Generative AI in Cybersecurity Market Size, Share Global Analysis Report, 2024 – 2032

Industry Insights

[221+ Pages Report] According to Facts & Factors, the global generative AI in cybersecurity market size was around USD 7.80 billion in 2023 and is predicted to grow to around USD 74.98 billion by 2032, with a compound annual growth rate (CAGR) of roughly 28.59% between 2024 and 2032.

Market Overview

Generative AI in cybersecurity is the use of improved ML models, such as different neural networks and GPT, to improve security systems. These AI solutions can produce insights, forecast impending vulnerabilities, and detect threats for businesses.

The global market is projected to grow substantially in the coming years as governments and businesses aim to enhance security protocols, prevent cyberattacks, and automate defense systems. A few other key drivers of generative AI in cybersecurity market include the growth in data breaches and cyberattacks and increasing demand for automation.

With the increasing number of ransomware attacks, cybercrimes, and data breaches, the demand for improved cybersecurity solutions is also increasing. The conventional techniques are comparatively less efficient than modern ones, triggering businesses and companies to use AI-based cybersecurity tools.

Furthermore, the volume and complexity of cybersecurity threats and data have increased the demand for automation. Also, improvements in ML and AI are enabling AI solutions to be more precise, efficient, and adaptable. These improvements are driving the global market growth.

Nevertheless, high initial investment and data privacy concerns are a few key barriers to the industry's growth. Implementing generative AI tools may be costly, mainly for smaller businesses. The cost of installing, along with the need for a proficient workforce to maintain and operate these systems, may refrain businesses from investing in and adopting them.

Generative AI systems usually need huge amounts of data to perform efficiently. This may increase privacy risk since sensitive data should be managed carefully to avoid misuse and illegal access, mainly in regulated settings.

Yet, the market will witness remarkable growth owing to opportunities like AI-based incident response automation. Businesses may use generative artificial intelligence to automate response time, which reduces the time required to detect and mitigate risks. This aids in the speedy containment of different malicious activities.

Generative AI can also effectively imitate a broader range of attack conditions, which allows companies to conduct training activities and enhance their security. This aids security groups to stay alert to diverse attack vectors.

Key Insights:

• As per the analysis shared by our research analyst, the global generative AI in cybersecurity market is estimated to grow annually at a CAGR of around 28.59% over the forecast period (2024-2032)
• In terms of revenue, the global generative AI in cybersecurity market size was valued at around USD 7.80 billion in 2023 and is projected to reach USD 74.98 billion by 2032.
• The generative AI in cybersecurity market is projected to grow significantly, owing to changing consumer preferences, global expansion of the supply chain, and rising warehouse automation.
• Based on type, the threat detection & analysis segment is expected to lead the market, while the network security segment is expected to register considerable growth.
• Based on technology, the Deep Neural Networks (DNNs) segment is the dominating segment among others, while the Generative Adversarial Networks (GANs) segment is projected to witness sizeable revenue over the forecast period.
• Based on end-use, the Banking, Financial Services, and Insurance (BFSI) segment is expected to lead the market compared to the government & defense segment.
• Based on region, North America is projected to dominate the global market during the estimated period, followed by Europe.

Growth Drivers

• Growing demand for automation in cybersecurity boosts the generative AI in cybersecurity market growth

With the complexity and volume of cyber threats rising, companies demand automation to manage their cybersecurity strategies. Generative AI can rightly automate severe processes like threat detection, monitoring, and incident response, thus reducing errors and improving efficacy.

According to a survey by IBM in 2024, approximately 44% of respondents sought AI-based solutions to automate their security functions. This denotes the rising recognition of AI's capacity to simplify complicated tasks and offer accurate and faster security responses.

Automation by generative AI aids in lowering the pressure on cybersecurity groups and enables companies to manage threats at scale. This contributes to speedy adoption in the cybersecurity domain.

• The growing need for rapid response and threat detection in real-time fuels the market growth

Another key driver of the global generative AI in cybersecurity market is the growing need for rapid response and threat detection in real-time. Cyber threats are becoming complex and harder to detect. Generative AI outshines this section by speedily studying huge quantities of data and offering immediate alerts when doubtful activity is identified.

A 2023 report also revealed that 68% of breaches were identified just a few months after the event. AI-driven detection (real-time) systems are important for closing this gap.

In December 2024, an AI-based cybersecurity system by Microsoft detected and blocked more than 80% of impending real-time malware. This presents the effect AI can have on speedy threat alleviation.

Restraints

• Threat of adversarial attacks on AI systems hampers the generative AI in cybersecurity market progress

One of the key risks of using generative artificial intelligence in cybersecurity is the possibility of adversarial attacks. These attacks specifically aim at the AI systems by serving them hostile input to handle their responses. As cyber criminals are largely using AI to build mature attacks, AI-enabled security solutions may become susceptible to these strategies.

Researchers explored the fact that cybercriminals used generative adversarial networks, or GANs, to introduce bogus attack simulations to avoid AI-based defense systems. This rising trend is resulting in elevated concerns regarding the weakness of AI-based cybersecurity systems.

Furthermore, the risk of adversarial highlights the trust in AI-based systems as reliable and secure tools for defending against cyberattacks. This may slow down the use of generative AI cybersecurity, mainly in crucial industries like BFSI, government, and defense.

Opportunities

• Tailored security solutions as per industry needs is an opportunity for generative AI in cybersecurity market growth

Generative artificial intelligence can modify cybersecurity solutions depending on an organization’s needs, threat profile, and industry risks. This alteration may improve the efficiency of security systems like government, finance, and medical.

The ability to tailor cybersecurity solutions for certain industries or companies offers prospects, mainly in regulated industries where obeying standards of data protection is important. Generative artificial intelligence aids in designing solutions that are effective, adaptive, and exceptionally suitable to threats faced by every industry.

Challenges

• Lack of trained workforce in cybersecurity and AI limits the growth of generative AI in cybersecurity market

One key challenge in using generative AI in cybersecurity is the lack of expert labor who can effectively manage, integrate, and operate these improved AI-based systems. Cybersecurity, mainly AI-based cybersecurity, needs professionals who are competent in cybersecurity practices and AI technologies.

The lack of a competent workforce lowers the scaling and deployment of generative AI in cybersecurity, as businesses find it difficult to retain and find talent capable of handling these developed tools.

Report Scope

Segmentation Analysis

The global generative AI in cybersecurity market is segmented based on type, technology, end-use, and region.

Based on type, the global generative AI in cybersecurity industry is divided into threat detection & analysis, adversarial defense, insider threat detection, network security, and others.

In 2023, the threat detection & analysis segment registered a notable share of the generative AI in cybersecurity market owing to its increasing use to study huge datasets in real-time, identify patterns, and detect rising threats. All these are performed accurately and faster than conventional methods.

As the development and maturity of cyber threats increase, businesses prefer solutions that can efficiently mitigate and detect threats aggressively. Generative AI models outshine in anomaly detection and pattern recognition, thus increasing their suitability for identifying novel and complex threats.

Based on technology, the global generative AI in cybersecurity industry is segmented as Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), Reinforcement Learning (RL), Deep Neural Networks (DNNs), Natural Language Processing (NLP), and others.

The Deep Neural Networks (DNNs) segment held a major market share in the previous years and will progress considerably owing to their broader use. DNNs are the largely used technology owing to their ability to process massive quantities of data and detect complicated patterns for anomaly detection, threat detection, and classification of malware. They are more effective for processing in real-time, thus gaining prominence as the most preferred choice for businesses asking for rigorous threat management.

Based on end-use, the global market is segmented as Banking, Financial Services, and Insurance (BFSI), healthcare & life sciences, government & defense, retail & e-commerce, manufacturing & industrial, IT & telecommunications, energy & utilities, and others.

The Banking, Financial Services, and Insurance (BFSI) segment held the majority of the market share in the past years and is projected to lead the market over the coming years as well. The said sector is commonly targeted by cyber criminals owing to huge quantities of confidential and sensitive financial information.

Hence, financial institutions actively spend on AI-based solutions to detect fraud activities, safeguard their networks, and obey strict regulations. AI technologies are mainly used to detect fraud, secure online transactions, and manage risk.

Regional Analysis

• North America to witness significant growth over the forecast period

North America registered a considerable share of the global generative AI in cybersecurity market in 2023 and is projected to continue its dominance over the forecast years as well. The remarkable growth is attributed to the rising threat of cybersecurity, improvements in technology, and growing investments.

North America, mainly the United States, is prone to cyberattacks, comprising data breaches, ransomware, and hacking (state-sponsored). This majorly propels the need for improved and high-tech AI-based cybersecurity tools.

Moreover, the region is a hub for the leading technology firms and innovators in artificial intelligence, like IBM, Google, and Microsoft, which are propelling the growth and incorporation of generative AI in several applications. Also, the region holds a leading share of the industry for global investments.

In 2024, the region held 40% of the overall market share for AI-based solutions in cybersecurity.

Europe is projected to progress as the second-leading region in the global generative AI in cybersecurity industry owing to the rising cyber threats, regulatory pressure, and rising adoption of AI in businesses. Europe experiences rising cyberattacks on crucial infrastructure, enterprises, and government bodies. This fuels the demand for AI-based solutions in cybersecurity. Most stringent data protection rules and GDPR have elevated the need for improved measures, comprising AI solutions to guarantee secure and compliance-sensitive data.

Furthermore, the rising adoption of these advanced solutions is notably driving investments and AI security tools in industries like healthcare, BFSI, and government

Competitive Analysis

The global generative AI in cybersecurity market is led by players like:

• Darktrace
• CrowdStrike
• Palo Alto Networks
• Fortinet
• IBM Security
• FireEye
• Check Point Software Technologies
• Trend Micro
• SentinelOne
• McAfee
• Cisco Systems
• SonicWall
• Microsoft
• Google Cloud
• Qualys

Key Market Trends

• AI-based threat detection:

Generative AI, mainly tools like Generative Adversarial Networks, Deep Neural Networks, and more, are transforming the way threats are identified in cybersecurity. These models study huge datasets to detect anomalies and patterns that might denote possible cyberattacks like phishing, malware, or (APT) Advanced Persistent Threats.

• Automated incident response:

With the growing number of cyber threats, businesses are shifting toward automated incident response solutions operated by generative AI. These systems neutralize and detect threats autonomously without waiting for interference from humans. This majorly limits damage from cyberattacks and reduces response time.

The global generative AI in cybersecurity market is segmented as follows:

 By Type Segment Analysis

• Threat Detection & Analysis
• Adversarial Defense
• Insider Threat Detection
• Network Security
• Others