R-2A Activity · President's Budget PB2027

Securing Artificial Intelligence for Battlefield Effective Robustness (SABER)

FY2027 Request
$16.4M
▲ 20% vs FY2026
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This activity requests $16.4M in FY2027, 12% of project MSL-05, up 20% on FY2026. The R-2A exhibit describes it across FY2026–FY2027, including what the FY2027 money is planned to buy.

FY2027 Request
$16.4M
▲ 20% vs FY2026
FY2026 Enacted
$13.7M
In law
Planned work

What the FY2027 request buys

Verbatim from the R-2A exhibit for project MSL-05 of PE 0602025E. 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

- Refine AI risk analysis techniques and tools based on the results of initial operational exercises and red team experiences. - Quantify the effectiveness of alternative robustness enhancements and TTPs across diverse use cases. - Conduct high-fidelity operational and red team exercises targeted to high-priority DoW AI-robustness use cases, and capture results in AI-robustness TTPs. - Explore the combined AI-cyber-physical attack and counter-measure spaces to anticipate and prepare for sophisticated adversarial AI challenges.

FY2026 to FY2027 change

The FY 2027 increase reflects continued development of AI risk analysis techniques and tools and expanded efforts to evaluate the technologies on diverse DoW use cases.

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

- Formulate a comprehensive approach to adversarial AI to serve as the basis for the development of risk analysis and robustness enhancement of AI-enabled systems. - Create techniques and tools for use by developers and red teams to perform risk analysis of AI-enabled systems during development and operations. - Collaborate with the Joint Force on a series of high-fidelity operational exercises to iteratively assess and red team AI-enabled military systems in battlefield settings, to demonstrate utility of AI robustness techniques across multiple use cases, and to formulate AI robustness TTPs.

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.

013.7FY26ENACTED16.4FY27REQUEST
Enacted Request
Fiscal YearEstimate TypeAmount ($M)
FY2026Enacted13.7
FY2027Request16.4

This activity is 12% of project MSL-05's FY2027 request and 1.0% of PE 0602025E'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

14 activities in project MSL-05

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.

Artificial Intelligence Engineering and Assurance Studies and Concepts$39.7M NEWArtificial Intelligence Operations and Effects Studies and Concepts$37.7M NEW
Securing Artificial Intelligence for Battlefield Effective Robustness (SABER) — this activity$16.4M ▲ 20%
Artificial Intelligence Quantified (AIQ)$13.4M ▲ 42%Anticipatory and Adaptive Anti-money Laundering (A3ML)$10.2M ▼ 22%
Fostering Research and Growth in Emerging Artificial Intelligence (AI FORGE)$6.6M ▲ 37%
Kallisti$6.0M ▼ 43%
National Security Economic Theory (NASCENT)$5.2M ▼ 70%
Transfer from Imprecise and Abstract Models to Autonomous Technologies (TIAMAT)$2.7M ▼ 82%
Scientific Feasibility (SciFy)$1.2M ▼ 55%
Open Price Exploration for National security (OPEN)▼ 100%
Learning Introspective Control (LINC)▼ 100%
Assured Neuro Symbolic Learning and Reasoning (ANSR)▼ 100%
Artificial Intelligence Cyber Challenge (AIxCC)▼ 100%
Source
FY2027 Office of the Secretary of Defense RDT&E Budget Justification · Exhibit R-2A · PE 0602025E, project MSL-05 (President's Budget PB2027). Congressional marks are recorded on the program element, never on an activity.
Machine access
Markdown twin /programs/0602025E/MSL-05/a0.md · MCP mcp.hitchintel.combudget_get_activity