运维效率成倍提高，安全智能体能否成为实现网安融合的“钥匙”？丨ToB产业观察

Core Insights - The emergence of large models has significantly transformed the security industry, leading to the adoption of AI-driven security solutions that enhance operational efficiency and threat detection capabilities [2][3][4] - The security industry is shifting from a product-centric approach to a service-oriented model, emphasizing integrated platform solutions over standalone products [3][4] - AI is expected to play a central role in the future of security operations, evolving from auxiliary tools to becoming the core of security systems [8][10] Industry Trends - AI and security are undergoing a three-phase evolution: initial application of machine learning, integration of generative AI for automated threat detection, and the current focus on security agents as central components of defense systems [3][8] - The demand for unified security solutions is increasing as organizations recognize the limitations of traditional product stacking in addressing complex security threats [4][5] - The concept of security operations is evolving, focusing on the systematic management of security measures rather than just individual product performance [5] Challenges - The security industry faces significant challenges regarding the proprietary nature and security of large models, including data poisoning and ensuring compliance and ethical standards [9][10] - Security agents must possess a deep understanding of industry-specific risk patterns, which is often lacking in general models, necessitating the integration of specialized knowledge and data [10] - Despite advancements, the outputs of security agents still require human confirmation to mitigate risks associated with AI's limitations in self-correction [10]