The emergence of generative AI tools offers significant efficiency and innovation opportunities but also introduces various risks for organizations. It's vital to conduct a thorough risk assessment before adopting these technologies, rather than embracing them due to popularity. Existing policies should be adapted rather than creating entirely new frameworks, focusing on integrating GenAI risks into known procedures. Additionally, organizations must prioritize input security when using public LLMs and differentiate between various AI types and the risks they present.
The introduction of generative AI tools creates new opportunities for efficiency and innovation, but also poses risks that require thoughtful assessment and policy alignment.
Organisations often believe they need new policies for GenAI; however, extending existing frameworks to include GenAI scenarios is usually more effective.
Probative input security is often overlooked; employees must not input sensitive information into public LLMs, as it poses greater immediate risks than output accuracy.
It’s essential to identify different types of AI and their unique risks, rather than oversimplifying under a single AI policy that overlooks potential blind spots.
Collection
[
|
...
]