# Artificial Intelligence and Machine Learning Technologies — Program Element 0602180A

**Program element:** 0602180A  
**Component:** U.S. Army  
**Appropriation:** 2040 — RDT&E, Army  
**Budget Activity:** 2 — Applied Research  
**Vintage:** President's Budget PB2027  
**Canonical URL:** https://hitchintel.com/programs/0602180A

## Summary

U.S. Army funding falls 100% to a $0.0M request in FY2027.

## Funding profile

| Fiscal Year | Estimate Type | Amount ($M) |
|---|---|---|
| FY2025 | Actual | 15.4 |
| FY2026 | Enacted | 13.7 |
| FY2027 | Request | 0.0 |
| FY2028 | Outyear | 0.0 |
| FY2029 | Outyear | 0.0 |
| FY2030 | Outyear | 0.0 |
| FY2031 | Outyear | 0.0 |

> Estimate types are not summed — the profile mixes actuals, enacted law, the request, and outyear projections.

## Projects (7)

| Project | Title | FY2025 actual | FY2026 enacted | FY2027 request | Move |
|---|---|---|---|---|---|
| DA6 | AI-Enabled Command and Coordination Apl Research | 3.4 | 5.0 | — | −100% |
| CL2 | AI Enhanced Intel Operations Technologies | 2.9 | 2.8 | — | −100% |
| CL7 | ATR Using Multiple Cooperative Sensors App Tech | 3.0 | 2.6 | — | −100% |
| DM7 | Counter AI App Rsch | — | 1.5 | — | −100% |
| CN7 | Predictive Maintenance Applied Research | 5.8 | 1.3 | — | −100% |
| DA5 | AI Enabled Talent Management Applied Research | 0.3 | 0.3 | — | −100% |
| DM8 | AI Enabled Contested Logistics Spt Tools App Tech | — | 0.2 | — | −100% |

> Projects are the summable leaves: the program element total is their sum, never added to it.

### Project DA6 — AI-Enabled Command and Coordination Apl Research

This project designs and develops solutions that enable Artificial Intelligence (AI)-Enabled Command and Coordination. Additionally, project investigates and matures technologies required to enable commanders and their staff to synchronize and converge all elements of available combat power to achieve multi-domain effects. Technology maturation includes the development and testing of algorithms, models, software, hardware, and interfaces required to support the command of Army forces, coordination of Army operations, execution of the operations process, and establishing necessary Command and Control (C2) systems. Work in this project complements Program Element (PE) 0603040A (Artificial Intelligence and Machine Learning Advanced Technologies) / Project DA7 (AI-Enabled Command and Coordination Adv Tech). Work in this project is performed by the Artificial Intelligence Integration Center (AI2C).

| Activity (R-2A) | FY2025 | FY2026 | FY2027 |
|---|---|---|---|
| AI-Enhanced Planning for Optimal Operations | 1.0 | 0.8 | — |
| AI-Enabled Common Operating Picture and Battle Tracking | 1.0 | 0.7 | — |
| Distributed Artificial Intelligence | 0.5 | 0.5 | — |
| AI Foundations for Command and Coordination | 1.0 | 1.0 | — |
| Soldier Assistant Language Technologies | — | 2.0 | — |

> R-2A activities carry the prior, current and budget year only — no five-year plan. Coverage is partial, so count them, never total them.

### Project CL2 — AI Enhanced Intel Operations Technologies

This project will design and develop technologies to augment human intelligence analysts with artificial intelligence (AI) and machine learning (ML)-enabled decision support, workflow automation, and recommendation tools to modernize how the Intelligence Warfighting Function supports Multi-Domain Operations and Joint All Domain Command and Control (JADC2). This project will mature technologies that will enable intelligence organizations to conduct synchronized, proactive intelligence operations, therefore optimizing team performance. Work in this project complements Program Element (PE) 0603040A (Artificial Intelligence and Machine Learning Advanced Technologies) / Project CL1 (AI Enhanced Intel Operations Advanced Technologies). Work in this project is performed by the Artificial Intelligence Integration Center (AI2C).

| Activity (R-2A) | FY2025 | FY2026 | FY2027 |
|---|---|---|---|
| AI-Enabled Intelligence Decision Support | 0.9 | 0.7 | — |
| Foundation for AI Intelligence Support to Operations (ARCANE SERIES) | 0.8 | 0.8 | — |
| AI-Enabled Intelligence Fusion for Targeting | 0.8 | 0.8 | — |
| AI-Enabled Social Media Exploitation | 0.4 | 0.5 | — |

> R-2A activities carry the prior, current and budget year only — no five-year plan. Coverage is partial, so count them, never total them.

### Project CL7 — ATR Using Multiple Cooperative Sensors App Tech

This project will design and develop Artificial Intelligence (AI) and Machine Learning (ML) algorithms that leverage a team of air and ground sensors to autonomously navigate and collaborate through shared perception of the optical, thermal, and electromagnetic spectrums to find, identify, geo-locate, and track targets during reconnaissance missions. These technologies will produce prototype implementations of novel autonomy and detection algorithms to be run on teams of air and ground sensors, as well as an appropriate interface to task and observe feedback from autonomous sensors. Work in this project complements Program Element (PE) 0603040A (Artificial Intelligence and Machine Learning Advanced Technologies) / Project CL6 (ATR Using Multiple Cooperative Sensors Adv Technologies) Work in this project is performed by the Artificial Intelligence Integration Center (AI2C).

| Activity (R-2A) | FY2025 | FY2026 | FY2027 |
|---|---|---|---|
| Collaborative Target Detection and Tracking | 1.2 | 1.3 | — |
| Autonomous and Collaborative Mobility | 1.2 | 0.3 | — |
| Intuitive Mission Command Interfaces | 0.6 | 1.0 | — |

> R-2A activities carry the prior, current and budget year only — no five-year plan. Coverage is partial, so count them, never total them.

### Project DM7 — Counter AI App Rsch

This project designs and develops mechanisms for the implementation of trusted artificial intelligence and machine learning (AI/ML) for processing, detecting, identifying, and reacting to potentially adverse effects on AI/ML capabilities. It provides recommendations for countering adversarial AI/ML, improving algorithms, and ensuring resilience in complex and contested environments. Effective use of Counter-AI to secure response mechanisms for the identification and detection of adversarial AI/ML is critical to address threats in a rapidly evolving environment. These technologies will produce an AI solution that rapidly adjusts AI/ML algorithms to disregard and stop malicious attempts to corrupt Army AI/ML tools. Work in this project is performed by the Artificial Intelligence Integration Center (AI2C).

| Activity (R-2A) | FY2025 | FY2026 | FY2027 |
|---|---|---|---|
| Counter AI ML Model Applied Research | — | 1.5 | — |

> R-2A activities carry the prior, current and budget year only — no five-year plan. Coverage is partial, so count them, never total them.

### Project CN7 — Predictive Maintenance Applied Research

This project designs and develops artificial intelligence (AI) and machine learning (ML) tools and capabilities to predict and analyze maintenance status for emerging and legacy aviation and ground platforms. Investigates techniques to extract data from maintenance databases and platform sensors and make inferences of missing data via virtual simulations. Will investigate maintenance concepts that employ AI data capture and integrate AI tools into enterprise resource planning for military aviation and ground vehicles. Will determine platforms of focus and prioritize by cost and value to Army missions. Each platform will be sequentially investigated at the appropriate component (i.e. engine health) and fleet level. Will determine appropriate technologies and capabilities needed to construct a robust Army-wide predicative maintenance platform that will accelerate the pace of innovation for this problem set. Will validate and inform requirements and technical architectures for modernization efforts of next generation aviation and ground systems both manned and unmanned. These technologies will produce concepts for a digitized maintenance environment that provides real-time decision-making support tools to maintainers and commanders by producing a warfighter optimized front end with an enterprise aggregated back end. Work in this project complements Program Element (PE) 0603040A (Artificial Intelligence and Machine Learning Advanced Technologies) / Project CN6 (Predictive Maintenance Advanced Technology). Work in this project is performed by the Artificial Intelligence Integration Center (AI2C).

| Activity (R-2A) | FY2025 | FY2026 | FY2027 |
|---|---|---|---|
| Predictive Maintenance | 5.8 | 1.3 | — |

> R-2A activities carry the prior, current and budget year only — no five-year plan. Coverage is partial, so count them, never total them.

### Project DA5 — AI Enabled Talent Management Applied Research

This project designs, develops, and validates applied behavioral and social science research to enhance the Soldier Lifecycle (e.g., selection, assignment, training, and leader development) and human relations (e.g., unit cohesion). This project will design and develop new personnel measures and methods that more fully assess potential and predict performance, behavior, attitudes, and resilience. These technologies also provide innovative and effective Force Integration methods to optimize individual and team performance to ensure the Army can meet mission requirements in uncertain and complex environments. This project designs and develops new performance measures and metrics for individuals and units, designs innovative training methods, and conducts scientific assessments to inform Human Capital policy and programs. This project will also investigate non-materiel solutions to help the Army adjust to changes in force size and structure, a variety of mission demands and contexts, challenges in human relations, and budgetary constraints. These technologies will produce tools that can measure and assess the skills of individual Soldiers and units' readiness to meet mission requirements. Work in this project complements Program Element (PE) 0603007A (Manpower, Personnel and Training Advanced Technology) / Project 792 (Personnel Performance & Training). Work in this project is performed by the Artificial Intelligence Integration Center (AI2C).

| Activity (R-2A) | FY2025 | FY2026 | FY2027 |
|---|---|---|---|
| Artificial Intelligence (AI)-Enabled Skill Identification for Job Matching and Team Building | 0.3 | 0.3 | — |

> R-2A activities carry the prior, current and budget year only — no five-year plan. Coverage is partial, so count them, never total them.

### Project DM8 — AI Enabled Contested Logistics Spt Tools App Tech

This project designs and develops AI-enabled contested logistics tools for warfighters using all platforms (legacy and future) at all echelons, from the maintenance area to the lowest tactical level. This project investigates data from programs of record and determines additional data streams required to build a complete picture of logistics operations in a contested environment. Contested logistics data will investigate the required maintenance data, operations information, and personnel data to increase unit readiness and reduce decision making timelines and predict unit readiness based on historical operations. These technologies will design a suite of applications uniquely tailored to the end-user that will actively expand machine learning capabilities across the force with regards to the contested logistics domain. Work in this project complements Program Element (PE) 0603040A / Artificial Intelligence and Machine Learning Advanced Technologies / CN6 / Predictive Maintenance Advanced Technology. Work in this project is performed by the Artificial Intelligence Integration Center (AI2C).

| Activity (R-2A) | FY2025 | FY2026 | FY2027 |
|---|---|---|---|
| Federated Predictive Logistics Applied Research | — | 0.2 | — |

> R-2A activities carry the prior, current and budget year only — no five-year plan. Coverage is partial, so count them, never total them.

## Mission & acquisition strategy

This PE investigates artificial intelligence (AI) and machine learning (ML) to support an AI-enabled Multi-Domain Operations (MDO) Force to mature target recognition/detection using multiple cooperative autonomous sensors (MCAS), leader decision-making, replication of tactical behaviors to enable autonomous capabilities for maneuver, predictive maintenance, and intelligence support for operations in support of long-range precision fires. The Army's Artificial Integration Center (AI2C) will provide strategic guidance and coordination of these applied research efforts in AI/ML across the Army Modernization enterprise.

## Related program elements

- [0603040A — Artificial Intelligence and Machine Learning Advanced Technologies](https://hitchintel.com/programs/0603040A) (Army)
- [0601601A — Artificial Intelligence and Machine Learning Basic Research](https://hitchintel.com/programs/0601601A) (Army)
- [0305205N — UAS Integration & Interoperability](https://hitchintel.com/programs/0305205N) (Navy)
- [0608140D8Z — Enterprise Platform and Capabilities Software Pilot Program](https://hitchintel.com/programs/0608140D8Z) (Defense-Wide)

## Source & machine access

- **Source:** FY2027 Department of the Army RDT&E Budget Justification, Exhibits R-2/R-3, PE 0602180A (PB PB2027).
- **MCP:** `mcp.hitchintel.com` — `budget_get_program_element(pe="0602180A")`.

*HitchAI is an independent intelligence service, not affiliated with the U.S. Department of Defense. Budget figures are requests/estimates, not obligations.*