Shadow AI: The Hidden Risk of Artificial Intelligence

COMMENTARY

The rapid rise of artificial intelligence (AI) has cast a long shadow, but its immense promise comes with a significant risk: shadow AI. Shadow AI refers to the use of AI technologies, including AI models and generative AI (GenAI) tools outside of a company’s IT-sanctioned governance. As more people use tools like ChatGPT to increase their efficiency at work, many organizations are banning publicly available GenAI for internal use. Among the organizations looking to prevent unnecessary security risks are those in the financial services and healthcare sectors, as well as technology companies like Apple, Amazon, and Samsung.

The Challenge of Enforcing Policy

Unfortunately, enforcing such a policy is an uphill battle. According to a recent report, non-corporate accounts make up 74% of ChatGPT use and 74% of Gemini and Bard use at work. Employees can easily skirt corporate policies to continue their AI use for work, making it difficult for organizations to maintain control over their AI usage.

Key Considerations for Governance

To mitigate potential risks, organizations must prioritize governance. This includes:

• Committing to ethical business practices
• Embedding data privacy across all operations
• Remaining current on data privacy regulations

Mitigating Risks with Security Measures

As is often the case with most tech advancements, GenAI’s ease and convenience come with some fallbacks. While employees want to take advantage of the increased efficiency of GenAI and LLMs for work, CISOs and IT teams must be diligent and stay on top of the most up-to-date security regulations to prevent sensitive data from entering the AI system. Along with making sure workers know the importance of data protection, it is key to mitigate potential risks by taking all measures to encrypt and secure data from the start.

Conclusion

Shadow AI poses a significant risk to organizations, and it is essential to prioritize governance and security measures to mitigate these risks. By committing to ethical business practices, embedding data privacy, and staying current on data privacy regulations, organizations can minimize the risks associated with shadow AI and ensure a secure and efficient use of AI technologies.