Moving troops and resources to a fight, and continuing that flow during the conflict, is vital for the Marine Corps. The arteries connecting Marines to the bullets, food, and fuel they need are crucial for their success, and all the work to move those items across the oceans is for nothing if it falters in the last mile. Once ashore, Marines must maximize the capabilities of the logistical infrastructure—roads, bridges, railways, and ports.
Discussing a potential future conflict with China, then-Commandant General David H. Berger stated in 2021, “If they’re able to contest and really choke us off logistically, they’ll take us to our knees. We can’t let that happen.” As the Marine Corps revamps its logistics for a new era of near-peer conflict, it must pay attention to an often overlooked (but critical) support function for its logistics combat elements (LCEs): intelligence. It is time for a bold investment in intelligence support capabilities that incorporates commercial unmanned solutions and applies artificial intelligence (AI) across a spectrum of areas.
Intelligence Support to the LCE
Intelligence support organic to LCEs is a vital element of the Marine air-ground task force (MAGTF). When operating effectively, it can enhance logistical survivability and improve the battlespace awareness of the entire MAGTF. Currently, small teams staff most intelligence shops at the battalion and regiment level, acting as conduits for intelligence rather than producers of intelligence. With limited teams, LCEs integrated into MAGTFs instead rely on the aggregate capabilities of the larger MAGTF S-2/G-2 element. This structure is inadequate to satisfy the LCEs’ unique intelligence requirements and does not capitalize on the value a more robust LCE intelligence section would provide to the whole MAGTF. Instead, LCEs compete for intelligence resources from air and ground combat elements (ACE and GCE)—often a hard sell for commanders.
Failing to provide robust intelligence support to LCEs creates considerable risk. A clever adversary engaged against GCEs and ACEs likely would seek to cut combat units off from the supplies and support that make them effective. By targeting the LCE, an adversary could starve these units of fuel, food, water, and ammunition, something effective intelligence support could help anticipate and mitigate.
Investing with an Intelligence Focus
The Marine Corps has a unique opportunity to align intelligence support to the LCE with the statements of senior leaders and the complex threat environment of any future conflict. Marine Corps Doctrinal Publication (MCDP) 4: Logistics, published in March 2023, updated the service’s foundational logistics doctrine for the first time in 25 years. The revamped publication acknowledges that LCEs require robust intelligence integration, as LCEs are critical consumers and sources of intelligence. Likewise, Installations and Logistics 2030 recognizes the need to make changes to logistics and highlights areas for evaluation, including experimentation with autonomous systems and the artificial intelligence (AI) tools needed to implement Force Design 2030.
A relatively small investment in capabilities and equipment could benefit LCE intelligence sections as well as the larger MAGTF, and help the naval services deliver the fight to an adversary. Fortunately, commercial logistics sector intelligence requirements often mirror those of LCEs, and some firms already have invested resources to develop advanced logistical intelligence capabilities. LCE intelligence sections have a unique opportunity to adapt those commercial technologies to warfighting.
Unmanned Systems: Getting the Tools
LCEs must understand the conduits that supplies and equipment need to move into and through the battlespace. Intelligence teams supporting LCEs conduct physical network analysis (PNA) to evaluate and plot logistical support networks (roads, rails, pipelines, etc.) for an operational environment and provide that information to the other elements of the MAGTF. Their understanding of these networks could benefit from tools that industries already use to improve efficiency, reduce staffing, and significantly increase data quality.
With more than 200,000 kilometers of railways in the Asia Pacific region, rail transport will be critical for moving supplies to sustain the MAGTF in any future Pacific conflict.Tools to monitor railways should be standard for LCEs. Commercial rail companies have already integrated emerging technologies for surveying and maintaining awareness of the status of their infrastructure, providing readily available and tested solutions for the LCE.
Unmanned aerial and ground systems (UASs and UGVs) are now commonplace in rail operations for surveying large distances and remote sections or providing rapid damage assessment. The Staaker BG-300 Railway Drone, for instance, physically rides the rails to monitor for issues. Unmanned systems such as this prevent companies from using manpower for supporting functions while still allowing them to gather and process the environmental information they need.
Bridges, also essential in the movement of troops and supplies, present major obstacles when they are downed, blocked, or denied. In October 2022, Ukrainian forces spent considerable effort to destroy the logistically valuable Kerch Strait Bridge connecting Russia and occupied Crimea. Earlier in the war, Ukrainians destroyed bridges to slow the advance of Russian troops on Kyev and choke off the supplies they needed to continue their offensives. In the Pacific, there are more than 29,000 bridges in Taiwan alone. The LCEs’ ability to know the status of bridges in the region and confidently move supplies across them would be integral to the success of troops engaged in combat during a future engagement.
Conducting a proper engineer bridge reconnaissance is a time-consuming process requiring Marines on and around a bridge. Here, commercial providers employ UASs to conduct the civilian equivalent. The Department of Transportation conducted multiple studies of UAS applications for bridge inspections and found that their use would “alleviate several barriers or challenges inherent in the bridge inspection process, including the high cost and limited availability of specialized access equipment, limited inspector access to portions of a bridge, and the cost and safety implications.” Systems by companies such as Skydio 2+ and Elios 3 offer multisensor platforms incorporating edge AI to assist with flying and assessing collected data. Off-the-shelf options range from $700 to more than $25,000 for more capable models.They are cost-effective enough to be pushed to the company or platoon level and could prevent losing a Marine unnecessarily.
Many unmanned systems integrate some form of AI, allowing them to rapidly process, exploit, and disseminate (PED) useful information from the raw data collected. PED is a major function of the intelligence cycle but is time-consuming when conducted entirely by humans. By integrating unmanned systems and artificial intelligence, companies augmented their ability to collect and analyze relevant data while reducing manpower requirements. The possibilities extend beyond bridges and railways. Commercial firms also use unmanned systems to inspect pipelines for oil and water. They survey water resources and infrastructure. They even monitor and verify the status of large port facilities. Adoption of unmanned capabilities have allowed commercial firms to do more, with less people. This should be a wakeup call for the Marine Corps to update the LCE’s unmanned capabilities.
Artificial Intelligence: Master the Data
Hardware alone is rarely the solution, and this problem set is no different. Even without an influx of unmanned systems hosting a range of sensors, it is time consuming and challenging to ingest, process, and apply data. Recent advances in artificial intelligence (AI) have produced promising tools that can help with this issue. The military applications of AI are expansive, and the Department of Defense (DoD) and Marine Corps are actively working to apply AI to improve warfighting capabilities. Installations and Logistics articulates the need for further analysis of how to apply AI to improve efficiency and support. AI has a powerful role to play in intelligence support, especially with logistical concerns where big-data sets lend themselves to the strengths of AI.
LCEs could apply existing or developmental AI-enabled solutions from government and commercial providers. In 2019, the Office of the Director of National Intelligence released a comprehensive AI implementation strategy, highlighting the need to adopt commercial and open source AI solutions. Think tanks also concluded that AI will be vital in helping manage more ubiquitous sensors, automate some elements of scheduling and deconflicting collection efforts, and sort through the enormous piles of information that intelligence Marines must triage for it to be of any use to a commander. Initial processing of information from new sensors could be automated by integrating AI, significantly increasing units’ speed and accuracy in identifying areas of the environment that will affect logistics operations. With the integration of new unmanned sensors, AI support would be vital to process the flow of data.
Powerful AI tools such as ChatGPT have garnered attention for their ability to answer complex questions accurately. Large language models based on this large language model technology can help Marines sort and search data across the vast web of siloed information. Computer vision algorithms can be applied to sort the visual data that comes from overhead satellite imagery, UAS imagery, and even imagery taken by Marines leading convoys.1 Commercial solutions could be adapted to the warfighter, and vendors such as Palantir already produce tailor-made combat solutions. The various disciplines of AI could readily be applied to intelligence support, particularly for the LCE.
Commercial providers are not the only pioneers in the field. The Marine Corps should consider the work done through various DoD and intelligence community elements. The Defense Intelligence Agency Machine-assisted Analytic Rapid-repository System (MARS) program aims to automate routine processes by integrating the artificial intelligence and machine learning to sort big data and augment analytic capacity.This program would be an excellent starting point to integrate AI for intelligence support to logistics. Even administrative tasks tying up DoD employees are being augmented by AI programs such as GAMECHANGER, a tool based on a large language model designed to ingest the endless volumes of DoD policies and then rapidly provide answers to users needing assistance. Using similar programs on classified systems could help Marines sort intelligence and offset manpower shortages for LCE intelligence sections.
Resourcing Logistics Intelligence for the Future Fight
It is an exciting time to be a military logistics professional. The compounding issues of a near-peer competitor and the emergence of technologies are reshaping what is possible (and desirable) for logistics for the next generation. Some have called for regenerative logistical capabilities, and others have noted narco-submarines’ utility in potentially sustaining a dispersed force under contested conditions. These are thought-provoking suggestions worth investigating. Regardless of the larger logistical model the Marine Corps adopts, it must rethink its intelligence support to logistics units, providing tools to improve self-sufficiency and more effectively use the valuable intelligence LCEs can provide.
These investments do not need to (and should not) start from scratch. Commercially available unmanned technologies could help LCE intelligence personnel provide high-fidelity physical network analysis data that benefit the whole MAGTF and naval services. Failing to make a bold investment in the sustainability of logistics capabilities is a fatal flaw. The Marine Corps must seize the opportunity and dramatically remake the intelligence support provided to its logistics combat elements.
1. Kirill Eremenko, “Artificial Intelligence (AI) for Executives and Top-Level Managers: How Does Computer Vision Work,” U.S. Air Force Phantom AI Accelerator Course.