Artificial Intelligence (AI) In Cybersecurity Market Size USD 102.78 BN by 2032 | Martech Edge | Best News on Marketing and Technology
Artificial Intelligence (AI) In Cybersecurity Market Size USD 102.78 BN by 2032


Artificial Intelligence (AI) In Cybersecurity Market Size USD 102.78 BN by 2032

Artificial Intelligence (AI) In Cybersecurity Market Size USD 102.78 BN by 2032


Published on : Jan 23, 2023

The global artificial intelligence (AI) in cybersecurity market size is projected to expand around USD 102.78 billion by 2032 and it is expected to grow at a registered CAGR of 19.43% from 2023 and 2032.

According to Precedence Research, the artificial intelligence (AI) in cybersecurity market size was valued at USD 17.4 billion in 2022. Artificial intelligence in cybersecurity is essentially the use of AI technology to streamline complicated cybersecurity procedures in order to increase the system's dependability, security, and independence. The rise of disruptive digital technologies in a variety of industry sectors, rising demand for advanced cybersecurity products and privacy, an increase in the frequency and complexity of cyberthreats, and steady technological advancements are the main factors propelling the artificial intelligence market in cybersecurity.

Key Takeaways:

  • North America market has accounted revenue share of 38% in 2022.
  • By offering, the services segment has accounted revenue share of 36% in 2022.
  • By technology, the machine learning segment has accounted revenue share of 47% in 2022. 
  • By vertical, the enterprise segment has accounted revenue share of 24% in 2022. 
  • By application, the fraud detection and anti-fraud segment has accounted revenue share of over 22% in 2022.

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Market Growth

Artificial intelligence (AI) in the cybersecurity market is driven by the increase in cybercrimes. The risk of cyber assaults has increased as IoT adoption and the number of connected devices has increased globally. If not addressed promptly, the majority of common cybercrimes, such as identity theft and credit card theft, filed by big businesses can result in significant financial losses. The adoption of cutting-edge security AI solutions is thus anticipated to fuel market expansion. In addition to offering greater security than human capabilities, AI security solutions also speed up the entire acknowledgment and identification process for cyberfrauds. Therefore, the usage of AI technology in the cyber security market is further anticipated to increase as cyber security risk occurrences rise.

Regional Analysis

In 2022, the revenue share was dominated by North America. The growth of IoT, 5G, and Wi-Fi 6 is largely responsible for the trend's increase in network-connected devices. A potential access point for hackers is the 5G network expansion driven by businesses in the automotive, healthcare, government, energy, and mining industries. As a result of strict government regulations and an increase in cyberattacks on the government, healthcare, automotive, and IT & telecommunication industries, Europe is set to offer attractive growth prospects. In the midst of measures to counter cyber-attacks from Russia and other belligerent states, the administration is nevertheless confident that increased defense spending would strengthen its position in Europe.

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Scope of the Report

Report Attributes Details
Market Size in 2022 USD 17.4 Billion
Revenue Forecast by 2032 USD 102.78 Billion
CAGR 19.43% from 2023 to 2032
North America Revenue Share 38% in 2022
Enterprise Category Segment Revenue Share 24% in 2022
Machine Learning Segment Revenue Share 47% in 2022
Base Year 2022
Forecast Year 2023 to 2032
Key Players NVIDIA Corporation, Intel Corporation, Xilinx Inc., Samsung Electronics Co Ltd, Micron Technology Inc., Amazon Web Services, Inc., IBM Corporation, Microsoft Corporation, FireEye, Inc., Palo Alto Networks, Inc., Juniper Networks, Inc., Fortinet, Inc., Cisco Systems, Inc., Check Point Software Technologies Ltd., Imperva, McAfee LLC, LogRhythm, Inc., Sophos Ltd., NortonLifeLock Inc. and Others

Market Dynamics of the Artificial Intelligence (AI) In Cybersecurity Market

Market Drivers

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 money. Political rivalry, financial gain, reputational injury, international rivalry, and the interest of radical religious groups are among the main motives of cybercriminals. Most cyberattacks aim to profit financially. Among the notable ransomware that has severely impacted businesses and government institutions are WannaCry, Petya, NotPetya, and BadRabbit. Business productivity is being hampered by cyber threats, which are also compromising enterprises' sensitive data and vital IT infrastructure. Cybercrimes are happening more frequently as a result of the swift expansion in digital trade across a variety of industries worldwide. The market for cybersecurity goods and services is being driven by the surge in data breaches or leaks at businesses. As a result, protecting against cyber risks has become crucial for commercial growth for organizations. 

Market Restraints

All AI methods and techniques, including machine learning, deep learning, genetic algorithms, and neural networks, are built on prior experiences. In other words, cybersecurity AI is built on learning from previous malware about what malware looks like and how it behaves. An unidentified computer security flaw is exploited by zero-day malware. An advanced persistent threat (APT) is a network attack in which an unauthorized user logs onto a network and remains there for a protracted length of time without being noticed. Genuine defense against complex, cutting-edge threats must not rely on earlier viruses or assaults. Therefore, a market limitation is being caused by AI's incapacity to counter advanced threats.

Market Opportunities

The security of complex networks is always under attack from both internal and external dangers, according to the zero-trust paradigm. Each connection a user makes to software or an application that connects to a data set via an API is verified and approved by a zero-trust security model (API). 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. The cornerstone of zero trust, the idea of least-privileged access, states that trust should be built according to the context (such as user identification and location, endpoint security posture, and the app or service being requested), with policy checks at each stage. 

Market Segmentations of the Artificial Intelligence (AI) In Cybersecurity Market

Type Insights

The market is divided into identity and access security services, network security services, cloud security services, data security services, and others based on the type of security provided. The fastest growth among all is anticipated to occur in the AI for cloud cyber security services throughout the projection period. The majority of causes driving the quickest growth of AI in the market for cyber security services include the growing number of large businesses using cloud platforms as servers and data repositories, which leaves them exposed to cyberattacks.

Offering Insights

In 2022, a significant revenue share is predicted for the services sector. The category is anticipated to significantly contribute to the expansion of the global market for AI in cybersecurity. The market will grow as a result of the strong need for application program interfaces, including those for machine learning techniques, sensor data, speech, and vision. The program is unique in its capacity to accurately and reliably identify abnormal activity. The software platform will advance to bolster the security offering as hardware operations become more popular. Modern cybersecurity solutions are going to be emphasized by industry participants, who may also invest money in the software platform. They'll probably expand on open-source software, open system architecture, and open standards to advance secret computing.

Technology Insights

With a revenue share in 2022, the machine learning segment took the lead. Against the backdrop of deep learning's explosive deployment across end-use industries, machine-learning technologies will experience significant growth. Leading businesses, including Google and IBM, have begun employing machine learning for threat detection and email filtering. Businesses are leveraging the potential of deep learning and machine learning to advance cybersecurity procedures. Additionally, ML platforms are becoming more and more popular as a way to automate monitoring, detect deviation from the norm, and sort through the enormous amount of data generated by security technologies.

Vertical Insights

In terms of revenue share, the enterprise category led in 2022. However, the BFSI industry may develop into a significant market for cyber-AI to stop data leaks, fend off cyberattacks, and improve security. A paradigm shift in how people make payments, purchases, borrow money, and withdraw money through crowdfunding has been brought about by the wave of innovations and technological advancements. The Hardware's zero-trust concept is also anticipated to be relied upon by banks and other financial institutions to strengthen threat intelligence-based operations.

Application Insights

The global revenue share in 2022 was accounted for by the fraud detection and anti-fraud segment. AI in cybersecurity will be encouraged for fraud detection and anti-fraud as preventative measures upfront. A growing number of fraud instances have led to the emergence of machine learning as a practical technique for enhancing the capacity of governments and other end-users to prevent fraudulent actions. As a result, AI tools may be used more frequently to stop fraud, email phishing, and false records. To safeguard their digital assets from dangers including spyware-infected files, phishing assaults, unauthorized website access, and trojans, businesses have shown greater interest in unified threat management (UTM).

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Recent Development

  • In March 2019, NVIDIA revealed the Jetson Nano, a device that can build numerous intelligent systems. The little yet mighty CUDA-X AI computer, which delivers 472 GFLOPS of computational capabilities while utilizing as little as 5 watts of power, can execute modern AI applications.
  • In Feb 2019, Cylance launched the Cylance native AI platform, which offers automated threat detection, prevention, forensic investigation, and response capabilities to customers all around the world. Deep-learning Al algorithms are combined into a single, adaptable agent to provide an all-encompassing attack surface defense.
  • In Feb 2019, privately held cybersecurity and artificial intelligence company Cylance was purchased by BlackBerry Limited. After the acquisition, Cylance's machine learning and artificial intelligence technologies are now a part of BlackBerry's end-to-end secure communications offering. Notably, BlackBerry Spark's advancement as the safe communications platform for the Internet of Things (IoT) in the future is accelerated by its embeddable AI technology.
  • In March 2020, a legally binding agreement has been reached for WatchGuard Technologies Inc. to buy Panda Protection, a supplier of endpoint security with operations in Madrid. As a result of this transaction, the previous organization's network offerings will grow.

Market Segmentation

By Type

  • Network Security
  • Endpoint Security
  • Application Security
  • Cloud Security

By Offering

  • Hardware
  • Software
  • Services

By Technology

  • Machine Learning
  • Natural Language Processing (NLP)
  • Context-aware Computing

By Vertical

  • BFSI
  • Retail
  • Government & Defense
  • Manufacturing
  • Enterprise
  • Healthcare
  • Automotive & Transportation
  • Others

By Application

  • Identity And Access Management
  • Risk And Compliance Management
  • Data Loss Prevention
  • Unified Threat Management
  • Fraud Detection/Anti-Fraud
  • Threat Intelligence
  • Others

By Geography

  • North America
  • Europe
  • Asia-Pacific
  • Latin America
  • The Middle East and Africa