Emphasis on Deployment (On-Premise, Cloud-Based, Hybrid); Technology (Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), Reinforcement Learning (RL), Deep Neural Networks (DNNs), Natural Language Processing (NLP), Others); Application (Network Security, Endpoint Security, Cloud Security, Application Security, Others); End-User (Banking, Financial Services, And Insurance (BFSI), Healthcare, Retail, IT & Telecom, Government and Defense, Energy and Utilities, and Others); and Region/Country
The Generative AI Cybersecurity market was valued at approximately USD 4 billion in 2023 and is expected to grow at a substantial CAGR of around 21.5% during the forecast period (2024-2032) owing to the rapid growth driven by the increasing complexity of cyberattacks.
Generative AI Cybersecurity aims at the application of computer-based control systems for operating industrial facilities and processes through reduced human involvement. It improves the quality, speed, and safety of production as well as lessening the costs of production. With the help of the automated systems industries can manage processes, quality of their products, and even control the manufacturing process which will make it all faster and more accurate.
To attain growth in generative AI cybersecurity, companies are integrating AI for threat detection and mitigation, security intelligence and analytics, and security response orchestration. Also, the rising adoption of AI-based Security Operations Centers (SOCs), implementation of AI for network monitoring, and utilization of machine learning for emulation of attack scenarios. Some of the major organizations such as Microsoft, IBM, and Palo Alto Networks are already implementing it to improve their cybersecurity software and solutions.
On August 27, 2024, CrowdStrike (NASDAQ: CRWD) announced it is providing additional safeguards for NVIDIA NIM Agent Blueprints with the AI-native CrowdStrike Falcon cybersecurity platform to help developers securely leverage open-source foundational models and accelerate generative AI innovation.
On August 5, 2024, IBM (NYSE: IBM) announced the introduction of generative AI capabilities to its managed Threat Detection and Response Services utilized by IBM Consulting analysts to advance and streamline security operations for clients. Built on IBM’s watsonx data and AI platform, the new IBM Consulting Cybersecurity Assistant is designed to accelerate and improve the identification, investigation, and response to critical security threats.
This section discusses the key market trends influencing the various segments of the Generative AI Cybersecurity market as identified by our research experts.
Network Security Transform Generative AI Cybersecurity Industry
Network Security aims at shielding computer platforms from unauthorized entry and control disruption. There are specialized AI tools for network security that run continuously sense any form of anomaly, and react to it automatically, thus ensuring security for big and open networks. Moreover, companies integrate artificial intelligence-based network security to help protect enterprise networks from emerging threats. A robust market for generative AI in this segment is driven by the growing IoT environments and clouds that require protection. For instance, on May 2, 2024, Fortinet (NASDAQ: FTNT), the global cybersecurity leader driving the convergence of networking and security, announced new updates to its generative AI (GenAI) portfolio to enhance both network and security operations, including the industry’s first generative AI IoT security assistant.
Asia-Pacific leads the growth.
The Asia-Pacific region is expected to lead growth in generative AI cybersecurity because of the quick shift to digitalization, accelerated cyber threat activity, and the widespread implementation of cloud services across sectors. Asia Pacific nations such as China, India, Japan, and Australia reported a rising number of cyber threats in recent years and companies are increasingly turning to AI-powered security platforms for better defense. Huawei, Tencent, and Infosys are amongst some of the companies starting to adopt generative AI within their cybersecurity systems to protect and ensure they remain in step with the latest legislation. The e-commerce, financial services, and manufacturing companies of the region are increasingly employing AI security due to the expansion of those sectors.
On August 29, 2024, Infosys, a global leader in next-generation digital services and consulting, announced the expansion of its collaboration with NVIDIA for AI-powered, customer-centric solutions to drive innovation and operational excellence for telcos. Leveraging Infosys Topaz, an AI-first set of services, solutions, and platforms using generative AI technologies, the collaboration will help telcos enhance their customer experiences, streamline network operations, and accelerate service delivery.
The Generative AI Cybersecurity market is competitive, with several global and international players. The key players are adopting different growth strategies to enhance their market presence, such as partnerships, agreements, collaborations, new product launches, geographical expansions, and mergers and acquisitions. Some of the major players operating in the market are Microsoft; Amazon Web Services, Inc.; SentinelOne; Fortinet, Inc.; NVIDIA Corporation; CrowdStrike; Palo Alto Networks; IBM; Darktrace Holdings Limited; Cisco Systems, Inc.
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1. Market Introduction
2. Research Methodology Or Assumption
3. Executive Summary
4. Market Dynamics
5. Pricing Analysis
6. Global Generative AI Cybersecurity Market Revenue (USD BN), 2022-2032F
7. Market Insights By Deployment
8. Market Insights By Technology
9. Market Insights By Application
10. Market Insights By End-User
11. Market Insights By Region
12. Value Chain Analysis
13. Competitive Landscape
14. Company Profiles
15. Acronyms & Assumption
16. Annexure
Analyzing the historical market, estimating the current market, and forecasting the future market of the global Generative AI Cybersecurity market were the three major steps undertaken to create and analyze the adoption of Generative AI Cybersecurity in major regions globally. Exhaustive secondary research was conducted to collect the historical market numbers and estimate the current market size. Secondly, to validate these insights, numerous findings and assumptions were taken into consideration. Moreover, exhaustive primary interviews were also conducted, with industry experts across the value chain of the global Generative AI Cybersecurity market. Post assumption and validation of market numbers through primary interviews, we employed a top-down/bottom-up approach to forecasting the complete market size. Thereafter, market breakdown and data triangulation methods were adopted to estimate and analyze the market size of segments and sub-segments of the industry. Detailed methodology is explained below:
Step 1: In-Depth Study of Secondary Sources:
A detailed secondary study was conducted to obtain the historical market size of the Generative AI Cybersecurity market through company internal sources such as annual reports & financial statements, performance presentations, press releases, etc., and external sources including journals, news & articles, government publications, competitor publications, sector reports, third-party database, and other credible publications.
Step 2: Market Segmentation:
After obtaining the historical market size of the Generative AI Cybersecurity market, we conducted a detailed secondary analysis to gather historical market insights and share for different segments & sub-segments for major regions. Major segments are included in the report as deployment, technology, application, end-user, and regions. Further country-level analyses were conducted to evaluate the overall adoption of testing models in that region.
Step 3: Factor Analysis:
After acquiring the historical market size of different segments and sub-segments, we conducted a detailed factor analysis to estimate the current market size of the Generative AI Cybersecurity market. Further, we conducted factor analysis using dependent and independent variables such as deployment, technology, application, end-user, and regions of the Generative AI Cybersecurity market. A thorough analysis was conducted for demand and supply-side scenarios considering top partnerships, mergers and acquisitions, business expansion, and product launches in the Generative AI Cybersecurity market sector across the globe.
Current Market Sizing: Based on actionable insights from the above 3 steps, we arrived at the current market size, key players in the global Generative AI Cybersecurity market, and market shares of the segments. All the required percentage shares split and market breakdowns were determined using the above-mentioned secondary approach and were verified through primary interviews.
Estimation & Forecasting: For market estimation and forecast, weights were assigned to different factors including drivers & trends, restraints, and opportunities available for the stakeholders. After analyzing these factors, relevant forecasting techniques i.e., the top-down/bottom-up approach were applied to arrive at the market forecast for 2032 for different segments and sub-segments across the major markets globally. The research methodology adopted to estimate the market size encompasses:
Primary Research: In-depth interviews were conducted with the Key Opinion Leaders (KOLs) including Top Level Executives (CXO/VPs, Sales Head, Marketing Head, Operational Head, Regional Head, Country Head, etc.) across major regions. Primary research findings were then summarized, and statistical analysis was performed to prove the stated hypothesis. Inputs from primary research were consolidated with secondary findings, hence turning information into actionable insights.
Market Engineering
The data triangulation technique was employed to complete the overall market estimation and to arrive at precise statistical numbers for each segment and sub-segment of the global Generative AI Cybersecurity market. Data was split into several segments and sub-segments after studying various parameters and trends in the deployment, technology, application, end-user, and regions of the global Generative AI Cybersecurity market.
The current & future market trends of the global Generative AI Cybersecurity market were pinpointed in the study. Investors can gain strategic insights to base their discretion for investments on the qualitative and quantitative analysis performed in the study. Current and future market trends determined the overall attractiveness of the market at a regional level, providing a platform for the industrial participant to exploit the untapped market to benefit from a first-mover advantage. Other quantitative goals of the studies include:
Q1: What is the Generative AI Cybersecurity market's current size and growth potential?
Q2: What are the driving factors for the growth of the Generative AI Cybersecurity market?
Q3: Which segment has the largest share of the Generative AI Cybersecurity market by end-user?
Q4: What are the major trends in the Generative AI Cybersecurity market?
Q5: Which region will dominate the Generative AI Cybersecurity market?
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