Cybersecurity

AI in Cybersecurity Market Is Expected To Reach A Revenue Of USD 147.5 Bn By 2033, At 20.8% CAGR: Dimension Market Research


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Dimension Market Research

In the coming years, AI will play a highly important role in cybersecurity, driving innovation in threat detection, incident response, and predictive intelligence. As AI algorithms advance, they will improve security measures by automating tasks, identifying complex threats, and enhancing overall resilience against cyberattacks. However, challenges like data privacy, adversarial attacks, and ethical considerations will require constant attention and reduction strategies.

New York, May 22, 2024 (GLOBE NEWSWIRE) — Overview:

The Global AI in Cybersecurity Market size reached USD 22.1 billion by 2023 and is further anticipated to reach USD 147.5 billion by 2033 according to Dimension Market Research. The market is anticipated to register a CAGR of 20.8% from 2023 to 2033.

AI, with applications in technology, healthcare, & pharmaceuticals, plays an important role in cost reduction across processes, manufacturing, development, & automation. Further, in cybersecurity, AI uses technologies like speech recognition to enhance capabilities, allowing swift responses to cybercrime, particularly in anti-fraud measures and security management.

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Network security claimed a significant revenue share in 2023 due to the broad adoption of machine learning and AI in cybersecurity. Also, businesses heavily depend on these technologies to tackle cyber-attacks, with AI-based endpoint security gaining traction for constant monitoring & automated risk-based controls, adapting to evolving cybersecurity landscapes.

The machine learning segment led in revenue share in 2023, driven by the broad adoption of deep learning, as key players like Google & IBM integrate machine learning for better threat detection & email filtering, supporting cybersecurity. Also, machine learning platforms automate monitoring, identify anomalies, & process large security data.

Also, the market is expected to further grow, driven by the NLP segment, as the increase in popularity of text summarization, sentiment analysis, question-answering systems, & natural language inference contributes to this trend.

Important Insights

  • The global AI in cybersecurity market is expected to grow by USD 147.5 billion by 2033 from 2023 with a CAGR of 20.8%.

  • Network security secured a notable revenue share in 2023, driven by the widespread adoption of machine learning & AI in cybersecurity, as businesses heavily depend on these technologies to combat cyber-attacks, with AI-based endpoint security adapting to evolving landscapes.

  • The services sector gained a notable revenue share in 2023, driving rapid growth in the AI cybersecurity market, as increased demand for machine learning, APIs, speech, sensor data, and vision drives market expansion.

  • Machine learning dominated revenue in 2023 with the broad adoption of deep learning by key players like Google & IBM, supporting cybersecurity. The market is expected to further grow, driven by the NLP segment.

  • North America dominated with a 39.1% market share in 2023, driven by IoT, 5G, and Wi-Fi 6 expansion. To enhance security, organizations plan investments in ML, analytics, and real-time tools.

Global AI in Cybersecurity Market: Trends

  • Zero-Trust Security: AI is largely integrated into zero-trust architectures, where constant authentication and authorization are crucial, improving overall security posture.

  • Explainable AI (XAI): Demand is growing for AI models that provide transparent explanations for their decisions in cybersecurity applications, helping in trust-building and regulatory compliance.

  • AI-Powered Deception Technology: AI-driven deception techniques are gaining traction, enabling organizations to deploy fake assets and breadcrumbs to lure and deceive attackers, improving threat detection and response capabilities.

  • Federated Learning: Federated learning techniques are being explored to train AI models collaboratively across many organizations while preserving data privacy, allowing more better and diverse threat detection capabilities.

AI in Cybersecurity Market: Competitive Landscape

Both established & emerging players in the AI in cybersecurity market are heavily investing in ML, neural networks, and NLP to provide users with AI-driven insights. In addition, cybercriminals are using AI to improve the effectiveness of their attacks.

Further, major companies are preparing to strengthen their cybersecurity defenses with AI, enabling industry participants to allocate funds towards both organic & inorganic strategies to enhance their proficiency in AI-based cybersecurity. Some of the major players in the market include NVIDIA Corp, Darktrace, Cisco System, LogRhythm, McAfee, Intel Corp, IBM Corp, and more.

Some of the prominent market players:

  • NVIDIA Corp

  • IBM Corp

  • Intel Corp

  • McAfee

  • Samsung Electronics

  • Micron Technology

  • Cylance Inc

  • Cisco System

  • Darktrace

  • LogRhythm

  • Other Key Players

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AI in Cybersecurity Market Scope

Report Highlights

Details

Market Size (2023)

USD 22.1 Bn

Forecast Value (2033)

USD 147.5 Bn

CAGR (2024-2033)

20.8%

Leading Region in terms of Revenue  Share

North America

Percentage of Revenue Share by Leading Region

39.1%

Historical Data

2017 – 2022

Forecast Data

2025 – 2033

Base Year

2023

Estimate Year

2024

Segments Covered

By Component, By Technology, By Application

Regional Coverage

North America, Europe, Asia Pacific, Latin America, Middle East & Africa (MEA)

Regional Analysis

North America led the AI in cybersecurity market with a 39.1% revenue share in 2023, driven by the increase in network-connected devices fueled by IoT, 5G, & Wi-Fi 6. Industries like healthcare, automotive, energy, government, & mining driving 5G expansion, introducing potential vulnerabilities.

To improve security, key organizations intend to invest in machine learning, advanced analytics, & real-time assessment tools. Further, the region is expected to lead the adoption of natural language processing, ML, and neural networks for cyber threat detection, mainly with the increasing use of mobile devices.

Further, in Europe, strict government policies & a rise in cyber incidents, mainly in healthcare, automotive, government, and IT & telecommunication, provide growth prospects. In addition, governments in France, the UK, Germany, and Russia plan increased investments in anomaly & threat detection, urging cybersecurity providers to enhance their AI solutions to address evolving cyber challenges.

By Region

North America

Europe

  • Germany

  • The U.K.

  • France

  • Italy

  • Russia

  • Spain

  • Benelux

  • Nordic

  • Rest of Europe

Asia-Pacific

  • China

  • Japan

  • South Korea

  • India

  • ANZ

  • ASEAN

  • Rest of Asia-Pacific

Latin America

  • Brazil

  • Mexico

  • Argentina

  • Colombia

  • Rest of Latin America

Middle East & Africa

  • Saudi Arabia

  • UAE

  • South Africa

  • Israel

  • Egypt

  • Rest of MEA

Segment Analysis:

Based on offerings, the services sector claimed a significant revenue share in 2023, driving quick growth in the AI cybersecurity market, as increased demand for machine learning, APIs, speech, sensor data, and vision fuels market expansion, driven by advanced programs adept at reliably detecting anomalies.

Also, hardware operations gain popularity, and the software platform changes to improve security capabilities, as industry participants are expected to prioritize open system architecture, open-source software, and open standards to advance hidden computing.

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AI in Cybersecurity Market Segmentation

By Type

  • Network Security

  • Endpoint Security

  • Application Security

  • Cloud Security

By Offering

By Type

By Deployment

  • Cloud

  • On-Premises

  • Hardware

  • Microprocessing Unit (MPU)

  • Graphics Processing Unit (GPU)

  • Field Programmable Gate Arrays (FPGA)

  • Application Specific Integrated Circuit (ASIC)

  • Tensor Processing Unit (TPU)\Other Processors

By Technology

  • Machine Learning

  • Convolutional Neural Networks (CNN)

  • Recurrent Neural Networks (RNN)

  • Generative AI

  • Generative Adversarial Networks

  • Variational Autoencoders

  • Transformative AI

  • Others

    • Supervised Learning

    • Unsupervised Learning

    • Reinforcement Learning

    • Neural Networks

  • Natural Language Processing

    • Text Analysis

    • Chatbot Security

    • Sentiment Analysis

    • Natural Language Generation (NLG)

    • Named Entity Recognition (NER)

    • Natural Language Understanding (NLU)

  • Context-Aware Computing

  • Security Orchestration, Automation, and Response (SOAR)

  • Robotic Process Automation (RPA)

  • Computer Vision

By Application

  • Identity And Access Management

  • Risk And Compliance Management

  • Data Loss Prevention

  • Unified Threat Management

  • Fraud Detection/Anti-Fraud

  • Threat Intelligence

  • Others

By End User

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Global AI in Cybersecurity Market: Driver

  • Threat Detection Enhancement: AI algorithms can quickly identify and respond to changing cyber threats, supporting overall security posture.

  • Automated Incident Response: AI smoothens incident response processes, reduces human error, and minimizes the impact of breaches.

  • Behavioral Analytics: AI-driven behavioral analysis detects anomalies in user and system behavior, indicating potential security breaches before they grow.

  • Predictive Intelligence: AI uses data analytics to predict future cyber threats, allowing proactive measures to reduce risks and vulnerabilities.

Global AI in Cybersecurity Market: Restraints

  • Data Privacy Concerns: The growing concerns about data privacy and compliance regulations limit the availability of large, diverse datasets required for training advanced AI models.

  • Adversarial Attacks: The risk of adversarial attacks targeting AI systems in cybersecurity applications creates a major challenge, reducing the reliability and effectiveness of AI-driven defenses.

  • Complexity and Integration Challenges: Integrating AI solutions into current cybersecurity infrastructures often demanding significant resources and expertise, causing adoption barriers for some organizations.

  • Ethical and Bias Issues: AI algorithms may inherit biases provides in training data or inadvertently contribute to discriminatory outcomes, growing ethical concerns and potential backlash from stakeholders.

Global AI in Cybersecurity Market: Opportunities

  • Market Expansion: AI opens doors for cybersecurity solutions in growing sectors like IoT, cloud computing, and critical infrastructure protection.

  • Customization and Scalability: AI allows for customized security solutions adaptable to different industries and organizational sizes, supporting market growth.

  • Compliance Solutions: AI helps in automating compliance processes, providing opportunities for vendors to provide complete regulatory compliance solutions.

  • Cybersecurity Skills Gap Mitigation: AI-driven tools look into the shortage of cybersecurity professionals by automating tasks and improving the efficiency of existing teams, developing a niche market for skill augmentation solutions.

Recent Developments in the AI in Cybersecurity Market

  • November 2023: CISA & NCSC collaborated on Secure AI System Development Guidelines, endorsed by 23 global cybersecurity organizations, integrating with US Voluntary Commitments on Safe AI, it focuses on customer-centric security, transparency, & organizational structures for secure design.

  • November 2023: Trellix launched innovative Generative Artificial Intelligence (GenAI) features, using Amazon Bedrock & the Trellix Advanced Research Center using AWS’s managed service, it improves generative AI application development & scalability.

  • November 2023: The DHS’s Cybersecurity & Infrastructure Security Agency (CISA) unveiled its inaugural AI Roadmap, aligning with national objectives for secure AI development, focusing on global safety standards, network protection, & talent attraction.

  • October 2023: IBM launched an updated version of its managed detection and response services, using advanced AI for the automatic handling of 85% of security alerts, as the Threat Detection & Response Services ensure constant monitoring and resolution in hybrid cloud environments.

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