The uncontrolled use of artificial intelligence (AI) applications by employees is becoming a significant threat to cloud deployments, with many organizations unaware of the risks posed by these "shadow AI" tools. In one notable example, a large financial organization saw the number of unauthorized AI applications skyrocket from just a couple to 65 within a few months, with all of these tools training on sensitive corporate data, including personally identifiable information.

The use of shadow AI solutions, such as those built on ChatGPT, can inadvertently expose a company's intellectual property to public models, raising alarms about potential data breaches and regulatory violations. This highlights the critical need for centralized AI governance, which can mitigate risks while allowing employees to leverage sanctioned AI tools.

The rise of shadow AI is a fundamental challenge to traditional security perimeters, with cloud security administrators grappling with the implications of unauthorized AI applications. According to recent findings, over 12,000 such apps have already been identified, with 50 new applications emerging daily. Many of these tools bypass established security protocols, and security admins are often unaware of their existence.

The risks associated with shadow AI are profound, including the threat of data breaches, compliance violations, and the potential for proprietary or sensitive data to mingle with public domain models. Cloud computing security admins are aware of these risks, but the tools available to combat shadow AI are grossly inadequate, with traditional security frameworks ill-equipped to deal with the rapid and spontaneous nature of unauthorized AI application deployment.

To address this challenge, organizations must adopt a collaborative approach to governance, involving representatives from IT, security, legal, compliance, and human resources. This can help ensure that employees have access to secure and sanctioned AI tools, while mitigating the risks associated with shadow AI applications. Rather than banning AI tools outright, organizations should focus on educating employees on how to use them safely and productively.

Proactive monitoring of network traffic and data flows is also essential, with organizations needing to continuously audit AI usage within their networks to identify and address potential security risks. By adopting a centralized governance model and educating employees on the safe use of AI tools, organizations can navigate the challenges posed by shadow AI and reap the benefits of AI technologies.

The shadow AI challenge is a pressing concern for cloud computing security administrators, highlighting the need for a proactive and collaborative approach to governance and education. By working together, organizations can ensure the safe and productive use of AI tools, while mitigating the risks associated with unauthorized AI applications.