Artificial Intelligence in Cybersecurity Market Forecasts to 2030 – Global Analysis By Type (Cloud Security, Application Security, Endpoint Security and Other Types), Offering (Services, Software and Hardware), Technology, Application, End User and By Geo

Artificial Intelligence in Cybersecurity Market Forecasts to 2030 – Global Analysis By Type (Cloud Security, Application Security, Endpoint Security and Other Types), Offering (Services, Software and Hardware), Technology, Application, End User and By Geography

According to Stratistics MRC, the Global Artificial Intelligence In Cybersecurity Market is accounted for $20.9 billion in 2023 and is expected to reach $74.3 billion by 2030 growing at a CAGR of 19.9% during the forecast period. Real-time defense is offered by AI-based endpoint security solutions. Real-time endpoint behavior analysis by AI algorithms may alert security teams of possible hazards. As a result, security teams can respond to attacks more rapidly and eliminate them before they do any damage. The technology, healthcare, and pharmaceutical industries all use AI in different ways. The use of AI has been recognized as a vital tool for lowering the costs of many operations, including development, manufacturing, automation, monitoring, modification, and a wide range of other operations.

According to the CISCO cybersecurity threat trends report 2021, 86% of the organizations of organizations had at least one user try to connect to a phishing site, 70% of organizations had users that were served malicious browser ads, 69% of organizations experienced some level of unsolicited crypto mining, and 50% of organizations encountered ransomware-related activity.

Market Dynamics

Driver

An architecture for zero trust that offers superior security

The security of complex networks is always under assault from both internal and external dangers, according to the zero trust paradigm. When a user connects to an application or piece of software that uses an API to connect to a data collection, a zero-trust security model verifies and approves each connection. Additionally, it aids in the organization and planning of a comprehensive strategy to deal with online threats. No one or any application should ever be assumed to be trustworthy, according to the zero-trust principle.

Restraint

Transforming threat environment

Cyber hazards are ever-changing, with new attack techniques and strategies appearing frequently. For continued effectiveness, AI-based cybersecurity systems need to adjust to these changing threats. However, access to current and diverse datasets which might not always be easy to come by is necessary for training AI models on new danger patterns. AI in cybersecurity is constantly faced with the issue of staying ahead of new threats.

Opportunity

Increasing proportions of cyberthreats

Globally, the number of cyberattacks is progressively rising. Cybercriminals target endpoints, networks, data, and other IT infrastructure, which costs consumers, businesses, and governments a lot of revenue. Political rivalry, financial gain, reputational damage, international rivalry, and the interests of radical religious groups are among the main motives of cybercriminals. Most cyberattacks aim to profit financially. Additionally, among the notable ransomware that has severely impacted businesses and government institutions are WannaCry, Petya, NotPetya, and BadRabbit.

Threat

Privacy and ethical issues

Ethics and privacy issues are raised by the use of AI in cybersecurity. To identify possible risks, AI systems may gather and examine a lot of private and sensitive data. It is essential to protect the security and privacy of sensitive data, as any breach could have severe consequences. However, to avoid abuse or biased consequences, AI systems must also abide by ethical standards, including fairness, transparency, and accountability.

Covid-19 Impact

Many leading cybersecurity firms consider the crisis as a chance to review and restructure their current strategies and develop more complex product portfolios. The COVID-19 outbreak has boosted demand for cutting-edge technologies as businesses commit more to work-from-home policies. Businesses have been obliged to spend money on deep learning and machine learning algorithms because of a surge in demand for digital products and services brought on by telecommuting workers and other individuals using potentially risky networks and devices.

The machine learning segment is expected to be the largest during the forecast period

As deep learning is being rapidly adopted by all end-use industries, the machine learning category is anticipated to hold the largest market share during the projection period. Leading corporations like Google and IBM are beginning to use machine learning for threat detection and email filtering. Businesses are making use of machine learning and deep learning to enhance cybersecurity protocols. Additionally, ML platforms are becoming more and more popular as a tool to automate monitoring, identify deviations, and navigate the vast amounts of data generated by security systems.

The government and defense segment is expected to have the highest CAGR during the forecast period

As a result of a rise in cyber incidents, the government and defense sectors are predicted to experience profitable growth. According to the Center for Strategic and International Studies, a DDoS attack on a significant Israeli telecommunications provider in March 2022 resulted in the removal of a number of Israeli government websites. Moreover, the Ukrainian government's 90 websites were apparently the subject of a cyberattack in January 2022 that spread harmful software and damaged the computers of numerous government institutions. Governments are therefore prepared to rely on cloud security and zero-trust architecture to prevent cyber accidents.

Region with largest share

Due to rising connected device usage, rising cybersecurity awareness among organizations, accelerating economic growth, widespread adoption of cutting-edge technologies like IoT, 5G technology, and cloud computing, as well as rising privacy and security concerns in the region, the Asia-Pacific region is predicted to experience rapid growth during the forecast period. Furthermore, significant investments in personnel, infrastructure, and AI technologies have been made in the region, spurring cybersecurity innovation.

Region with highest CAGR

North America is projected to hold lucrative growth over the projection period. Organizations in North America experience cyber threats frequently, which has resulted in a significant demand for effective security solutions. The adoption of AI-powered cybersecurity measures is further fueled by the existence of strict data protection laws like the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA). Furthermore, a strong basis for integrating AI into cybersecurity plans is provided by the region's robust digital infrastructure and early adoption of cloud technology.

Key players in the market

Some of the key players in Artificial Intelligence In Cybersecurity market include Fortinet, Inc, Intel Corporation, Micron Technology Inc., Acalvio Technologies Inc, Xilinx Inc, Samsung Electronics Co Ltd, Microsoft Corporation, Amazon Web Services, Inc, FireEye, Inc, IBM Corporation and Palo Alto Networks, Inc..

Key Developments

In September 2022, NVIDIA launched NVIDIA IGX, which is a platform for high-precision edge AI, bringing advanced security and proactive safety to sensitive industries such as manufacturing, logistics and healthcare.

In August 2022, Microsoft has officially launched Microsoft Defender Experts for Hunting, enabling proactive threat hunting. According to Microsoft Security, they have successfully thwarted over 35.7 billion phishing and malicious emails as well as over 9.6 billion malware threats in 2021.

Types Covered
• Cloud Security
• Application Security
• Endpoint Security
• Other Types

Offerings Covered
• Services
• Software
• Hardware

Technologies Covered
• Context Aware Computing
• Natural Language Processing (NLP)
• Machine Learning
• Other Technologies

Applications Covered
• Threat Intelligence
• Fraud Detection/Anti-Fraud
• Unified Threat Management
• Data Loss Prevention
• Other Applications

End Users Covered
• Automotive & Transportation
• Healthcare
• Manufacturing
• Government & Defense
• Other End Users

Regions Covered
• North America
US
Canada
Mexico
• Europe
Germany
UK
Italy
France
Spain
Rest of Europe
• Asia Pacific
Japan
China
India
Australia
New Zealand
South Korea
Rest of Asia Pacific
• South America
Argentina
Brazil
Chile
Rest of South America
• Middle East & Africa
Saudi Arabia
UAE
Qatar
South Africa
Rest of Middle East & Africa

What our report offers
- Market share assessments for the regional and country-level segments
- Strategic recommendations for the new entrants
- Covers Market data for the years 2021, 2022, 2023, 2026, and 2030
- Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
- Strategic recommendations in key business segments based on the market estimations
- Competitive landscaping mapping the key common trends
- Company profiling with detailed strategies, financials, and recent developments
- Supply chain trends mapping the latest technological advancements