방위 분야 인공지능(AI) 및 애널리틱스 시장 : 시장 점유율 분석, 업계 동향 및 통계, 성장 예측(2026-2031년)

According to Mordor Intelligence, the artificial intelligence and analytics in defense market size is expected to grow from USD 10.41 billion in 2025 to USD 11.79 billion in 2026 and is forecasted to reach USD 21.93 billion by 2031 at a 13.22% CAGR during 2026-2031.

This report is Segmented by Component (Hardware, Software, and Services), Platform (Airborne, Land, and Naval), Application (Cybersecurity, Battlefield Healthcare, Warfare Platform, Logistics Management, and More), Technology (AI, Big Data Analytics, and Others Technologies), and Geography (North America, Europe, and More). The Market Forecasts are Provided in Terms of Value (USD).

Global Artificial Intelligence And Analytics In Defense Market Trends and Insights

Rising Defense Expenditure on AI-Enabled Autonomous Systems

Defense buyers are converting pilots into programs with contracts that fund autonomy at scale across air, ground, and maritime domains. The US Navy's multiyear award to Saronic for modular unmanned surface vessels signals procurement acceptance of attritable systems and validates mission demand for autonomous maritime surveillance and security roles. Software spending is expanding through enterprise-level agreements that embed data integration and AI decision support across services and classification levels, demonstrated by the US Army's maximum-value agreement for Palantir platforms. Allied governments are standardizing on AI-enabled decision support as well, with the UK awarding a large contract for a data integration and AI platform that consolidates workflows and accelerates delivery across defense organizations. Flight test activity has also advanced autonomy maturity with collaborative combat aircraft demonstrations that validate mid-flight software handoffs and interoperability between competing control stacks, an indicator that autonomy software is approaching multi-vendor operability at a relevant scale. New solicitations for classified-ready compute clusters indicate continued investment in training and hosting advanced models within secure environments, strengthening demand for hardened edge and deployable cloud infrastructure.

Exponential Growth of Real-Time Battlefield Data

Operational video and telemetry generation has surged, with Ukraine's war experience producing millions of hours of video used to train detection and targeting models. This data foundation enables faster classification cycles and improved accuracy rates in the field. Field demonstrations by the Indian military showed that fusing satellite, drone, and radar feeds using machine learning improved detection accuracy against concealed launchers, supporting the case for multi-sensor analytics on contested borders. Intelligence platforms that scale across services, such as Maven deployments, are helping process imagery and signals data at speeds that reallocate analyst time to higher-value tasks, aligning with the operational shift toward automated triage and human-on-the-loop review. As software-defined kill chains depend on accurate, timely data, institutions are establishing model-serving platforms and common data layers in accredited environments to shorten the collection-to-decision timelines. The combination of more sensors, better onboard compute, and secure AI pipelines now underwrites mission threads where machine-speed correlation becomes decisive in contested electromagnetic conditions.

High Upfront Integration Costs

Integrating AI into legacy networks and platforms involves accreditation, cybersecurity, and interface mediation, which extend timelines and add costs. Accreditation pathways, such as the Cybersecurity Maturity Model Certification Level 2, have become table stakes for software vendors that want to handle controlled unclassified information across defense networks. Program offices are also working to standardize software stacks across vessels and platforms to reduce fragmentation, which can lower integration cost but requires upfront investment in typical operating environments. Department-level guidance that promotes automation while ensuring human oversight of lethal outcomes means systems must be designed with auditability and controls, which adds non-recurring engineering workload for safety and governance. The artificial intelligence and analytics in the defense market reflect this reality in services growth rates, as integrators monetize ongoing accreditation and sustainment activities aligned with evolving compliance baselines. Vendors with prior accreditations and cleared personnel enjoy a head start, but many programs still require tailored integration that cannot be reused across customers.

Other drivers and restraints analyzed in the detailed report include:

1. Government AI R&D Funding Initiatives
2. Need for Faster, Data-Driven Decision-Making
3. Scarcity of Defense-Qualified AI Talent

For complete list of drivers and restraints, kindly check the Table Of Contents.

Segment Analysis

Hardware accounted for 45.70% of 2025 revenue, setting the baseline for compute, sensors, and autonomous platforms, while services posted the fastest projected growth at a 17.10% CAGR through 2031 as integration and sustainment became core value drivers. Authorities are procuring classified-ready compute clusters to support current and next-generation models, including large language and vision architectures, which reinforces demand for ruggedized servers and accelerators. At the same time, enterprise data platforms and command-and-control software continue to anchor software spending, with multi-service agreements that bring common tooling to analysis, operations planning, and intelligence workflows. These developments indicate that buyers prefer scalable platforms capable of operating across classification levels and coalitions, enabling data access and supporting modular application ecosystems instead of isolated point tools. Consequently, the artificial intelligence and analytics in defense market is balancing initial investments in computing and sensors with recurring service contracts for deployment, accreditation, and updates management.

Service expansion in the defense sector is influenced by accreditation requirements and sustainment challenges, including Authority to Operate, adherence to cybersecurity standards, and integration with existing legacy networks, which collectively contribute to recurring scope adjustments. Department policy also encourages automation in logistics and maintenance, which increases the need for model operations, data engineering, and user training across large organizations. Over the forecast, primes and IT integrators are expected to deepen partnerships with autonomy software firms to accelerate fielding and share compliance burdens, an arrangement that fits long-term sustainment contracts as AI permeates mission threads. The artificial intelligence and analytics in defense industry is also adding DevSecOps practices adapted for classified environments, which standardize delivery pipelines and speed patching without undermining security. In this context, services capture the integration premium as data volumes grow and as mission owners demand continuous model retraining that responds to adversary adaptation.

Land systems held the leading 2025 share at 43.55%, while airborne platforms recorded the highest projected growth at 15.85% CAGR through 2031 as autonomy matured in collaborative combat aircraft programs and attritable drones scaled into operational use. Demonstrations of platform-agnostic autonomy and mid-flight software handoff across different control architectures showed that software portability is improving, reducing vendor lock-in and encouraging multi-vendor fleets. Maritime autonomy is also advancing with multi-hundred-million-dollar awards for unmanned surface vessels (USVs) that emphasize modular payloads and persistent surveillance, a sign that navies are building complementary fleets of crewed and uncrewed assets. These platform trends confirm that autonomy is moving beyond isolated pilots into sustained programs where open interfaces and mission software agility are key evaluation factors.

Airborne momentum reflects operational advantages, including rapid deployment, modular payload swaps, and software updates that can be fielded without structural retrofits. Land systems remain central because of volume and mission diversity, from logistics to electronic warfare (EW) and counter-mine roles that scale across brigades. Naval programs are setting the stage for mixed-crewed architectures that exploit uncrewed endurance and risk tolerance in mine countermeasures (MCM), anti-submarine warfare (ASuW), and coastal defense. As programs move into production, the market is likely to reward suppliers that prove reliable autonomy at the edge with robust safety cases, telemetry capture, and post-mission analytics packaged for commanders and maintainers. Over the forecast, platform budgets will continue to favor software-defined capabilities, which makes sustained integration and test capacity a competitive advantage.

Geography Analysis

North America held 41.80% of the market share in 2025 due to sustained procurement, enterprise software consolidation, and accredited cloud build-outs across services. Institutional guidance and accredited environments for generative AI are strengthening experimentation and deployment pathways that touch operations, training, and maintenance. Suppliers have secured multi-year awards that standardize data foundations across commands and services, shortening onboarding for new applications and reducing duplication. Maritime autonomy and common operating system initiatives are also driving US naval software standardization, which should simplify cross-platform deployments at sea. These structural choices produce a durable base for further AI investments across the region.

Asia-Pacific is projected to grow at a 15.30% CAGR through 2031, supported by official budgets that emphasize modernization and intelligentization as well as domestic investment in surveillance and border security. India's 2026 defense budget and project pipeline include dozens of AI initiatives and significant deployments along contested borders, a sign that operational demand and industrial capability are converging. China's official 2025 defense budget provides further context on the scale of regional modernization, which reinforces the need for autonomy and multi-sensor analytics across domains. These factors, together, point to increased regional demand for integrators that can deliver edge autonomy and secure analytics within strict sovereignty rules.

Europe is closing its capability gap through a mix of national programs and union-level initiatives, while also advancing governance frameworks that influence data sharing and AI deployment. The European Commission's Data Act establishes data rights and sharing conditions that shape defense software architectures, especially in coalition or transatlantic settings. Several countries are seeding specialized institutions and partnerships for defense AI, including newly created or expanded agencies and cross-industry collaborations. Large national awards that standardize data platforms for defense use, including analytics and decision support, further demonstrate the region's push for sovereign capabilities at scale.

1. Lockheed Martin Corporation
2. Northrop Grumman Corporation
3. RTX Corporation
4. BAE Systems plc
5. THALES Group
6. IBM Corporation
7. General Dynamics Information Technology (General Dynamics Corporation)
8. L3Harris Technologies, Inc.
9. Palantir Technologies Inc.
10. Shield AI
11. Avathon, Inc.
12. Elbit Systems Ltd.
13. Anduril Industries, Inc.
14. Airbus SE
15. Rheinmetall AG
16. QinetiQ Group
17. Atos SE
18. HENSOLDT AG
19. Systematic A/S
20. Dassault Systemes S.E.

Additional Benefits:

• The market estimate (ME) sheet in Excel format
• 3 months of analyst support

TABLE OF CONTENTS

1 INTRODUCTION

• 1.1 Study Assumptions and Market Definition
• 1.2 Scope of the Study

2 RESEARCH METHODOLOGY

3 EXECUTIVE SUMMARY

4 MARKET LANDSCAPE

• 4.1 Market Overview
• 4.2 Market Drivers
  • 4.2.1 Rising defense expenditure on AI-enabled autonomous systems
  • 4.2.2 Exponential growth of real-time battlefield data
  • 4.2.3 Government AI R&D funding initiatives
  • 4.2.4 Need for faster, data-driven decision-making
  • 4.2.5 AI-based predictive maintenance for extended platform life
  • 4.2.6 Growth of synthetic training environments
• 4.3 Market Restraints
  • 4.3.1 High upfront integration costs
  • 4.3.2 Scarcity of defense-qualified AI talent
  • 4.3.3 Ethical and regulatory concerns over lethal autonomy
  • 4.3.4 Data-sovereignty limits on multi-nation model training
• 4.4 Value Chain Analysis
• 4.5 Regulatory Landscape
• 4.6 Technological Outlook
• 4.7 Porter's Five Forces Analysis
  • 4.7.1 Bargaining Power of Suppliers
  • 4.7.2 Bargaining Power of Buyers
  • 4.7.3 Threat of New Entrants
  • 4.7.4 Threat of Substitutes
  • 4.7.5 Intensity of Competitive Rivalry

5 MARKET SIZE AND GROWTH FORECASTS (VALUE)

• 5.1 By Component
  • 5.1.1 Hardware
  • 5.1.2 Software
  • 5.1.3 Services
• 5.2 By Platform
  • 5.2.1 Airborne
    • 5.2.1.1 Combat Aircraft
    • 5.2.1.2 Unmanned Aerial Vehicles (UAVs)
  • 5.2.2 Land
    • 5.2.2.1 Military Fighthing Vehicles
    • 5.2.2.2 Unmanned Ground Vehicles (UGVs)
  • 5.2.3 Naval
    • 5.2.3.1 Ships
    • 5.2.3.2 Submarines
    • 5.2.3.3 Unmanned Marine Vehicles (UMVs)
• 5.3 By Application
  • 5.3.1 Cybersecurity
  • 5.3.2 Battlefield Healthcare
  • 5.3.3 Warfare Platform
  • 5.3.4 Logistics Management
  • 5.3.5 Training and Simulation
  • 5.3.6 Surveillance and Situational Awareness
  • 5.3.7 Others
• 5.4 By Technology
  • 5.4.1 Artificial Intelligence (AI)
  • 5.4.2 Big Data Analytics
  • 5.4.3 Other Technologies
• 5.5 By Geography
  • 5.5.1 North America
    • 5.5.1.1 United States
    • 5.5.1.2 Canada
    • 5.5.1.3 Mexico
  • 5.5.2 Europe
    • 5.5.2.1 United Kingdom
    • 5.5.2.2 France
    • 5.5.2.3 Germany
    • 5.5.2.4 Russia
    • 5.5.2.5 Rest of Europe
  • 5.5.3 Asia-Pacific
    • 5.5.3.1 China
    • 5.5.3.2 India
    • 5.5.3.3 Japan
    • 5.5.3.4 South Korea
    • 5.5.3.5 Rest of Asia-Pacific
  • 5.5.4 South America
    • 5.5.4.1 Brazil
    • 5.5.4.2 Rest of South America
  • 5.5.5 Middle East and Africa
    • 5.5.5.1 Middle East
      • 5.5.5.1.1 Saudi Arabia
      • 5.5.5.1.2 United Arab Emirates
      • 5.5.5.1.3 Israel
      • 5.5.5.1.4 Rest of Middle East
    • 5.5.5.2 Africa
      • 5.5.5.2.1 South Africa
      • 5.5.5.2.2 Rest of Africa

6 COMPETITIVE LANDSCAPE

• 6.1 Strategic Moves
• 6.2 Market Share Analysis
• 6.3 Company Profiles (includes Global Level Overview, Market Level Overview, Core Segments, Financials as aAvailable, Strategic Information, Market Rank/Share for Key Companies, Products and Services, and Recent Developments)
  • 6.3.1 Lockheed Martin Corporation
  • 6.3.2 Northrop Grumman Corporation
  • 6.3.3 RTX Corporation
  • 6.3.4 BAE Systems plc
  • 6.3.5 THALES Group
  • 6.3.6 IBM Corporation
  • 6.3.7 General Dynamics Information Technology (General Dynamics Corporation)
  • 6.3.8 L3Harris Technologies, Inc.
  • 6.3.9 Palantir Technologies Inc.
  • 6.3.10 Shield AI
  • 6.3.11 Avathon, Inc.
  • 6.3.12 Elbit Systems Ltd.
  • 6.3.13 Anduril Industries, Inc.
  • 6.3.14 Airbus SE
  • 6.3.15 Rheinmetall AG
  • 6.3.16 QinetiQ Group
  • 6.3.17 Atos SE
  • 6.3.18 HENSOLDT AG
  • 6.3.19 Systematic A/S
  • 6.3.20 Dassault Systemes S.E.

7 MARKET OPPORTUNITIES AND FUTURE OUTLOOK

• 7.1 White-space and Unmet-Need Assessment