This report analyzes the key theme of artificial intelligence (AI) in the defense sector. AI is taking on greater importance as defense companies navigate the advances being made in this technological field. This report provides an insight into key trends, challenges, and recommendations, as well as providing concrete case studies to help the reader see examples of AI in action.
According to the analyst forecasts, the total AI market, including software, hardware, and services, will be worth $1 trillion by 2030, having grown at a CAGR of 39% from $103 billion in 2023.
Militaries developing increasingly advanced algorithms are presented with specific challenges. Policymakers are having difficulty tackling the ethical concerns surround lethal autonomous weapons (LAWs) and their capacities to identify, target, and eliminate perceived hostile entities. Target misidentification is a prominent concern amongst lawmakers and activists. Furthermore, the lack of clear legal parameters raises further questions about using AI in an offensive military context, as it is currently unclear how responsibility and accountability apply to AI-enabled defense systems.
Operation and maintenance (O&M) costs are a series expenditure for militaries, accounting for 39% of the US Department of Defense's 2024 budget. AI can predict when assets will need maintenance, allowing for work to be done proactively, reducing downtime and improving the cost-effectiveness of each asset.
Training can also become more cost-effective by incorporating AI. It can be used to create realistic virtual scenarios that are easily adaptable and repeatable and require less space and fewer personnel to accomplish. Though not a complete substitute for live training, virtual training can help refine skills and save governmental departments money in the process.
According to the analyst forecasts, the total AI market, including software, hardware, and services, will be worth $1 trillion by 2030, having grown at a CAGR of 39% from $103 billion in 2023.
Militaries developing increasingly advanced algorithms are presented with specific challenges. Policymakers are having difficulty tackling the ethical concerns surround lethal autonomous weapons (LAWs) and their capacities to identify, target, and eliminate perceived hostile entities. Target misidentification is a prominent concern amongst lawmakers and activists. Furthermore, the lack of clear legal parameters raises further questions about using AI in an offensive military context, as it is currently unclear how responsibility and accountability apply to AI-enabled defense systems.
Operation and maintenance (O&M) costs are a series expenditure for militaries, accounting for 39% of the US Department of Defense's 2024 budget. AI can predict when assets will need maintenance, allowing for work to be done proactively, reducing downtime and improving the cost-effectiveness of each asset.
Training can also become more cost-effective by incorporating AI. It can be used to create realistic virtual scenarios that are easily adaptable and repeatable and require less space and fewer personnel to accomplish. Though not a complete substitute for live training, virtual training can help refine skills and save governmental departments money in the process.
Scope
- This report analyzes the key theme of AI in the defense sector.
- This report provides an insight into key trends, challenges, and recommendations, as well as providing case studies to help the reader see examples of AI in action.
Reasons to Buy
- Understand the impact of AI on the defense industry, using case studies to help you understand how you can adapt and understand this theme.
- Assess the strategies that companies are adopting to succeed in AI.
- Discover companies that are leading in the space.
- Analyze real-world trends created by integrating AI across the defense sector.
- The analyst’s thematic research ecosystem is a single, integrated global research platform that provides an easy-to-use framework for tracking all themes across all companies in all sectors. It has a proven track record of identifying the important themes early, enabling companies to make the right investments ahead of the competition, and secure that all-important competitive advantage.
Table of Contents
1. Executive Summary
2. Players
3. Value Chain
4. The Impact of AI on Defense
5. Case Studies
6. Market Size and Growth Forecasts
7. AI Timeline
8. Signals
9. Companies
10. Sector Scorecard
11. Glossary
12. Further Reading
13. Thematic Research Methodology
14. About the Analyst
15. Contact the Publisher
List of Tables
- The key M&A transactions associated with the AI theme since January 2022
- Companies - Leading AI adopters in defense
- Companies - Specialist AI vendors in defense
List of Figures
- Key players in advanced AI capabilities
- The artificial intelligence value chain
- There are five categories of advanced AI capabilities
- AI should be integrated into all segments of the defense value chain
- Kraken K4 Manta USSV with a BlueHalo IEV3 drone
- The global market for specialized AI applications will be worth $512 billion by 2030
- The global specialized AI applications market will grow at a CAGR of 44%
- North America and Asia Pacific are the leading AI markets
- The AI story
- Mentions of AI are increasing across the entire aerospace and defense sector
- Mentions of AI are increasing among the largest aerospace and defense companies
- AI, like other technology fields, is a volatile hiring environment
Companies Mentioned (Partial List)
A selection of companies mentioned in this report includes, but is not limited to:
- BAE Systems
- Boeing
- Elbit Systems
- IAI
- L3Harris Technologies
- Lockheed Martin
- Northrup Grumman
- Rafael
- RTX
- Anduril
- BlueHalo
- Percepto
- Shield AI
- Veloxiti
- Leidos
- Adarga
- Cylance
- Palantir
- Rebellion Defense
- SparkCognition
- NASA
- Red6
- Atlas Elektronik
- Autodesk
- FLIR Systems
- Hadean
- Alibaba
- Alpha MOS
- Amazon
- Apple
- Aryballe
- Baidu
- Generic Robotics
- IBM
- iFlytek
- Kernel
- Mevii (Face++)
- Merative
- Meta
- Microsoft
- Mobileye
- Neuralink
- Nvidia
- Odometric
- Paradromics
- Sanctuary AI
- SenseTime
- Synchron
- Tastewise
- Tencent
- ABB
- Alphabet (Google
- Waymo)
- Aurora
- Basler
- Cognex
- GM (Cruise)
- Hyundai (Boston Dynamics)
- Keyence
- Midea (KUKA)
- Motional
- Oracle
- Pony.ai
- SAS
- Teradyne
- Tesla
- Thales Group
- Festo
- Omron
- Robotiq
- iRobot
- Aifnet (Deep Dream)
- Aiva Technologies
- Amadeus Code
- Anthropic
- Artbreeder
- Auiocipher
- Big Sleep
- Boomy
- Cohere
- DeepAI
- Ecrett Music
- Hugging Face
- Jasper Art
- Midjourney
- Mistral AI
- NightCafe
- OpenAI
- Output
- Shutterstock (Amper)
- Stability.ai
- StarryAI
- WOMBO (Dream)
