Generative AI can be used in a variety of applications, including image and speech recognition, natural language processing, and cybersecurity.
In the context of cybersecurity, generative AI can be used to learn from existing data or simulation agents and then generate new artifacts. For example, generative cybersecurity AI can be used to develop secure application development assistants or security operations chatbots. These applications can help organizations improve their security and risk management, optimize resources, defend against emerging attack techniques, or even reduce costs.
However, there are also risks associated with the consumption of GenAI applications. Overoptimistic GenAI announcements in the security and risk management space could drive improvements, but also lead to waste and disappointments. CISOs and security teams need to prepare for impacts from generative AI in four different areas: defending with generative cybersecurity AI, working with organizational counterparts who have active interests in GenAI, applying the AI trust, risk and security management (AI TRiSM) framework, and reinforcing methods for assessing exposure to unpredictable threats.