Generative AI has fundamentally changed the makeup of the enterprise IT infrastructure. Its introduced new opportunities and innovations and influenced new requirements to secure and govern adoption while maintaining business continuity. As businesses integrate private and public AI applications into day-to-day operations, the complexity, volume, and sensitivity of data being used for training and prompting demands novel solutions.
At the same time, IT and security operations have benefitted from stronger, generative AI-influenced cybersecurity outcomes through anticipatory and predictive insights, tailored remediation recommendations, script decoding, and custom automations. These two trends — happening in parallel — are easily contrasted as “Cybersecurity for AI Enterprise Adoption” and “AI Applications Serving Cybersecurity Teams.”
AI Transformation Necessitates Risk Management
AI transformation necessitates risk management and security by design. Data protection and content analysis become table stakes as internal and threat actor-driven risk scales. Concerns like sensitive data exposure, shadow AI, compliance and policy violations, rogue AI instances,…
