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AI and Analytics in Military and Defense Market, Opportunity, Growth Drivers, Industry Trend Analysis and Forecast, 2025-2034

Publisher Global Market Insights
Published Jan 08, 2026
Length 238 Pages
SKU # GMI20836560

Description

The Global AI & Analytics in Military and Defense Market was valued at USD 10.4 billion in 2024 and is estimated to grow at a CAGR of 13.4% to reach USD 35.7 billion by 2034.

Market growth is driven by the increasing need for data-driven decision-making, real-time battlefield intelligence, and enhanced situational awareness across defense operations. Armed forces worldwide are rapidly integrating artificial intelligence and advanced analytics into command, control, intelligence, surveillance, and reconnaissance (C4ISR) systems to process massive volumes of structured and unstructured data. AI-enabled analytics significantly improve threat detection, predictive maintenance, mission planning, and autonomous system performance. The growing complexity of modern warfare, coupled with asymmetric threats and cyber vulnerabilities, is accelerating investments in AI-powered defense platforms to enhance operational efficiency, reduce human error, and enable faster response times across land, air, sea, space, and cyber domains.

The software segment generated USD 3.6 billion in 2024. Defense organizations increasingly rely on AI-driven software platforms for data fusion, pattern recognition, predictive analytics, and real-time intelligence processing. These software solutions support mission-critical applications such as battlefield management systems, intelligence analysis platforms, and autonomous mission control. Continuous advancements in machine learning algorithms, deep learning models, and edge AI architectures are enhancing the accuracy, scalability, and adaptability of defense analytics software.

The land segment reached USD 4.4 billion in 2024, driven by the increasing deployment of AI-enabled systems across ground-based military operations. Land forces rely heavily on advanced analytics for battlefield management, threat assessment, logistics optimization, and predictive maintenance of armored vehicles and artillery systems. AI-powered platforms enhance situational awareness by integrating data from ground sensors, surveillance radars, unmanned ground vehicles, and soldier-worn systems, enabling commanders to make faster and more informed decisions in complex combat environments.

North America AI & Analytics in Military and Defense Market garnered USD 3.9 billion in 2024, driven by substantial defense budgets, early adoption of advanced digital technologies, and strong investments in AI-enabled warfare systems. The region benefits from robust collaboration between defense agencies, technology providers, and research institutions focused on next-generation military capabilities. The U.S. Department of Defense’s emphasis on Joint All-Domain Command and Control (JADC2), autonomous systems, and AI-driven decision support platforms continues to accelerate market growth. North America’s dominance is also supported by the presence of leading defense contractors and AI solution providers actively developing scalable, secure, and mission-ready analytics solutions tailored to complex defense environments.

Key players operating in the AI & Analytics in Military and Defense Market include Lockheed Martin Corporation, Northrop Grumman, Raytheon Technologies, Thales Group, BAE Systems, Palantir Technologies, IBM Corporation, General Dynamics, L3Harris Technologies, and Leidos Holdings. Companies operating in the AI & Analytics in Military and Defense Market are focusing on long-term defense contracts, platform modernization, and secure AI innovation to strengthen their market foothold. Leading players are heavily investing in defense-grade AI software capable of operating in contested, data-denied, and cyber-threat environments. Strategic partnerships with defense ministries, research organizations, and allied governments help accelerate technology validation and deployment. Firms are also prioritizing modular and scalable AI architectures that integrate seamlessly with legacy defense systems while supporting future upgrades.

Table of Contents

238 Pages
Chapter 1: Methodology
1.1. Definitions
1.2. Research Design
1.2.1. Research approach
1.2.2. Data collection methods
1.3. Base estimates and calculations
1.3.1. Base year calculation
1.3.2. Key trends for market estimates
1.4. Forecast model
1.5. Primary research & validation
1.5.1. Some of the primary sources (but not limited to):
1.5.2. Inputs from primary interviews:
1.6. Data Mining Sources
1.6.1. Secondary Sources
1.6.1.1. Paid Sources
1.6.1.2. Public Sources
1.7. Sources, by region
Chapter 2: Executive Summary
2.1. Industry 360° synopsis
2.2. Key market trends
2.2.1. Business trends
2.2.2. Offering trends
2.2.3. Installation type trends
2.2.4. Technology trends
2.2.5. Application trends
2.2.6. Platform trends
2.2.7. Regional trends
2.3. TAM Analysis, 2025-2034 (USD Million)
2.4. CXO perspectives: Strategic imperatives
2.4.1. Executive decision points
2.4.2. Critical Success Factors
2.5. Future Outlook and Strategic Recommendations
Chapter 3: Industry Insights
3.1. Industry snapshot
3.1.1. Component Manufactures
3.1.2. Technology Providers
3.1.3. Platform Developers & System integration
3.1.4. Application
3.1.1. Supplier Landscape
3.1.2. Profit Margin
3.1.3. Cost structure
3.1.4. Value addition at each stage
3.1.5. Factor affecting the value chain
3.1.6. Disruptions
3.2. Industry impact forces
3.2.1. Market growth drivers
3.2.1.1. The improvement in autonomous systems advancement
3.2.1.2. Increasing emphasis on cybersecurity enhancement
3.2.1.3. Rising demand for real-time decision-making, that elevate AI analytics platforms
3.2.1.4. Growing integration of AI in multi-domain operations to coordinate land, sea, air, space, and cyber missions at machine speed
3.2.1.5. Increasing government spending
3.2.2. Restraints and challenges
3.2.2.1. High implementation costs.
3.2.2.2. Data security and privacy concerns.
3.2.3. Market opportunities
3.2.3.1. Expansion of multi-domain autonomous operations
3.2.3.2. Strengthening Cybersecurity and Intelligence Capabilities
3.3. Growth Potential
3.4. Regulatory Landscape
3.5. Porter’s Analysis
3.6. PESTEL Analysis
3.7. Technology and Innovation Landscape
3.7.1. Current Technological Trends
3.7.2. Emerging Technologies
3.8. Emerging Business Models
3.9. Compliance Requirements
3.10. Defense Budget Analysis
3.11. Global Defense Spending Trends
3.12. Regional Defense Budget Allocation
3.12.1. North America
3.12.2. Europe
3.12.3. Asia Pacific
3.12.4. Middle East and Africa
3.12.5. Latin America
3.13. Key Defense Modernization Programs
3.14. Budget Forecast (2025–2034)
3.14.1. Impact on Industry Growth
3.14.2. Defense Budgets by Country
3.15. Supply Chain Resilience
3.16. Geopolitical Analysis
3.17. Workforce Analysis
3.18. Digital Transformation
3.19. Mergers, acquisitions, and strategic partnerships landscape
3.20. Risk Assessment and Management
3.21. Major Contract Awards (2021–2024)
Chapter 4: Competitive Landscape, 2024
4.1. Competitive Landscape
4.2. Company market share analysis, 2024
4.2.1. Market Concentration Analysis
4.3. Competitive analysis of the key market players
4.3.1. Financial Performance Comparison
4.3.1.1. Revenue
4.3.1.2. Profit Margin
4.3.1.3. R&D
4.3.2. Product Portfolio Comparison
4.3.2.1. Product Range Breadth
4.3.2.1. Technology
4.3.2.2. Innovation
4.3.3. Geographic Presence Comparison
4.3.3.1. Global Footprint Analysis
4.3.3.2. Service Network Coverage
4.3.3.3. Market Penetration by Region
4.4. Strategic Initiative
4.4.1. L3Harris Technologies
4.4.2. Lockheed Martin Corporation
4.4.3. Palantir Technologies
4.4.4. Northrop Grumman Corporation
4.4.5. BAE Systems plc
4.4.6. Boeing
4.4.7. IBM Corporation
4.4.8. Safran
4.5. Competitive Positioning Matrix
4.6. Strategic Outlook Matrix
Chapter 5: AI and Analytics in Military & Defence, By Offering
5.1. Offering Key Trends
5.2. Hardware
5.3. Software
5.3.1. Cloud
5.3.2. On-premise
5.4. Service
5.4.1. Deployment & Integration
5.4.2. Upgrades & Maintenance
5.4.3. Software Support
5.4.4. Others
Chapter 6: AI and Analytics in Military & Defence, By Installation Type
6.1. Installation Type Key Trends
6.2. New Installation
6.3. Upgradation
Chapter 7: AI and Analytics in Military & Defence, By Technology
7.1. Technology Key Trends
7.2. Machine learning
7.3. Natural language processing
7.4. Context-aware computing
7.5. Computer vision
7.6. Intelligent virtual agent (Iva) /virtual agents
7.7. Others
Chapter 8: AI and Analytics in Military & Defence, By Application
8.1. Application Key Trends
8.2. Warfare platforms
8.3. Cybersecurity
8.4. Logistics & transportation
8.5. Surveillance & situational awareness
8.6. Command & control
8.7. Battlefield healthcare
8.8. Simulation & training
8.9. Threat detection
8.10. Information processing
8.11. Information processing
Chapter 9: AI and Analytics in Military & Defence, By Platform
9.1. Platform Key Trends
9.2. Airborne
9.2.1. Fighter Aircaft
9.2.2. Special mission aircraft
9.2.3. Helicopters
9.2.4. Unmanned aerial vehicles (UAV)
9.3. Land
9.3.1. Military fighting vehicles (MFV)
9.3.2. Unmanned ground vehicles (UGV)
9.3.3. Weapons systems
9.3.4. Headquarter & command centers
9.3.5. Dismounted Soldier Systems
9.4. Naval
9.4.1. Ships
9.4.2. Submarines
9.4.3. Unmanned marine vehicles (UMVs)
9.5. Space
9.5.1. CubeSats
9.5.2. Satellites
Chapter 10: AI and Analytics in Military & Defence, By Region
10.1. Regional Key Trends
10.2. North America
10.3. Europe
10.4. Asia Pacific
10.5. Latin America
10.6. Middle East & Africa (MEA)
Chapter 11: Company Profile
11.1. Global Key Players
11.1.1. Lockheed Martin Corporation
11.1.1.1.Financial Data
11.1.1.2.Product Landscape
11.1.1.3.Strategic Outlook
11.1.1.4.SWOT Analysis
11.1.2. Raytheon Technologies (RTX)
11.1.2.1.Financial Data
11.1.2.2.Product Landscape
11.1.2.3.Strategic Outlook
11.1.2.4.SWOT Analysis
11.1.3. Northrop Grumman Corporation
11.1.3.1.Financial Data
11.1.3.2.Product Landscape
11.1.3.3.Strategic Outlook
11.1.3.4.SWOT Analysis
11.2. Regional Key Players
11.2.1. North America
11.2.1.1.General Dynamics
11.2.1.1.1. Financial Data
11.2.1.1.2. Product Landscape
11.2.1.1.3. SWOT Analysis
11.2.1.2.Boeing
11.2.1.2.1. Financial Data
11.2.1.2.2. Product Landscape
11.2.1.2.3. Strategic Outlook
11.2.1.2.4. SWOT Analysis
11.2.1.3.L3Harris Technologies Inc.
11.2.1.3.1. Financial Data
11.2.1.3.2. Product Landscape
11.2.1.3.3. Strategic Outlook
11.2.1.3.4. SWOT Analysis
11.2.2. Europe
11.2.2.1.BAE Systems
11.2.2.1.1. Financial Data
11.2.2.1.2. Product Landscape
11.2.2.1.3. Strategic Outlook
11.2.2.1.4. SWOT Analysis
11.2.2.2.Thales
11.2.2.2.1. Financial Data
11.2.2.2.2. Product Landscape
11.2.2.2.3. SWOT Analysis
11.2.2.3.Rheinmetall AG
11.2.2.3.1. Financial Data
11.2.2.3.2. Product Landscape
11.2.2.3.3. Strategic Outlook
11.2.2.3.4. SWOT Analysis
11.2.3. Asia Pacific
11.2.3.1.Safran
11.2.3.1.1. Financial Data
11.2.3.1.2. Product Landscape
11.2.3.1.3. Strategic Outlook
11.2.3.1.4. SWOT Analysis
11.2.3.2.Rafael Advanced Defense Systems
11.2.3.2.1. Financial Data
11.2.3.2.2. Product Landscape
11.2.3.2.3. Strategic Outlook
11.2.3.2.4. SWOT Analysis
11.3. Niche Player
11.3.1. IBM Corporation
11.3.1.1.Financial Data
11.3.1.2.Product Landscape
11.3.1.3.Strategic Outlook
11.3.1.4.SWOT Analysis
11.3.2. Palantir Technologies
11.3.2.1.Financial Data
11.3.2.2.Product Landscape
11.3.2.3.Strategic Outlook
11.3.2.4.SWOT Analysis
11.3.3. Charles River Analytics
11.3.3.1.Financial Data
11.3.3.2.Product Landscape
11.3.3.3.SWOT Analysis
11.3.4. SparkCognition (Avathon)
11.3.4.1.Financial Data
11.3.4.2.Product Landscape
11.3.4.3.SWOT Analysis
11.3.5. Leidos
11.3.5.1.Financial Data
11.3.5.2.Product Landscape
11.3.5.3.Strategic Outlook
11.3.5.4.SWOT Analysis
11.3.6. Anduril Industries
11.3.6.1.Financial Data
11.3.6.2.Product Landscape
11.3.6.3.SWOT Analysis
11.3.7. Shield AI
11.3.7.1.Financial Data
11.3.7.2.Product Landscape
11.3.7.3.Strategic Outlook
11.3.7.4.SWOT Analysis
11.3.8. Helsing
11.3.8.1.Financial Data
11.3.8.2.Product Landscape
11.3.8.3.SWOT Analysis
11.3.9. Booz Allen Hamilton
11.3.9.1.Financial Data
11.3.9.2.Product Landscape
11.3.9.3.SWOT Analysis
Chapter 12: Appendix
12.1. Market Definitions

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