission threads and relevant hardware footprints to support test scaling; mature and demonstrate an automated approach to create mission threads that reduce setup time and allow for a more dynamic implementation of continuous learning demands; optimize and validate the evolving threat foundation that enables the Army Science and Technology community to conduct demonstrations with real assets while bringing in virtualized future systems and threat profiles.