The practice of employing “Shadow AI” essentially involves projects or initiatives developed within an organization without official approval or in the absence of support from IT departments or other entities responsible for managing AI technology. These projects are often undertaken by individual employees or small teams using ad-hoc AI tools and techniques to address specific needs. While the use of AI systems can offer numerous advantages, such as rapid innovation or increased operational efficiency, it also entails a series of significant risks that must be carefully managed.
One of the most critical risks associated with Shadow AI use involves the uncontrolled handling of data, as these systems may process sensitive categories of personal data in ways that do not comply with legal regulations or the company’s privacy policies. Furthermore, unauthorized AI usage can lead to data security risks, as these systems may not adhere to cybersecurity standards. Additionally, a significant implication of Shadow AI usage concerns the operation of systems without adequate monitoring, audit mechanisms, or accountability.
Consequently, to prevent or address potential negative consequences arising from employee use of Shadow AI, employers need to implement a set of appropriate measures. In this regard, updating the internal regulations, drafting and implementing a policy, and establishing an approval process would be effective. This process should include a risk and benefit assessment, during which employees are required to seek official approval for initiating projects or initiatives involving AI technology.
In this context, the measures taken by employers regarding the prevention and combat of illegitimate Shadow AI use should focus on updating internal documentation related to labor relations, as well as documentation concerning personal data protection and IT security.
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