Top 10 Use Cases of Gen AI in Defense Tech & National Security
By Umang Dayal
May 9, 2025
The defense tech and national security are undergoing a profound technological shift, and at the forefront of this transformation is Generative AI. From creating battlefield simulations to generating actionable intelligence summaries, GenAI is beginning to play a critical role in how modern militaries operate and respond.
As global security environments become increasingly complex and multi-domain, from cyberspace to urban warfare, the demand for faster, more adaptive, and more autonomous systems has never been greater. Traditional approaches to decision-making and defense operations often struggle to keep up with the speed and scale of today’s threats. GenAI offers a powerful solution by enabling rapid synthesis of data, predictive analysis, and scenario generation, thereby supporting commanders and analysts in high-pressure environments.
This blog explores the top 10 use cases of Gen Ai in defense tech and national security, and explores real-world applications.
Use Cases of Gen AI in Defense Tech and National Security
Intelligence Summarization and Threat Analysis
Modern military operations generate vast amounts of data from various sources, including satellite imagery, intercepted communications, and open-source intelligence. Processing this data manually is time-consuming and prone to oversight. Generative AI models can automate the summarization of this information, extracting key insights and presenting them in a concise format for analysts.
These AI systems can identify patterns and anomalies that might be indicative of emerging threats. By continuously learning from new data, they adapt to evolving tactics and strategies employed by adversaries. This dynamic analysis enables military intelligence units to stay ahead of potential threats, providing timely warnings and recommendations. However, the integration of AI into intelligence analysis also raises concerns about the reliability and potential biases of AI-generated insights, necessitating human oversight to validate findings.
Mission Planning and Simulation
Mission planning in military operations involves complex decision-making processes that consider numerous variables, including terrain, enemy capabilities, and logistical constraints. Generative AI can assist by rapidly generating multiple courses of action (COAs), simulating potential outcomes, and identifying optimal strategies. For example, the Pentagon's "Thunderforge" project aims to enhance military planning using AI tools developed in collaboration with tech companies, integrating data from intelligence sources and battlefield sensors to provide commanders with strategic recommendations.
These AI-driven simulations allow for the testing of various scenarios, enabling commanders to anticipate potential challenges and adapt plans accordingly. By incorporating real-time data, generative AI can adjust simulations to reflect changing battlefield conditions, providing dynamic support for decision-making. This capability enhances the agility and responsiveness of military operations, particularly in rapidly evolving conflict zones.
Autonomous Drone Coordination
The deployment of autonomous drones in military operations has transformed surveillance, reconnaissance, and combat strategies. Generative AI enhances the capabilities of these drones by enabling real-time decision-making and coordination without direct human intervention.
These AI systems allow drones to adapt to changing environments, identify targets, and coordinate with other units to execute missions effectively. For instance, in swarm operations, generative AI enables multiple drones to work collaboratively, sharing information and adjusting tactics in response to threats. This level of autonomy enhances operational efficiency and reduces the risk to human personnel in hostile environments.
Electronic Warfare Simulation
Electronic warfare (EW) involves the use of the electromagnetic spectrum to disrupt enemy communications and radar systems. Generative AI can simulate complex EW scenarios, generating synthetic signals and interference patterns to test and improve defense systems. By creating realistic simulations, military units can train for and adapt to various EW threats without the need for live exercises, which can be costly and risky.
These simulations enable the development of countermeasures and the refinement of tactics to protect against electronic attacks. For example, AI-generated decoy signals can be used to confuse enemy sensors, while adaptive jamming techniques can be tested against simulated adversary systems. This proactive approach allows for the continuous improvement of EW capabilities in response to evolving threats.
Personalized Military Training Modules
Traditional military training programs often adopt a one-size-fits-all approach, which may not address the specific needs and learning styles of individual soldiers. Generative AI offers the potential to create personalized training modules that adapt to the performance and progress of each trainee. By analyzing data on a soldier's strengths and weaknesses, AI can tailor training content to focus on areas requiring improvement, enhancing overall effectiveness.
These AI-driven training systems can simulate a wide range of scenarios, from basic drills to complex combat situations, providing immersive and interactive learning experiences. For instance, virtual reality environments powered by generative AI can replicate battlefield conditions, allowing soldiers to practice decision-making and tactical skills in a controlled setting. This approach not only improves readiness but also reduces the costs and risks associated with live training exercises.
Doctrine and Policy Drafting
Developing military doctrines and policies is a complex process that involves analyzing historical data, current capabilities, and future projections. Generative AI can assist by processing vast amounts of information to identify patterns and generate draft documents that serve as starting points for human review. This capability accelerates the development of strategic guidelines and ensures that policies are informed by comprehensive data analysis.
AI-generated drafts can highlight potential areas of concern, suggest alternative strategies, and provide evidence-based recommendations. By automating the initial stages of policy development, military organizations can allocate more resources to critical evaluation and refinement, enhancing the quality and relevance of the final documents. This approach also allows for more frequent updates to doctrines, ensuring that they remain aligned with evolving threats and technologies.
Conversational Battle Assistants
In high-pressure combat situations, access to timely and accurate information is critical for decision-making. Conversational battle assistants powered by generative AI can provide real-time support to commanders and soldiers by answering queries, offering recommendations, and retrieving relevant data. These AI systems can process natural language inputs, making them accessible and user-friendly in the field.
For example, the U.S. Army has experimented with AI chatbots trained to provide battle advice in war game simulations, demonstrating the potential of such systems to enhance operational planning. By integrating with existing communication and information systems, conversational assistants can serve as valuable tools for situational awareness and tactical support.
Synthetic Target Generation for Training and AI Model Development
Effective training and the development of AI models for target recognition rely on extensive datasets representing various scenarios and conditions. Generative AI can create synthetic images and data that simulate different environments, targets, and situations, providing a rich resource for training purposes. This approach addresses the limitations of collecting real-world data, which can be time-consuming, expensive, and potentially hazardous.
Synthetic data generation enables the creation of diverse and customizable datasets tailored to specific training needs. For instance, AI can generate images of vehicles or personnel in various terrains, weather conditions, and lighting conditions.
Cyber Defense and Threat Hunting
The cyber domain is now a critical battleground in defense, with state-sponsored cyberattacks, espionage, and sabotage becoming increasingly common. Generative AI plays a pivotal role in strengthening cyber defense by analyzing massive volumes of network data to identify vulnerabilities, generate synthetic attack scenarios, and simulate potential intrusions. These capabilities allow defense tech to proactively hunt for threats before they escalate. AI can learn from past breaches, model attacker behavior, and simulate zero-day exploits to test a system’s resilience in a controlled environment.
In addition to reactive capabilities, generative AI supports continuous monitoring of complex digital infrastructures. It can create synthetic phishing emails or malware variants to evaluate the robustness of existing detection systems. This synthetic generation helps in training cybersecurity models to recognize novel threats that have not yet been encountered in the wild. It also aids red teams in stress-testing internal systems, thereby improving preparedness. By continuously generating new threats for simulation, defense units can stay ahead of evolving cyber tactics used by adversaries.
Logistics Optimization and Autonomous Resupply
Efficient logistics are foundational to successful military operations, particularly in austere or contested environments. Generative AI is transforming military logistics by optimizing supply chain routes, forecasting demand, and simulating resupply scenarios. These models can process real-time data on terrain, weather, and enemy movement to generate resupply plans that minimize risk and maximize speed. This has led to significant advancements in automated resupply systems using unmanned vehicles or drones capable of navigating complex environments autonomously.
Generative AI also enhances inventory management by forecasting equipment and ammunition consumption patterns based on mission profiles. It can simulate multiple logistical scenarios under different constraints, enabling planners to assess trade-offs in real time. For example, an AI system could model the impact of delayed fuel delivery on a forward operating base and generate mitigation strategies like route changes or reallocation of resources. These AI-powered logistics systems contribute to more agile and adaptive operations, especially in multi-domain operations (MDO) environments.
A key application area is autonomous convoy planning, where AI helps unmanned ground vehicles chart optimal paths through hazardous zones while dynamically responding to threats. By integrating AI into both strategic and tactical logistics, militaries can reduce the need for human personnel in dangerous supply missions, thereby decreasing casualties.
Real-World Examples of Generative AI Applications in Defense Tech
Project Maven – U.S. Department of Defense
Project Maven is the Pentagon’s flagship AI initiative, designed to process and analyze vast amounts of surveillance data. In May 2024, Palantir Technologies secured a $480 million contract to expand the Maven Smart System.
This system leverages AI to ingest data from multiple sources, such as satellite imagery and geolocation data, and uses it to automatically detect potential targets. The expansion aims to provide this capability to thousands of users across various combatant commands, enhancing decision-making processes across the Department of Defense.
Osiris – CIA’s Open-Source AI Tool
The CIA has developed an AI tool named Osiris to manage the overwhelming influx of data from global surveillance technology. Osiris processes open-source data and assists analysts with summaries and follow-up queries, functioning similarly to ChatGPT.
While the integration of generative AI like Osiris offers significant advantages in processing and analyzing intelligence data, it also raises concerns about reliability and potential biases, necessitating human oversight to validate findings.
Anduril’s Lattice for Mission Autonomy and Autonomous Drones
Anduril Industries has developed Lattice for Mission Autonomy, a software platform that simplifies the management of potentially hundreds of drones and robots. In May 2023, the company unveiled this software, which serves as a central node for threat identification, electronic signature management, maneuvering, and more. Lattice enables a single operator to control multiple uncrewed systems, enhancing operational efficiency and reducing the need for extensive manpower.
DARPA’s Air Combat Evolution (ACE) Program
DARPA's ACE program aims to increase human trust in autonomous platforms through AI-driven air combat simulations. In April 2024, a series of trials witnessed a manned F-16 face off against a bespoke Fighting Falcon known as the Variable In-flight Simulator Aircraft (VISTA), which was controlled by an AI agent. These trials demonstrated the potential of AI in executing complex air combat maneuvers, marking a significant milestone in the integration of AI into military aviation.
Palantir and the Army Vantage Program
Palantir Technologies has been instrumental in enhancing military logistics and data management through the Army Vantage program. In September 2023, the U.S. Army awarded Palantir a contract worth up to $250 million to research and experiment with artificial intelligence and machine learning. This initiative focuses on integrating and analyzing thousands of disparate data sources to support readiness, supply chain forecasting, and strategic planning, thereby streamlining decision-making processes across various military domains.
How We Can Help
At Digital Divide Data, we offer comprehensive Generative AI solutions designed to streamline processes and empower your AI models in the defense tech and national security. Our human-in-the-loop process and advanced AI-Integration tools enable us to deliver highly reliable and accurate training data solutions for computer vision and LLM applications.
In the defense sector, accurate, timely, and secure data is critical for operations ranging from intelligence gathering to autonomous systems. Our data operation solutions and data preparation services enable military and defense contractors to efficiently process large volumes of data such as satellite imagery, video feeds, and sensor data into actionable insights.
Conclusion
Generative AI is transforming defense tech and national security, introducing advanced capabilities that enhance strategic decision-making, operational efficiency, and battlefield effectiveness. From intelligence gathering and autonomous systems to cyber defense and logistics optimization, the potential applications of generative AI in defense are vast and increasingly vital for modern military operations.
Adoption of such technologies requires careful consideration of security, ethical, and operational risks. The reliance on AI models to make critical decisions whether in autonomous combat scenarios or logistics optimization requires robust oversight, continuous training, and transparent accountability to ensure safe deployment. As defense agencies and private sector innovators continue to push the boundaries of what generative AI can achieve, it is crucial to remain mindful of the broader implications, including the potential for misuse and unintended consequences.
Talk to our experts to accelerate innovation in defense technology with trusted generative AI.
