Artificial Intelligence In Military Market Size & Trend Report, 2023-2032
The global artificial intelligence in military market size was exhibited at USD 8.1 billion in 2022 and is projected to hit around USD 23.12 billion by 2032, growing at a CAGR of 11.06% during the forecast period 2023 to 2032.
Key Pointers:
The growth of the market for Artificial Intelligence in the Military Sector can be attributed to the increasing investment in the development of AI-integrated systems and the rising adoption of cloud-based applications and high-performance computers. However, protectionist policies and lack of standard protocols, leading to limited access to military platforms, are acting as a restraint to the growth of this market.
Artificial Intelligence In Military Market Report Scope
|
Report Coverage |
Details |
|
Market Size in 2023 |
USD 9 Billion |
|
Market Size by 2032 |
USD 23.12 Billion |
|
Growth Rate From 2023 to 2032 |
CAGR of 11.06% |
|
Base Year |
2022 |
|
Forecast Period |
2023 to 2032 |
|
Segments Covered |
By Component, By Technology, By Platform, By Installation, and By Application |
|
Market Analysis (Terms Used) |
Value (US$ Million/Billion) or (Volume/Units) |
|
Regional Scope |
North America; Europe; Asia Pacific; Central and South America; the Middle East and Africa |
|
Key Companies Profiled |
Machine Halo, Lockheed Martin, Northrop Grumman, Raytheon Company, Thales Group, Bae Systems, IBM, General Dynamics, Soartech, Nvidia, Sparkcognition, Saic, Charles River Analytics, Leidos, Boeing, GovBrain, and others. |
COVID-19 Impact on the AI in Military Market
Even though the COVID-19 pandemic has caused a large-scale impact on economies across the world, leading to many challenges, the Artificial Intelligence in military market has continued to expand. This can be seen from both, the demand and supply sides, as leading manufacturers like Lockheed Martin (US), IBM (US), Northrop Grumman (US), and others continue to invest heavily in developing AI capabilities, and governments continue to invest significantly in securing these systems. This can be attributed to governments realizing the potential of improved capabilities that these AI systems offer in terms of defense arsenal as the global AI arms race tightens.
However, even though the development of AI technology witnessed expansion, the overall building of the AI systems saw a hit. This was a result of the shortage of raw materials due to disruptions in the supply chain. Resuming manufacturing and demand depends on the level of COVID-19 exposure a country is facing, the level at which manufacturing operations are running, and import-export regulations, among other factors. Although companies may still be taking in orders, delivery schedules might not be fixed.
AI in Military warfare Market Dynamics
AI in Military Market Driver: Increased Government Spending on Defense to Improve AI Capabilities
According to Stockholm International Peace Research Institute (SIPRI), the global military expenditure in 2022 was estimated at USD 2017 billion, an increase of 3.9% as compared to the 2019 spending. This can be due to the rise in conflicts between countries, leading to the strengthening of their defense forces. For instance, 2020 witnessed over nine major international conflicts, including the Syrian Civil War, the Saudi Arabia-Yemen conflict, US-Iran tensions, and India-China tensions.
Such conflicts result in increased procurement of advanced AI-enabled weapon systems and the incorporation of newer technologies into existing systems to make them more efficient.
Many governments have established special departments or agencies dedicated to planning, initiating, and integrating AI capabilities into the existing equipment as well as developing new capabilities. The National Science and Technology Council (US), the Strategic Council for AI Technologies (Japan), and the AI Council (UK) are some such agencies. For instance, in January 2021, the UK AI Council presented a roadmap to the UK Government recommending it to scale up and make sustainable public sector investment in AI and also invest in The Alan Turing Institute (UK), fostering development to gain a strategic leadership for the UK in AI research.
The UK Government’s Research & Development Roadmap of July 2020 also includes similar projects. This report states that the Defence and Security Accelerator (DASA) is working closely with the Institute for Security Science and Technology (ISST) at Imperial’s White City Campus (UK) to bring together government, academia, industry, and small & medium-sized enterprises (SMEs) to look at developing the next generation of solutions for security and defense problems.
AI in Military Market Restraints: Concerns Over Possibility of Errors in Complex Combat Situations
With various governments adopting AI-powered systems for surveillance and automation, concerns are being raised, stating that human control over robots is necessary to ensure control and humanitarian protection. There is also concern among humanitarian organizations like Human Rights Watch regarding whether governments are secretly developing “Automated Killer Robots” to top the AI arms race. This compels governments to publicly declare their current capabilities and refrain from developing autonomous weapons and fully automated robots, as these will be incapable of meeting the standards of International Humanitarian Law.
Additionally, the possibility of errors is also high with AI systems. Since they make quick decisions, they may not be able to adapt to the inevitable complexities of war. As a result, these systems might not accurately distinguish between combatants and non-combatants or threats and system anomalies and ultimately be less accurate and precise than human operators. These problems could be magnified if systems are fielded before being adequately tested or if adversaries succeed in spoofing or hacking into them. These concerns are restraining market growth.
Artificial Intelligence in Military Market Opportunitie: Incorporation of Quantum Computing in AI
A quantum computer works on phenomena such as “superposition” and “entanglement.” Through these computational advantages, a quantum computer can outperform any modern classical computer. For instance, Google recently reported that it developed a quantum processor, “Sycamore,” that has demonstrated the ability to solve a complex mathematical problem in 200 seconds, while the same results will only be obtained in 10,000 years using the most advanced supercomputer available today.
This power of quantum computing can also be introduced in AI systems. This will supercharge the AI systems that now depend on binary-based classical computing and enhance their capabilities. For instance, AI can crunch through a larger data set and learn from it to give a better model and, thus, more accurate predictions. This can have various applications in the defense industry for security and privacy. Having the ability to process larger datasets, the information can be processed much quicker locally rather than depending on the cloud. For instance, data from all sensors attached in an autonomous Ai-powered tank can be processed quickly and decisions can be made faster. Quantum computing will play a huge role in cybersecurity, as this will power up the systems for faster detection of threats and take necessary countermeasures. This presents significant opportunities for the Artificial Intelligence in military market.
AI in Military Market Challenges: Absence of Backward Analysis
Research in artificial intelligence and machine learning has led to the development of advanced applications with the ability to perceive, learn, decide, and act of their own accord. To fully exploit their capabilities, it is vital to understand how the applications arrived at a certain conclusion. In other words, an AI system should explain why it has taken certain decisions or actions. Current AI technologies lack in this. Hence, the development of systems that can explain their rationale is underway under the Explainable AI (XAI) program of the Defense Advanced Research Projects Agency (DARPA) by companies such as Raytheon and Charles River Analytics. However, it may be a while before such systems are fully developed and functional. Thus, the current inability to completely predict and ascertain the reasoning that AI uses to arrive at a conclusion poses risks to military applications and thus serves as a challenge to the market.
Increasing Threats of Cyber Attacks is Driving the Growth of the Defense Applications That Leverages AI
The defense industry across countries is constantly under threat of cyberattacks. For instance, in September 2022, SolarWinds, a US technology company, was hacked, revealing sensitive data of many hospitals, universities, and US government agencies. Another notable incident was in October 2020, when the FBI and the US Cyber Command announced that a North Korean group had hacked think tanks, individual experts, and government entities of the US, Japan, and South Korea to illegally obtain intelligence, including that on nuclear policies.
Current cybersecurity technology falls short in terms of tackling advanced ransomware and spyware threats. The above mentioned SolarWinds hack was revealed when FireEye, a cybersecurity provider, was probing one of its own hacks. Such incidents indicate the increasing importance of having advanced cybersecurity capabilities. Artificial intelligence-based cybersecurity solutions that can be trained to independently gather data from various sources, analyze the data, correlate it to the signals indicating cyberattacks, and take relevant actions, can be deployed.
Some of the prominent players in the Artificial Intelligence In Military Market include:
Segments Covered in the Report
This report forecasts revenue growth at global, regional, and country levels and provides an analysis of the latest industry trends in each of the sub-segments from 2018 to 2032. For this study, Nova one advisor, Inc. has segmented the global Artificial Intelligence In Military market.
By Component
By Technology
By Platform
By Installation
By Application
By Region
Chapter 1. Introduction
1.1. Research Objective
1.2. Scope of the Study
1.3. Definition
Chapter 2. Research Methodology
2.1. Research Approach
2.2. Data Sources
2.3. Assumptions & Limitations
Chapter 3. Executive Summary
3.1. Market Snapshot
Chapter 4. Market Variables and Scope
4.1. Introduction
4.2. Market Classification and Scope
4.3. Industry Value Chain Analysis
4.3.1. Raw Material Procurement Analysis
4.3.2. Sales and Distribution Channel Analysis
4.3.3. Downstream Buyer Analysis
Chapter 5. COVID 19 Impact on Artificial Intelligence In Military Market
5.1. COVID-19 Landscape: Artificial Intelligence In Military Industry Impact
5.2. COVID 19 - Impact Assessment for the Industry
5.3. COVID 19 Impact: Global Major Government Policy
5.4. Market Trends and Opportunities in the COVID-19 Landscape
Chapter 6. Market Dynamics Analysis and Trends
6.1. Market Dynamics
6.1.1. Market Drivers
6.1.2. Market Restraints
6.1.3. Market Opportunities
6.2. Porter’s Five Forces Analysis
6.2.1. Bargaining power of suppliers
6.2.2. Bargaining power of buyers
6.2.3. Threat of substitute
6.2.4. Threat of new entrants
6.2.5. Degree of competition
Chapter 7. Competitive Landscape
7.1.1. Company Market Share/Positioning Analysis
7.1.2. Key Strategies Adopted by Players
7.1.3. Vendor Landscape
7.1.3.1. List of Suppliers
7.1.3.2. List of Buyers
Chapter 8. Global Artificial Intelligence In Military Market, By Component
8.1. Artificial Intelligence In Military Market, by Component, 2023-2032
8.1.1. Hardware
8.1.1.1. Market Revenue and Forecast (2020-2032)
8.1.2. Software
8.1.2.1. Market Revenue and Forecast (2020-2032)
8.1.3. Services
8.1.3.1. Market Revenue and Forecast (2020-2032)
Chapter 9. Global Artificial Intelligence In Military Market, By Technology
9.1. Artificial Intelligence In Military Market, by Technology, 2023-2032
9.1.1. Advanced Computing
9.1.1.1. Market Revenue and Forecast (2020-2032)
9.1.2. Ai Systems
9.1.2.1. Market Revenue and Forecast (2020-2032)
9.1.3. Learning and Intelligence
9.1.3.1. Market Revenue and Forecast (2020-2032)
Chapter 10. Global Artificial Intelligence In Military Market, By Platform
10.1. Artificial Intelligence In Military Market, by Platform, 2023-2032
10.1.1. Airborne
10.1.1.1. Market Revenue and Forecast (2020-2032)
10.1.2. Land
10.1.2.1. Market Revenue and Forecast (2020-2032)
10.1.3. Naval
10.1.3.1. Market Revenue and Forecast (2020-2032)
10.1.4. Space
10.1.4.1. Market Revenue and Forecast (2020-2032)
Chapter 11. Global Artificial Intelligence In Military Market, By Installation
11.1. Artificial Intelligence In Military Market, by Installation, 2023-2032
11.1.1. New Procurement
11.1.1.1. Market Revenue and Forecast (2020-2032)
11.1.2. Upgrade
11.1.2.1. Market Revenue and Forecast (2020-2032)
Chapter 12. Global Artificial Intelligence In Military Market, By Application
12.1. Artificial Intelligence In Military Market, by Application, 2023-2032
12.1.1. Cyber Security
12.1.1.1. Market Revenue and Forecast (2020-2032)
12.1.2. Battlefield Healthcare
12.1.2.1. Market Revenue and Forecast (2020-2032)
12.1.3. Logistics and Transportation
12.1.3.1. Market Revenue and Forecast (2020-2032)
12.1.4. Information Processing
12.1.4.1. Market Revenue and Forecast (2020-2032)
12.1.5. Warfare Platform
12.1.5.1. Market Revenue and Forecast (2020-2032)
Chapter 13. Global Artificial Intelligence In Military Market, Regional Estimates and Trend Forecast
13.1. North America
13.1.1. Market Revenue and Forecast, by Component (2020-2032)
13.1.2. Market Revenue and Forecast, by Technology (2020-2032)
13.1.3. Market Revenue and Forecast, by Platform (2020-2032)
13.1.4. Market Revenue and Forecast, by Installation (2020-2032)
13.1.5. Market Revenue and Forecast, by Application (2020-2032)
13.1.6. U.S.
13.1.6.1. Market Revenue and Forecast, by Component (2020-2032)
13.1.6.2. Market Revenue and Forecast, by Technology (2020-2032)
13.1.6.3. Market Revenue and Forecast, by Platform (2020-2032)
13.1.6.4. Market Revenue and Forecast, by Installation (2020-2032)
13.1.6.5. Market Revenue and Forecast, by Application (2020-2032)
13.1.7. Rest of North America
13.1.7.1. Market Revenue and Forecast, by Component (2020-2032)
13.1.7.2. Market Revenue and Forecast, by Technology (2020-2032)
13.1.7.3. Market Revenue and Forecast, by Platform (2020-2032)
13.1.7.4. Market Revenue and Forecast, by Installation (2020-2032)
13.1.7.5. Market Revenue and Forecast, by Application (2020-2032)
13.2. Europe
13.2.1. Market Revenue and Forecast, by Component (2020-2032)
13.2.2. Market Revenue and Forecast, by Technology (2020-2032)
13.2.3. Market Revenue and Forecast, by Platform (2020-2032)
13.2.4. Market Revenue and Forecast, by Installation (2020-2032)
13.2.5. Market Revenue and Forecast, by Application (2020-2032)
13.2.6. UK
13.2.6.1. Market Revenue and Forecast, by Component (2020-2032)
13.2.6.2. Market Revenue and Forecast, by Technology (2020-2032)
13.2.6.3. Market Revenue and Forecast, by Platform (2020-2032)
13.2.7. Market Revenue and Forecast, by Installation (2020-2032)
13.2.8. Market Revenue and Forecast, by Application (2020-2032)
13.2.9. Germany
13.2.9.1. Market Revenue and Forecast, by Component (2020-2032)
13.2.9.2. Market Revenue and Forecast, by Technology (2020-2032)
13.2.9.3. Market Revenue and Forecast, by Platform (2020-2032)
13.2.10. Market Revenue and Forecast, by Installation (2020-2032)
13.2.11. Market Revenue and Forecast, by Application (2020-2032)
13.2.12. France
13.2.12.1. Market Revenue and Forecast, by Component (2020-2032)
13.2.12.2. Market Revenue and Forecast, by Technology (2020-2032)
13.2.12.3. Market Revenue and Forecast, by Platform (2020-2032)
13.2.12.4. Market Revenue and Forecast, by Installation (2020-2032)
13.2.13. Market Revenue and Forecast, by Application (2020-2032)
13.2.14. Rest of Europe
13.2.14.1. Market Revenue and Forecast, by Component (2020-2032)
13.2.14.2. Market Revenue and Forecast, by Technology (2020-2032)
13.2.14.3. Market Revenue and Forecast, by Platform (2020-2032)
13.2.14.4. Market Revenue and Forecast, by Installation (2020-2032)
13.2.15. Market Revenue and Forecast, by Application (2020-2032)
13.3. APAC
13.3.1. Market Revenue and Forecast, by Component (2020-2032)
13.3.2. Market Revenue and Forecast, by Technology (2020-2032)
13.3.3. Market Revenue and Forecast, by Platform (2020-2032)
13.3.4. Market Revenue and Forecast, by Installation (2020-2032)
13.3.5. Market Revenue and Forecast, by Application (2020-2032)
13.3.6. India
13.3.6.1. Market Revenue and Forecast, by Component (2020-2032)
13.3.6.2. Market Revenue and Forecast, by Technology (2020-2032)
13.3.6.3. Market Revenue and Forecast, by Platform (2020-2032)
13.3.6.4. Market Revenue and Forecast, by Installation (2020-2032)
13.3.7. Market Revenue and Forecast, by Application (2020-2032)
13.3.8. China
13.3.8.1. Market Revenue and Forecast, by Component (2020-2032)
13.3.8.2. Market Revenue and Forecast, by Technology (2020-2032)
13.3.8.3. Market Revenue and Forecast, by Platform (2020-2032)
13.3.8.4. Market Revenue and Forecast, by Installation (2020-2032)
13.3.9. Market Revenue and Forecast, by Application (2020-2032)
13.3.10. Japan
13.3.10.1. Market Revenue and Forecast, by Component (2020-2032)
13.3.10.2. Market Revenue and Forecast, by Technology (2020-2032)
13.3.10.3. Market Revenue and Forecast, by Platform (2020-2032)
13.3.10.4. Market Revenue and Forecast, by Installation (2020-2032)
13.3.10.5. Market Revenue and Forecast, by Application (2020-2032)
13.3.11. Rest of APAC
13.3.11.1. Market Revenue and Forecast, by Component (2020-2032)
13.3.11.2. Market Revenue and Forecast, by Technology (2020-2032)
13.3.11.3. Market Revenue and Forecast, by Platform (2020-2032)
13.3.11.4. Market Revenue and Forecast, by Installation (2020-2032)
13.3.11.5. Market Revenue and Forecast, by Application (2020-2032)
13.4. MEA
13.4.1. Market Revenue and Forecast, by Component (2020-2032)
13.4.2. Market Revenue and Forecast, by Technology (2020-2032)
13.4.3. Market Revenue and Forecast, by Platform (2020-2032)
13.4.4. Market Revenue and Forecast, by Installation (2020-2032)
13.4.5. Market Revenue and Forecast, by Application (2020-2032)
13.4.6. GCC
13.4.6.1. Market Revenue and Forecast, by Component (2020-2032)
13.4.6.2. Market Revenue and Forecast, by Technology (2020-2032)
13.4.6.3. Market Revenue and Forecast, by Platform (2020-2032)
13.4.6.4. Market Revenue and Forecast, by Installation (2020-2032)
13.4.7. Market Revenue and Forecast, by Application (2020-2032)
13.4.8. North Africa
13.4.8.1. Market Revenue and Forecast, by Component (2020-2032)
13.4.8.2. Market Revenue and Forecast, by Technology (2020-2032)
13.4.8.3. Market Revenue and Forecast, by Platform (2020-2032)
13.4.8.4. Market Revenue and Forecast, by Installation (2020-2032)
13.4.9. Market Revenue and Forecast, by Application (2020-2032)
13.4.10. South Africa
13.4.10.1. Market Revenue and Forecast, by Component (2020-2032)
13.4.10.2. Market Revenue and Forecast, by Technology (2020-2032)
13.4.10.3. Market Revenue and Forecast, by Platform (2020-2032)
13.4.10.4. Market Revenue and Forecast, by Installation (2020-2032)
13.4.10.5. Market Revenue and Forecast, by Application (2020-2032)
13.4.11. Rest of MEA
13.4.11.1. Market Revenue and Forecast, by Component (2020-2032)
13.4.11.2. Market Revenue and Forecast, by Technology (2020-2032)
13.4.11.3. Market Revenue and Forecast, by Platform (2020-2032)
13.4.11.4. Market Revenue and Forecast, by Installation (2020-2032)
13.4.11.5. Market Revenue and Forecast, by Application (2020-2032)
13.5. Latin America
13.5.1. Market Revenue and Forecast, by Component (2020-2032)
13.5.2. Market Revenue and Forecast, by Technology (2020-2032)
13.5.3. Market Revenue and Forecast, by Platform (2020-2032)
13.5.4. Market Revenue and Forecast, by Installation (2020-2032)
13.5.5. Market Revenue and Forecast, by Application (2020-2032)
13.5.6. Brazil
13.5.6.1. Market Revenue and Forecast, by Component (2020-2032)
13.5.6.2. Market Revenue and Forecast, by Technology (2020-2032)
13.5.6.3. Market Revenue and Forecast, by Platform (2020-2032)
13.5.6.4. Market Revenue and Forecast, by Installation (2020-2032)
13.5.7. Market Revenue and Forecast, by Application (2020-2032)
13.5.8. Rest of LATAM
13.5.8.1. Market Revenue and Forecast, by Component (2020-2032)
13.5.8.2. Market Revenue and Forecast, by Technology (2020-2032)
13.5.8.3. Market Revenue and Forecast, by Platform (2020-2032)
13.5.8.4. Market Revenue and Forecast, by Installation (2020-2032)
13.5.8.5. Market Revenue and Forecast, by Application (2020-2032)
Chapter 14. Company Profiles
14.1. Machine Halo
14.1.1. Company Overview
14.1.2. Product Offerings
14.1.3. Financial Performance
14.1.4. Recent Initiatives
14.2. Lockheed Martin
14.2.1. Company Overview
14.2.2. Product Offerings
14.2.3. Financial Performance
14.2.4. Recent Initiatives
14.3. Northrop Grumman
14.3.1. Company Overview
14.3.2. Product Offerings
14.3.3. Financial Performance
14.3.4. Recent Initiatives
14.4. Raytheon Company
14.4.1. Company Overview
14.4.2. Product Offerings
14.4.3. Financial Performance
14.4.4. Recent Initiatives
14.5. Thales Group
14.5.1. Company Overview
14.5.2. Product Offerings
14.5.3. Financial Performance
14.5.4. Recent Initiatives
14.6. Bae Systems
14.6.1. Company Overview
14.6.2. Product Offerings
14.6.3. Financial Performance
14.6.4. Recent Initiatives
14.7. IBM
14.7.1. Company Overview
14.7.2. Product Offerings
14.7.3. Financial Performance
14.7.4. Recent Initiatives
14.8. General Dynamics
14.8.1. Company Overview
14.8.2. Product Offerings
14.8.3. Financial Performance
14.8.4. Recent Initiatives
14.9. Soartech
14.9.1. Company Overview
14.9.2. Product Offerings
14.9.3. Financial Performance
14.9.4. Recent Initiatives
14.10. Nvidia
14.10.1. Company Overview
14.10.2. Product Offerings
14.10.3. Financial Performance
14.10.4. Recent Initiatives
Chapter 15. Research Methodology
15.1. Primary Research
15.2. Secondary Research
15.3. Assumptions
Chapter 16. Appendix
16.1. About Us
16.2. Glossary of Terms
Cross-segment Market Size and Analysis for
Mentioned Segments
Additional Company Profiles (Upto 5 With No Cost)
Additional Countries (Apart From Mentioned Countries)
Country/Region-specific Report
Go To Market Strategy
Region Specific Market DynamicsRegion Level Market Share Import Export AnalysisProduction AnalysisOthers