R-2A Activity · President's Budget PB2027

Combined Joint All-Domain Command & Control (CJADC2)

FY2027 Request
$28.6M
▼ 7.1% vs FY2026
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This activity requests $28.6M in FY2027, 30% of project 625315, down 7.1% on FY2026. The R-2A exhibit describes it across FY2026–FY2027, including what the FY2027 money is planned to buy.

FY2027 Request
$28.6M
▼ 7.1% vs FY2026
FY2026 Enacted
$30.7M
▲ 40% vs FY2025
FY2025 Actual
$22.0M
Prior year
Planned work

What the FY2027 request buys

Verbatim from the R-2A exhibit for project 625315 of PE 0602788F. This is the budget justification's own description of work that has not happened yet — the one thing no other level of the budget carries.

FY2027 planned work

- Continue development of standards that will be used to create an end-to-end (Australia, United Kingdom, and United States) joint machine learning ecosystem for the rapid development, sharing, and deployment of machine learning (ML) and artificial intelligence (AI) tools to enable joint AI missions for nation and coalition operational capabilities, and to enhance interoperability of AI assets between international partners for improved coalition operations. Activities include development, testing, assessment, and verification of "AI Passport" for release to partner nations and their respective users. - Continue research and development of an AI battle management command and control (BMC2) system to bring operators into the 5th Generation combat fight to develop a tech insertion module assisting with BMC2 decisions and enable seamless synchronization and mission persistence throughout the long-range kill chain (LRKC) life cycle. Activities include algorithm development and experimentation of capability during test event.

FY2026 to FY2027 change

FY 2027 funding decreased compared to FY 2026 by $2.171 million due to re-prioritization to meet the nation's future security needs and the completion of research and development of counter-AI techniques and an end-to-end analysis engine, an AI predictor to enable AI adaptation for pulsed operations, a capability to represent and display spatio-temporal logistics information, an identification and characterization of technical gaps for pulsed operations, management of distributed command and control resources and assessment of task redistribution, and an application of generative AI techniques for indicators & warnings analysis, for advancing ML approaches for operations in complex adversarial environments.

Before the request year

FY2026: the year under way

Prior-year accomplishments and current-year plans from the same exhibit. Context for the FY2027 plan, not a series — an activity partitions its project exactly in the request year, but can under-cover it in earlier years.

FY2026 plans — current year

- Continue development of standards that will be used to create an end-to-end (Australia, United Kingdom, and United States) joint machine learning ecosystem for the rapid development, sharing, and deployment of machine learning (ML) and artificial intelligence (AI) tools to enable joint AI missions for nation and coalition operational capabilities, and to enhance interoperability of AI assets between international partners for improved coalition operations. Activities include development, testing, assessment, and verification of "AI Passport" for release to partner nations and their respective users. - Complete research and development to manage the complexity of distributed C2 resources and assess the ability to perform task redistribution in a highly-resource constrained environment. Optimize, orchestrate, and execute workflows from across multiple locations for distributed C2. Activities include development, testing, and assessment of distributed C2 optimization algorithms on operationally relevant data and scenarios. - Complete research and development of generative AI techniques applied to DAF data and problem sets through selected use cases, focusing on indicators & warnings analysis and multi-modal knowledge analysis through sensor fusion. Increase effectiveness for DAF operations by leveraging generative AI techniques to process large amounts of data that leads to optimal decision-making and C2. - Complete advancing research and development ML approaches for supporting and performing operations in complex adversarial environments. Increase the speed to employ AI agents for operational evaluation for potential implementation. - Commence and complete research and development of counter-AI techniques via non-cyber means for DAF and DoW missions to enhance warfighter counter-AI that will degrade or deny adversaries' own ability to utilize their AI & ML. Activities include initiating the development of an end-to-end analysis engine to perform operational analytics against adversarial AI using established counter-AI techniques. - Commence and complete research and development for an AI predictor to enable AI adaptation for pulsed operations to enhance the adaptation of AI & Autonomy for operations in contested environments against peer adversaries. - Commence and complete research and development for a capability to represent and display spatio-temporal logistics information and connections to varying mission objectives and perform analysis on the robustness of logistics plans to enhance logistics planning for DAF operations that reduce, or are resilient to, adversary attacks. - Commence and complete research and development to identify and characterize technical gaps for pulsed operations as it relates to command, control, communications, computers, and intelligence (C4I). Identify technological capabilities needed for command and control (C2) and battle management (BM) of pulsed operations in the Pacific theater. - Commence research and development of an AI battle management command and control (BMC2) system to bring operators into the 5th Generation combat fight to develop a tech insertion module assisting with BMC2 decisions and enable seamless synchronization and mission persistence throughout the long-range kill chain (LRKC) life cycle. Activities include algorithm development and experimentation of capability during test event.

Money

Three years, and no five-year plan

An R-2A activity publishes the prior year, the current year and the budget year. The FYDP outyears exist at project and program-element level and are deliberately absent here rather than inferred. Estimate types are colored and never summed into one figure.

25022.0FY25ACTUAL30.7FY26ENACTED28.6FY27REQUEST
Actual Enacted Request
Fiscal YearEstimate TypeAmount ($M)
FY2025Actual22.0
FY2026Enacted30.7
FY2027Request28.6

This activity is 30% of project 625315's FY2027 request and 19% of PE 0602788F's. In the request year the activities under a project sum to it exactly; in the current year they under-cover it in about 9% of cases, so an activity's delta can legitimately exceed its parent's and the two must not be compared row to row.

Where this sits

6 activities in project 625315

Every R-2A line of this project, largest FY2027 request first. Linked where the activity has enough of its own narrative to carry a page; the rest are shown in full on the project page.

Multi-Domain Exploitation and Decision Support$29.4M ▼ 26%
Combined Joint All-Domain Command & Control (CJADC2) — this activity$28.6M ▼ 7%
Assured Communications & Networks$28.3M ▼ 11%
Quantum Information Science$8.9M ▼ 30%
Data to Decisions$0.0M
Processing Technologies$0.0M
Source
FY2027 Department of the Air Force RDT&E Budget Justification · Exhibit R-2A · PE 0602788F, project 625315 (President's Budget PB2027). Congressional marks are recorded on the program element, never on an activity.
Machine access
Markdown twin /programs/0602788F/625315/a0.md · MCP mcp.hitchintel.combudget_get_activity