Accelerating Intelligence Dissemination: Leveraging MAVEN AIP Agent Studio for HUMINT Reporting
Introduction
The objective of human intelligence (HUMINT) collection, as outlined in Army Field Manual (FM) 2-22.3, Human Intelligence Collector Operations, is to provide the commander with prompt, precise, and objective information, delivered in a standardized, structured format. Timely and accurate intelligence reporting is an essential driver of force readiness, helping leaders make informed, data-driven decisions in the heat of battle. Yet FM 2-22.3 also establishes robust administrative requirements for intelligence information reports (IIRs) while noting that the gap between raw data collection and doctrinal reporting can delay actionable intelligence.1 Traditional HUMINT reporting is a laborious, time-consuming process that requires extensive personnel effort. Artificial intelligence (AI) offers a practical solution to this problem: it can quickly aggregate collectors’ notes and convert them into polished, doctrinally formatted reports, closing the reporting gap and enhancing military readiness.
HUMINT reporting has historically been a slow, grinding process. Translating a localized conversation or a page of raw field notes into a doctrinally sound IIR requires hours of careful drafting, formatting, and editing. Collectors grapple with formatting issues, battle passive voice, and ensure every paragraph follows the stringent theater rules such as Combatant Command (COCOM) Standard Operating Procedures (SOPs). This level of administrative detail requires deep quality control and quality assurance checks, frequently resulting in reports being routed back and forth between collectors and reports officers. This leads highly trained collectors to devote a disproportionate percentage of their time to basic data entry and wordsmithing and delays delivery of critical intelligence to the customer.
Applying AI to Intelligence Reporting
To address the administrative burden of traditional HUMINT reporting, AI can be applied directly to drafting and formatting. Palantir’s Artificial Intelligence Platform (AIP) includes a tool called MAVEN AIP Agent Studio, which has been successfully implemented on the Secret Internet Protocol Router Network (SIPRNet), where it functions as an orchestration layer within the Maven Smart System (MSS). This allows users to apply specific logic and doctrinal standards to raw, unstructured data. The system is designed explicitly to fuse and automate disparate data and workflows across complex operational environments to allow for faster “sensor-to-shooter” and “data-to-decision” timelines for the Joint Force and NATO.2 Leveraging AIP, the system creates a no-code environment where intelligence professionals can construct their own custom “agents” to perform repetitive processes.
Given a uniform set of collector notes and a predefined format, an AI agent can generate a fully structured, readable report requiring little to no additional formatting. The team leader or collectors can create a new AIP agent configured with formatting specifications for the desired report format. That AIP agent can be pinned to the MAVEN task bar to allow easy access whenever a collector needs to generate a report. While an experienced HUMINT collector is still required to review, validate, and issue the report, allowing AI to take care of administrative tasks dramatically shortens the time needed to prepare an IIR. This allows more time for HUMINT operations, research, and analysis, while retaining the quality of the intelligence offered.
A Proof-of-Concept Case Study
Recently, First Cavalry Division (1CD) HUMINT collectors conducted a pilot test run of the MAVEN AIP Agent Studio to tackle reporting bottlenecks. The workflow is straightforward: a collector simply logs raw notes into a standard Word document. Using the AIP agent hosted locally on SIPRNet, the collector issues a system command prompt along the lines of “format this into an IIR according to the COCOM HUMINT SOP standards.”
Figure 1: Side-by-Side Task Time Comparison with Savings
The quantitative effect of this workflow has been immediate and significant. Before collectors began using this tool, one standard IIR required approximately 125 minutes of manual drafting, formatting, and editing. Now, however, a collector may refine the generated draft in just 20 minutes. Adding in the required manual research for grids and intelligence requirements, the overall time required to produce a finished, quality-controlled IIR using MAVEN Agent Studio is now roughly one hour. As an example, 1CD collectors produced 4 completed IIRs within one day of deciding which AI model to use for the task and dialing in prompts. With the help of AI, the group saved an estimated 105 minutes per report.
The Payoff
The best metric for any new operational tool is whether it improves mission outcomes and supports the warfighter. MAVEN AIP Agent Studio has transformed reporting from an administrative burden to an operational driver. Commenting on this evolution, one of 1 CD’s corps-level HUMINT Operations Cell reports officers said that reporting quality has substantially improved since the team began using AI, noting enhanced readability across the board, less time spent on quality assurance and quality control, and attention-grabbing subject lines and summaries that immediately highlight intelligence value for consumers. This shift has resulted in a significant operational payoff to individual collectors.
Figure 2: Traditional QA/QC Time Compared to AI-assisted QA/QC Time per IIR
Traditionally, it was not unusual for a collector to have to rewrite an IIR 3 or 4 times to fix formatting issues, passive voice critiques, or doctrinal conflict issues. The AI tool produces a product that is nearly 100% doctrinally aligned on the first draft, significantly reducing the QA/QC timelines at echelon. This ensures collectors are largely freed from performing endless data entry. Instead, they are spending that time on their core HUMINT responsibilities: deep research, verifying intelligence requirements, and conducting HUMINT collection operations. This accelerates the intelligence cycle on the ground at the tactical level, improving both speed and accuracy.
The “so what” here extends well beyond local unit effectiveness. In saving collectors hours of typing, this is a major improvement that will meaningfully accelerate HUMINT’s contribution to the greater Intelligence Warfighting Function. Because AIP Agent Studio enforces rigorous adherence to doctrinal formatting—see, for example, COCOM HUMINT SOPs—the resulting IIRs, while engineered for machine ingestion, are highly readable for humans. These complete reports are easily ingested by the wider MSS to more quickly update the common operational picture. This does more than speed up reporting: it configures products for enterprise-level data ingestion. The process ensures tactical HUMINT feeds into the strategic picture, allowing commanders to monitor and act on actionable insights in near real-time.
Preparing for the Future: Meeting the Demands of LSCO
The transition to large-scale combat operations (LSCO) demands a fundamental shift in how the Intelligence Warfighting Function operates. FM 3-0, Operations, describes LSCO against peer and near-peer threats as characterized by intense lethality, degraded communications, and relentless operational tempo.3 The force that can process, analyze, decide, and act faster has the operational advantage in this environment. The deliberate, multi-hour reporting processes used in counterinsurgency operations are too slow for the demands of the modern battlefield.
Army Doctrine Publication (ADP) 2-0, Intelligence, reflects this same principle, underscoring that intelligence must arrive quickly, remain accurate, and anticipate future developments to allow commanders to seize the initiative.4 Administrative formatting requirements bog down collectors, delaying intelligence dissemination and directly affecting the commander’s situational awareness. Furthermore, ADP 6-0, Command and Control, emphasizes the critical nature of the commander’s decision cycle. Delayed reporting introduces a significant lag in this cycle, potentially rendering intelligence obsolete by the time it reaches the decision-maker.5
At the tactical level of operations, Army Techniques Publication (ATP) 2-22.33, 2X Operations and Source Validation Techniques, stresses that the rapid flow of HUMINT reporting from the collector to the analytical elements is vital for cross-cueing other intelligence disciplines.6 The integration of MAVEN AIP Agent Studio appears to reduce IIR production time by roughly 60%, thereby expediting the dissemination of critical intelligence to decision-makers. Reclaiming hours of administrative time per collector allows intelligence cells to operate at the speed of LSCO, enabling commanders to maintain an accelerated tempo and consistently act inside the adversary’s decision cycle.
Challenges and Limitations of AI in Reporting
While AI offers significant potential for reporting, it is not a “fire and forget” system. There are critical limitations where the tool falls short, requiring manual intervention:
- Grid Verification and Spatial Data. AI models may struggle with precise spatial data, legacy grid formats, or geographically ambiguous notes. Collectors must manually research and verify all Military Grid Reference System and latitude/longitude coordinates to confirm accuracy before publication.
- Requirement Mapping. The tool does not automatically know which specific Intelligence Requirements, Priority Intelligence Requirements, or Specific Information Requirements the raw data answers. Collectors must manually research theater requirements and explicitly align the generated report to the correct intelligence gaps, a process that itself may require manually configuring a new AIP agent to track current requirements.
- Contextual Understanding. An AI agent may occasionally miss subtle cultural or operational nuances present in the collector’s notes. The AI will format what it is given, but the collector retains sole responsibility for the “so what” of the intelligence.
- Human Oversight and Quality Control. Although it has proven valuable, AI can still misinterpret ambiguous or incomplete input. The heavy analytical lifting remains with the collector. As FM 2-22.3 makes clear, collectors are still fully responsible for the factual accuracy and rigorous quality assurance and quality control of reports before they are released.7 The AI drafts the shell, but the collector provides the substance and verification.
Recommendations
Units can harness AI’s potential for intelligence reporting by taking the following steps:
- Develop AI-Enabled Reporting SOPs. Intelligence cells should integrate AI drafting tools into their existing reporting architectures, creating clear left and right limits for what the AI is allowed to process.
- Establish Prompt Engineering Training. Units should establish internal training programs on writing effective prompts, ensuring all collectors know how to command AI agents to utilize specific SOPs (such as COCOM standards).
- Enforce Strict Human-in-the-Loop Validation. Leadership must enforce policies requiring manual verification of all grid coordinates, intelligence requirements, and AI-generated source descriptions prior to release.
Conclusion
Military professionals can use AI to automate formatting and grammar checking. This speeds up reporting, improves readability, and strengthens operational readiness. Challenges in validating grids and requirements persist, but AI’s advantages in saving time are clear. By using these tools, military intelligence organizations can empower collectors to spend less time typing and more time analyzing, better supporting national security and advancing readiness for LSCO.
Endnotes
1. Headquarters (HQ), Department of the Army, Field Manual (FM) 2-22.3, Human Intelligence Collector Operations (Government Publishing Office [GPO], 06 September 2006).
2. Palantir, “Maven Smart System: Innovating for the Alliance,” Palantir Blog, 05 March 2026, https://blog.palantir.com/maven-smart-system-innovating-for-the-alliance-5ebc31709eea.
3. HQ, Department of the Army, FM 3-0, Operations (GPO, 21 March 2025).
4. HQ, Department of the Army, Army Doctrine Publication (ADP) 2-0, Intelligence (GPO, 31 July 2019).
5. HQ, Department of the Army, ADP 6-0 Command and Control (GPO,
6. HQ, Department of the Army, Army Techniques Publication 2-22.33, 2X Operations and Source Validation Techniques (GPO, 09 September 2016, including Change 1, 29 May 2025), access restricted.
7. HQ Department of the Army, FM 2-22.3, Human Intelligence Collector Operations.
CW2 Jordan Peters serves as the Operational Management Team (OMT) Chief for the 3rd Armored Brigade Combat Team, 1st Cavalry Regiment (3 ABCT, 1CD). He has completed five deployments with units, including 201st Expeditionary Military Intelligence Brigade, 82nd Airborne Division, 1st Security Forces Assistance Brigade, 1st Special Forces Group, and 1st Cavalry Division. CW2 Peters holds a masters degree in intelligence studies from American Military University.