AI In Cybersecurity Market (By Type: Network Security, Cloud Security; By Technology; By Application; By Vertical) - Global Industry Analysis, Size, Share, Growth, Trends, Revenue, Regional Outlook and Forecast 2024-2033

The global AI in cybersecurity market was estimated at USD 20.47 billion in 2023 and it is expected to surpass around USD 180.81 billion by 2033, poised to grow at a CAGR of 24.34% from 2024 to 2033. Artificial intelligence (AI) technologies, such machine learning (ML) and natural language processing (NLP), are becoming more and more popular as a means of threat detection, protection, and response. Furthermore, the necessity for enhanced AI in cybersecurity has been highlighted by the exponential surge in cyberattacks against government, defense, and high-tech enterprises. 

Key Pointers

• North America region dominated the market with the largest market share of 36% in 2023.
• By Type, the network security segment is registered the maximum market share of 38% in 2023.
• By Technology, the ML segment generated the maximum market share of 47% in 2023.
• By Application, the fraud detection/anti-fraud segment had the largest market share of 22% in 2023.
• By Vertical, the enterprise segment captured the maximum market share of 24% in 2023.

AI In Cybersecurity Market Overview

The intersection of artificial intelligence (AI) and cybersecurity has given rise to a dynamic and rapidly evolving market landscape. As organizations grapple with increasingly sophisticated cyber threats, the integration of AI technologies has become a strategic imperative. This overview provides a snapshot of the AI in cybersecurity market, examining key drivers, applications, challenges, and market players shaping this transformative industry.

AI In Cybersecurity Market Growth

The growth of the AI in cybersecurity market is underpinned by several key factors propelling the industry forward. Firstly, the escalating sophistication of cyber threats has created an imperative for advanced and adaptive defense mechanisms, with AI standing out as a proactive solution capable of analyzing patterns and identifying anomalies in real-time. Additionally, the need for instantaneous threat detection has fueled the adoption of AI, as traditional security measures often lag in providing swift responses. The exponential growth in data generated in the digital landscape further drives market expansion, with AI's capacity for efficient data analysis enhancing the identification of potential security risks. As organizations increasingly recognize the limitations of conventional cybersecurity approaches, the integration of AI, particularly through machine learning algorithms and behavioral analytics, becomes instrumental in fortifying digital ecosystems. The confluence of these factors positions the AI in cybersecurity market as a dynamic and vital sector in the ongoing battle against evolving cyber threats.

Report Scope of the AI In Cybersecurity Market

AI In Cybersecurity Market Dynamics

Drivers

• Cyber Threat Sophistication: The increasing complexity of cyber threats necessitates advanced defense mechanisms, and AI offers a proactive approach by analyzing patterns and detecting anomalies in real-time.
• Real-time Threat Detection Needs: Traditional security measures often fall short in providing real-time threat detection. AI empowers cybersecurity systems to identify and respond to threats instantly, minimizing the potential impact of cyber attacks.

Restraints

• Adversarial AI Challenges: The evolution of AI techniques is met with corresponding advancements in adversarial attacks, posing a significant challenge. Adversarial AI seeks to deceive AI systems, requiring continuous innovation in cybersecurity solutions to stay ahead of malicious actors.
• Data Privacy Concerns: The utilization of AI in cybersecurity involves the processing of vast amounts of sensitive data. Striking a delicate balance between effective threat detection and maintaining user privacy presents an ongoing challenge, particularly in compliance with evolving data protection regulations.

Opportunities

• Innovations in Explainable AI: The development of explainable AI (XAI) presents a significant opportunity, allowing organizations to better understand and trust AI-driven cybersecurity systems. Enhanced transparency can lead to increased adoption and acceptance of AI technologies.
• Integration of AI in Cloud Security: As organizations increasingly migrate to cloud-based infrastructure, there is a growing opportunity for the integration of AI in cloud security. AI can enhance threat detection, response, and overall resilience in cloud environments.

Type Insights

The network security segment is held the largest revenue share of 38% in 2023 owing to the high prominence of ML algorithms and AI. Businesses are leveraging cybersecurity to protect and prevent cyber-attacks. Hardware could be a major growth enabler to boost business efficiency and scalability of operations. Prominently, the zero-trust model-needing all users to be authorized and authenticated-has gained ground. For instance, in June 2022, Cisco revealed its plans to foster a secure hardware strategy through Cisco Security Hardware.

The AI-based endpoint security will receive drive across organizations for continuous monitoring, risk-based application control, and automated classification. Prominently, endpoint security solutions automatically create an allow list based on known goodware and a deny list based on known malware. With endpoint attacks becoming prevalent, AI-based real-time authentication and behavioral analytics could be pursued to underpin security solutions

Technology Insights

The ML segment led with a revenue share of 47% in 2023. ML technology will witness profound growth against the backdrop of rising use of DL across end-use industries. Leading companies, such as Google and IBM, have been using ML to filter emails and threat detection. Organizations are cashing in on the power of ML and DL to boost cybersecurity practices. For instance, DL has set the trend for image recognition across applications, including medical diagnoses and autonomous vehicles. In addition, ML platforms have gained popularity in automating the monitoring process, spotting deviation from the norm, and sifting through the massive volume of data produced by security tools.

The NLP segment will have a significant growth during the forecast period. The trend is mainly due to the high prominence of sentiment analysis, natural language inference, text summarization, and question-answering systems (QAS). Moreover, NLP has become sought-after to identify overlaps in data, frameworks, and standards and detect vulnerabilities in the security infrastructure. NLP could make significant strides and expand AI applications in cybersecurity over the next few years through automation and customization.

Application Insights

The fraud detection/anti-fraud segment contributed the largest market share of 22% in 2023. AI in cybersecurity will receive impetus for fraud detection and anti-fraud as upfront prevention controls. Machine learning has emerged as a viable tool for bolstering governments’ and other end-users ability to deter fraudulent activities amidst a rise in fraud cases. In in February 2022, the Federal Trade Commission (FTC) data suggested that it received 2.8 million fraud reports from consumers in the preceding year. Accordingly, AI tools could gain ground to prevent fraud, email phishing, and fake records.

Enterprises have exhibited increased traction for unified threat management (UTM) to protect their digital assets against threats, such as spyware-infected files, phishing attacks, unapproved website access, and trojans. UTM approach is expected to gain ground to provide multiple security functions, including business virtual private network (VPN), intrusion detection & prevention, network firewalls, gateway anti-virus, and web content filtering. Organizations are likely to prioritize UTM software tools to detect advanced threats quickly with increased accuracy. UTM tools are expected to gain traction for scalable hardware-based monitoring and prevent the attack before it enters the network.

Vertical Insights

The enterprise segment held the leading revenue share of 24% in 2023. However, the BFSI sector could emerge as a major market for cyber-AI to prevent data leaks, resist cyberattacks, and bolster security. The wave of innovations and technological advances has brought a paradigm shift in making payments, purchases, applying for loans, and withdrawals to crowdfunding. Furthermore, banks and financial institutions are likely to count on the zero-trust model on the hardware to boost threat intelligence-based actions. Industry participants expect the adoption of AI in the fintech sector to boost market share. The robust forecast is mainly due to the penetration of AI-based solutions to prevent and identify financial crimes & fraud.

Furthermore, rampant distributed denial of service (DDoS) attacks across banks and fintech sectors have furthered the demand for AI. Moreover, artificial neural networks (ANN) will also receive impetus to anticipate hackers’ behavior, enabling banks to respond to attacks in real-time. The government & defense sector has exhibited an increased inclination toward AI following the surge in cyber incidents.

In January 2022, a cyberattack reportedly targeted 90 websites of the Ukrainian government and deployed malicious software, taking a toll on dozens of government agencies’ computers. Accordingly, governments are poised to bank on Cloud Security and zero-trust architecture to keep cyber incidents at bay. The media & entertainment industry is expected to witness substantial growth. Vendors are focusing on data enrichment, automated reporting, analyzing, metadata insights, etc. for improved customer experience and operations.

Regional Insights

North America accounted for a major revenue share of 36% in 2023 due to the surge in network-connected devices with the growing footfall of Internet of Things (IoT), 5G, and Wi-Fi 6. Organizations across the automotive, healthcare, government, energy, and mining sectors have propelled 5G network expansion, providing a possible entry point for hackers. Leading organizations are likely to infuse funds into ML platforms, advanced analytics, and asset mapping and visualization platforms for a real-time assessment. North America is slated to be the prominent adopter of NLP, ML, and neural networks to deter attacks and spot strange user behavior and other abnormal patterns.

Rising penetration of mobile devices, including smartwatches, tablets, and phones, are also likely to augment the need for AI solutions and services for increased security. According to CUJO AI’s security data, nearly 60% of threats to mobile device security emanate from browsing activities. Stakeholders across North America are likely to seek AI algorithms to overcome cybersecurity concerns. Europe is likely to provide lucrative growth opportunities in the wake of strong government policies and growing cyber cases across the automotive, healthcare, government, and IT & telecommunication sectors.

AI In Cybersecurity Market Key Companies

• Acalvio Technologies, Inc.
• Amazon Web Services, Inc.
• Cylance Inc. (BlackBerry)
• Darktrace
• FireEye, Inc.
• Fortinet, Inc.
• IBM Corporation
• Intel Corporation
• LexisNexis
• Micron Technology, Inc.

AI In Cybersecurity Market Report Segmentations:

By Type

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

By Technology

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

By Application

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

By Vertical

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

By Region

• North America
• Europe
• Asia Pacific
• South America
• Middle East & Africa (MEA)