Organisations face uncharted challenges in securing and overseeing Generative AI (GenAI) solutions. Rapid technological evolution not only drives innovation but also opens new paths for adversaries. As GenAI advances, organisations must proactively measure and manage emerging risks to outpace shifting attack strategies.

Trust is critical—robust risk management and governance frameworks ensure AI is developed, deployed, and maintained responsibly. By embedding these practices throughout the AI lifecycle, organisations foster transparency, ethics, and stakeholder confidence in GenAI.

Ai Governance Framework

With AI capabilities rapidly evolving, organisations must establish a robust governance framework to define clear roles, responsibilities, and oversight. This framework should identify and address AI risks—especially new threats like deepfake phishing—and ensure data is properly managed. AI governance starts at the top, where leadership sets strategy, ensures compliance, and aligns AI initiatives with organisational goals.

Ai Risk Management Framework

AI risks emerge in two ways: threats to AI (e.g., data bias) and threats from AI (e.g., reduced security barriers). Traditional risk management strategies often don’t cover these evolving challenges. Clear usage policies, ongoing assessments, and dedicated frameworks are crucial to address issues like bias, privacy breaches, misinformation, and copyright concerns. By understanding and managing these risks from the start, organisations can ensure responsible AI adoption.