Another risk is that many shadow AI tools, such as those utilizing OpenAI’s ChatGPT or Google’s Gemini, default to training on any data provided. This means proprietary or sensitive data could already mingle with public domain models. Moreover, shadow AI apps can lead to compliance violations. It’s crucial for organizations to maintain stringent control over where and how their data is used. Regulatory frameworks not only impose strict requirements but also serve to protect sensitive data that could harm an organization’s reputation if mishandled.
Cloud computing security admins are aware of these risks. However, the tools available to combat shadow AI are grossly inadequate. Traditional security frameworks are ill-equipped to deal with the rapid and spontaneous nature of unauthorized AI application deployment. The AI applications are changing, which changes the threat vectors, which means the tools can’t get a fix on the variety of threats.
Getting your workforce on board
Creating an Office of Responsible AI can play a vital role in a governance model. This office should include representatives from IT, security, legal, compliance, and human resources to ensure that all facets of the organization have input in decision-making regarding AI tools. This collaborative approach can help mitigate the risks associated with shadow AI applications. You want to ensure that employees have secure and sanctioned tools. Don’t forbid AI—teach people how to use it safely. Indeed, the “ban all tools” approach never works; it lowers morale, causes turnover, and may even create legal or HR issues.
