Keeping Pace With the Growth of Generative AI
The rapid proliferation of generative AI has forced organizations to prioritize developing and implementing the appropriate security protocols to help protect sensitive company, customer, and employee data in interactions with this technology. As companies work to establish what the right long-term security posture should encompass, many companies have taken to restricting access to generative AI for their employees. This approach, though well-intentioned, has inadvertently led to the emergence of Shadow AI. In this blog, we delve into what Shadow AI is, the challenges it poses, and how organizations can effectively manage it.
The Rise of Shadow AI
A massive survey conducted by Liminal reveals that 68% of organizations have chosen to fully or partially block employee access to generative AI tools. While this measure is meant to provide companies with time to comprehend the security risks associated with this technology, it has led to employee frustration due to being cut off from the productivity and efficiency gains that generative AI offers. As a result, employees are circumventing security policies and using generative AI anyway. A recent Salesforce study highlights that more than 50% of the survey participants using generative AI are doing so against organizational policy. As employees increasingly pursue independent access to these tools, the prevalence of Shadow AI continues to grow, and companies are encountering a mounting challenge in effectively managing it and the associated threats it poses.
The Challenges Related to Shadow AI
When employees use generative AI models that have not been vetted and approved, organizations have no visibility into what data is being shared, by whom, with which models, and how that data will be treated by those models going forward. This lack of oversight introduces several risks for companies:
Exposure of sensitive data
Generative AI requires data to learn and improve. If an employee inadvertently shares protected or confidential information - such as PII, PHI, PCI, or intellectual property - absent appropriate protections, this data can become vulnerable to misuse, theft, or leakage. This concern is compounded by the fact that 63% of employees reported they would be comfortable sharing at least some personal or proprietary information with generative AI tools, regardless of company policy.
Inability to appropriately protect against bias and non-compliance
Without oversight on which generative AI tools employees are using and what data governance rules apply, organizations cannot implement the necessary security protocols to protect against inputs or outputs that perpetuate biases, discriminatory practices, or breaches of regulatory compliance.
Lack of insight into high-value use cases
With no visibility into employee usage of generative AI, organizations are prevented from identifying highly effective applications of the technology that could benefit the entire company.
While unrestricted access to generative AI poses its own security challenges, the unintended consequences of limiting its use leads to a governance gap where organizations can’t confidently manage this technology. What’s the best course of action, then?
Preventing Shadow AI Starts With Providing Secure Access
So long as organizations attempt to prevent the usage of generative AI, employees will continue to find ways to bypass policy; it is too transformative a technology. The solution to preventing Shadow AI lies in providing secure, compliant access to generative AI.
Liminal helps mitigate Shadow AI by enabling organizations to safely say yes to generative AI.
The Liminal platform caters to both end-users and security personnel. It allows employees to harness the productivity advantages of generative AI in a non-disruptive manner that preserves the intended user experience. At the same time, security teams gain complete control over generative AI use within the organization, with full observability and the power to designate which users can access specific models, the types of data that can be shared, and what data governance rules apply.
With Liminal, you can begin addressing Shadow AI today. Getting started is easy, and deployment can be completed in under an hour. Click here to talk to the Liminal team.