Artificial Intelligence in Cybersecurity Market Forecasts to 2030 – Global Analysis By Component (Hardware, Software and Services), Security Type, Deployment Type, Technology, Application, End User and By Geography

Artificial Intelligence in Cybersecurity Market Forecasts to 2030 – Global Analysis By Component (Hardware, Software and Services), Security Type, Deployment Type, Technology, Application, End User and By Geography

According to Stratistics MRC, the Global Artificial Intelligence in Cybersecurity Market is accounted for $22.4 billion in 2023 and is expected to reach $100.4 billion by 2030 growing at a CAGR of 23.9% during the forecast period. Artificial intelligence (AI) has a big impact on cybersecurity, by making it easier to identify, stop, and respond to cyber threats. Massive amounts of data can be analysed in real-time by AI systems, which can then spot odd patterns or behaviors that can point to a cyberattack. Malware, viruses, and other dangerous software are among the things that can be found. Algorithms for machine learning can be taught to detect known risks and adjust to new ones. Anomaly detection systems powered by AI provide a baseline of typical network behavior and issue alarms when this baseline is violated. This can be used to find previously undiscovered attack methods or insider risks.

According to the Consumer Technology Association, 44% of organizations across the globe are implementing AI applications to detect and deter security intrusions.

Market Dynamics

Driver

Increase in demand for better security measures

As cyberattacks are becoming more sophisticated and frequent, organizations are rapidly feeling the need for improved and modern security solutions. Nowadays, a number of stakeholders are very concerned about cyber dangers. As a result, implementing safeguards to reduce the identified hazards is urgently needed for an organization's systems, networks, and data. Due to the increasing frequency of cyberattacks and data breaches, there is a growing need for security solutions. Additionally, the need of proactive cyber security measures, such as better cyber security and threat modelling solutions, is increasingly being recognized by enterprises, which is fuelling market expansion.

Restraint

False alarms with defamatory attacks

Security systems powered by AI run the risk of producing false alarms or failing to identify genuine threats. These errors may result in the loss of time and resources or the failure to identify vulnerabilities. AI can be used by hackers to create attacks that are intended to especially harm AI-based security systems. These assaults, often referred to as adversarial attacks, might fudge the input data to lead AI algorithms to draw the wrong conclusions thus hampering the growth of the market.

Opportunity

Requirements for regulatory compliance and industry standards

Threat modeling is frequently required of organizations as part of security programs by regulatory compliance standards and industry standards like the General Data Protection Regulation (GDPR), Payment Card Industry Data Security Standard (PCI-DSS), and National Institute of Standards and Technology (NIST). Government agencies now have an even greater need for improved security solutions, which in turn is fueling the market for AI in cybersecurity. The growing technical investment of both public and private companies is also encouraging the use of AI in the cybersecurity market.

Threat

AI's inability to combat modern and complex dangers

AI techniques and methods, such as deep learning, neural networks, genetic algorithms, and machine learning, are founded on prior experiences. An advanced persistent threat (APT) is a network attack where a user gains access to a network without authorization and remains hidden for a considerable amount of time. While some APT behaviors may be similar to past events that AIs can detect them, new APTs have no prior experiences and are therefore equipped with novel ways to invoke application programming interfaces (APIs) and cutting-edge approaches to access system resources. Real defence against complex, modern dangers cannot rely on previous viruses or assaults. This market is being constrained by AI's incapacity to counter advanced threats.

Covid-19 Impact

A lot of top cybersecurity organizations see the current crisis as a chance to review and restructure their current strategies and develop more complex product portfolios. The COVID-19 outbreak has boosted the demand for cutting-edge solutions as firms commit more to work-from-home policies. Due to a rise in demand for digital goods and services brought on by telecommuting workers and other users of potentially risky networks and devices, businesses have been pushed to invest money in machine learning and deep learning algorithms.

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

The machine learning segment is estimated to have a lucrative growth, as these deep learning spreads quickly throughout end-use industries, machine-learning technologies will grow dramatically. 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 well-liked as a tool to automate monitoring, identify anomalies, and navigate the vast amounts of data generated by security systems.

The fraud detection/anti-fraud segment is expected to have the highest CAGR during the forecast period

The fraud detection/anti-fraud segment is anticipated to witness the highest CAGR growth during the forecast period, as the use of artificial intelligence (AI) in cybersecurity will be pushed as preventative measures for fraud detection and anti-fraud. As a result of an increase in fraud incidences, machine learning has become a beneficial technique for enhancing the capacity of governments and other end users to prevent fraudulent actions. AI tools may therefore be used more frequently to get rid of fraud, email phishing, and fraudulent records. To safeguard their digital assets from threats including spyware-infected files, phishing assaults, unauthorized website access, and trojans (UTM), businesses are more interested in unified threat management thereby encouraging the market.

Region with largest share

North America is projected to hold the largest market share during the forecast period owing to the increase in network-connected devices brought on by the adoption of IoT, 5G, and Wi-Fi 6 is primarily responsible for the rise. The expansion of the 5G network has been driven by businesses in the automotive, healthcare, government, energy, and mining industries, which might be a point of access for hackers. Leading companies are likely to invest money in platforms for machine learning, sophisticated analytics, asset mapping, and visualization for a real-time evaluation. Natural language processing, machine learning (ML), and neural networks are expected to be widely used in North America to thwart assaults, detect odd user behaviour, and identify other anomalous patterns thus enhancing the growth of the market in this region.

Region with highest CAGR

Asia Pacific is projected to have the highest CAGR over the forecast period as this region has been a hotspot for cyberattacks because of its economic expansion and rising level of digitalisation. To protect against emerging threats, there is now a larger demand for advanced cybersecurity solutions, particularly those that are AI-powered. Numerous governments in the APAC area have started initiatives to encourage the creation and use of AI in cybersecurity because they understand how important it is. These projects frequently include financing for R&D as well as regulatory assistance which drive the market.

Key players in the market

Some of the key players profiled in the Artificial Intelligence in Cybersecurity Market include Micron Technology, Inc., Amazon Web Services, Inc., Cylance Inc. (BlackBerry), FireEye, Inc., Fortinet, Inc., Acalvio Technologies, Inc, Intel Corporation, IBM Corporation, LexisNexis, Darktrace, Microsoft Corporation, Samsung Electronics Co. Ltd., Cisco Systems, Inc., Gen Digital Inc., NVIDIA Corporation, McAfee LLC, Palo Alto Networks Inc. and Cylance Inc.

Key Developments

In September 2023, Cylance Inc. (BlackBerry) Launches ‘Intrinsically Safe’ Certified Solution for Hazardous Materials Carriers the new series is backed by an ‘Intrinsically Safe’ certification designation, enabling BlackBerry Radar, an asset tracking solution, to target transportation and logistics companies that move hazardous materials, including fuel haulers, tank carriers, ocean shipping lines and railroads.

In September 2023, Intel presents a software-defined, silicon-accelerated approach built on a foundation of openness, choice, trust and security. which allows the hardware to process the data without it ever being decrypted. In essence, the processor performs calculations directly on the encrypted data.

In August 2023, Micron Launches Memory Expansion Module Portfolio to Accelerate CXL 2.0 Adoption. Additionally, the CZ120 modules are capable of running up to 36GB/s memory read/write bandwidth1 and augment standard server systems when incremental memory capacity and bandwidth is required.

Components Covered
• Hardware
• Software
• Services

Security Types Covered
• Application Security
• Endpoint Security
• Network Security
• Cloud Security

Deployment Types Covered
• On-Premises
• Cloud

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

Applications Covered
• Antivirus/ Malware
• Data Loss Prevention
• Fraud Detection/Anti-Fraud
• Identity And Access Management
• Intrusion Detection/ Prevention System
• Risk And Compliance Management
• Security & Vulnerability Management
• Threat Intelligence
• Unified Threat Management
• Other Applications

End Users Covered
• BFSI
• Automotive & Transportation
• Enterprise
• Government & Defense
• Healthcare
• Infrastructure
• Manufacturing
• Retail
• 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