Chicago, Aug. 12, 2024 (GLOBE NEWSWIRE) -- The global Generative AI Cybersecurity Market is anticipated to grow at a compound annual growth rate (CAGR) of 33.4% over the course of the forecast period, from an estimated USD 7.1 billion in 2024 to USD 40.1 billion by 2030, according to a new report by MarketsandMarkets™. Browse in-depth TOC on "Generative AI Cybersecurity Market" 350 - Tables 60 - Figures 450 - Pages Download Report Brochure @ https://www.marketsandmarkets.com/pdfdownloadNew.asp?id=164202814 Generative AI Cybersecurity Market Dynamics: Drivers: Advanced AI-Driven Threats Proactive Defense Efficiency in Cybersecurity Improved Capabilities Restraints: AI Governance Concerns Shadow IT Risks Need for Strict Measures Securing AI Deployment Opportunities: Bridging the Skills Gap Efficiency in Entry-Level Roles Reduction in Incidents Untapped Opportunity List of Key Players in Generative AI Cybersecurity Market: Palo Alto Networks (US) AWS (US) CrowdStrike (US) SentinelOne (US) Google (US) MOSTLY AI (Austria) XenonStack (UAE) BigID (US) Abnormal Security (US) Adversa AI (Israel) Request Sample Pages: https://www.marketsandmarkets.com/requestsampleNew.asp?id=164202814 The generative AI cybersecurity market is growing rapidly and evolving significantly as more industries adopt generative AI technologies. By employing generative artificial intelligence systems for cyber security purposes, organizations will expand their market base. Major trends include leveraging generative AI to automate threat detection and response; enhance natural language interfaces for security products; and protect against sophisticated cyber threats such as deepfakes or social engineering attacks. This notwithstanding, some challenges like data privacy, security risks and the need for explainable AI persist thus requiring robust risk mitigation strategies. In order to strike a balance between innovation and security, organizations are likely to make huge investments into generative AI. Generative AI cybersecurity landscape has been impacted by several technologies. NLP and LLMs such as GPT-4/4o enhance threat detection systems and automate incident response by analyzing vast volumes of text data to detect security threats, phishing attempts, and anomalies in behavior. Tools for deepfake detection that are powered by AI tackle the challenges of verifying authenticity in synthetic media like video, audio, or images. Advanced security mechanisms and new cyber threats are created ...