The Rise and Risks of Shadow AI

Shadow AI is becoming an increasingly serious problem.

Employees are not only flocking to use third-party AI services like ChatGPT but also importing models and building internal AI systems without informing their enterprise operations teams. Both scenarios are on the rise, and many organizations are oblivious to the associated risks.

Shadow AI refers to the internal use of AI tools and services without the knowledge or approval of enterprise oversight teams (such as IT, legal, cybersecurity, compliance, and privacy teams).

The Growing Threat of Shadow AI

According to a recent report by Cyberhaven, the surge in AI usage and its accompanying risks are alarming:

• AI is Accelerating: Corporate data input into AI tools surged by 485%.

• Increased Data Risks: Sensitive data submission jumped by 156%, led by customer support data.

• Threats are Hidden: The majority of AI usage occurs on personal accounts, lacking enterprise safeguards.

• Security Vulnerabilities: There's an increased risk of data breaches and exposure through the use of AI tools.

These statistics illustrate that the risks are real and growing. Organizations must act now to mitigate these dangers.

Steps to Mitigate Shadow AI Risks

1. Establish Clear Policies for AI Use and Development: Organizations need to create comprehensive policies that govern the use and development of AI. These policies should detail what is permissible, what is not, and the steps required for compliance.

2. Define and Communicate an AI Ethics Posture: Developing a clear AI ethics framework is crucial. This framework should be communicated across the organization to ensure that all employees understand the ethical implications of AI usage and development.

3. Incorporate Cybersecurity, Privacy, and Compliance Teams Early: Involving these teams at the outset of AI projects can help identify and mitigate risks before they become significant issues. Their expertise is essential in ensuring that AI initiatives comply with all relevant regulations and standards.

4. Drive Awareness and Compliance through Training: Including AI topics in employee and vendor training programs is vital. These training sessions should cover the risks associated with AI, the organization's policies, and the importance of adhering to them.

5. Foster a Culture of Collaboration and Transparency: Building awareness and collaboration across the organization is key. Encouraging open communication about AI projects can help ensure that they are aligned with enterprise oversight requirements and reduce the likelihood of Shadow AI occurrences.

As the saying goes, "Do what is great while it is small." A little effort now can help avoid serious mishaps in the future. By proactively addressing the challenges posed by Shadow AI, organizations can leverage the tremendous benefits of AI while minimizing risks.

The Importance of Controlled AI Implementation

AI has the potential to transform businesses, drive innovation, and improve efficiency. However, these benefits can only be fully realized if AI is implemented in a controlled and secure manner. Here are a few additional considerations:

• Regular Audits and Monitoring: Conduct regular audits of AI usage within the organization. Monitoring tools can help identify unauthorized AI activities and ensure compliance with established policies.

• Risk Assessment: Perform thorough risk assessments for all AI projects. This includes evaluating the potential impact on data security, privacy, and compliance.

• Stakeholder Engagement: Engage stakeholders from various departments, including legal, compliance, and IT, to provide a holistic view of AI projects and ensure that all perspectives are considered.

• Incident Response Plan: Develop and maintain an incident response plan specifically for AI-related breaches or issues. This plan should outline the steps to be taken in the event of a data breach or other security incident involving AI.

By taking these steps, organizations can create a robust framework for AI governance that mitigates the risks associated with Shadow AI. This proactive approach will not only protect sensitive data and ensure compliance but also foster a culture of responsible AI usage.

In conclusion, Shadow AI is a growing problem that requires immediate attention from organizations. By establishing clear policies, defining an AI ethics posture, incorporating key teams early, driving awareness through training, and fostering collaboration, organizations can mitigate the risks associated with unmonitored AI usage. Leveraging AI in a controlled and secure manner will enable businesses to harness its benefits while safeguarding against potential threats.