Shadow AI is the use of AI applications and tools without the explicit approval or oversight of an organization’s IT department. Shadow AI is becoming increasingly common in today’s fast-paced digital environment, and typically occurs in one of two ways:
1. Staff enable newly released AI features of existing and already sanctioned tools, without realizing the update necessitates a review by IT and security teams prior to deploying.
2. Departments or teams, driven by innovation and agility, use SaaS AI apps to improve productivity and meet their objectives, without waiting for central IT or security review and approval.
Shadow AI typically arises from the best intentions. Teams across organizations strive for efficiency and a competitive edge, leading them to adopt the latest AI technologies. This unauthorized use of AI can range from simple AI chatbots to complex machine learning models designed for data analysis.
The proliferation of easily accessible cloud-based AI services has only accelerated the Shadow AI trend, making it simpler for non-IT professionals to deploy advanced AI solutions without involving IT departments.
While AI apps can drive innovation and operational efficiency, Shadow AI harbors significant risks. The lack of oversight and integration with established IT security and governance frameworks can lead to data breaches from AI apps developed with few (or questionable) security protections, non-compliance with data protection regulations, and the unintentional leak of proprietary data. Shadow AI applications may also duplicate efforts or work at cross purposes with other IT initiatives, leading to operational inefficiencies and increased costs.
Shadow AI refers to the deployment and use of artificial intelligence tools and applications within an organization without formal approval or oversight from the IT department.
Shadow AI happens when teams or individuals seek to increase productivity or gain a competitive advantage by adopting AI SaaS solutions quickly or by enabling new AI capabilities in existing tools, bypassing the formal IT and security vetting process.
The unmonitored use of AI technologies can expose an organization to a variety of risks, including potential data breaches, non-compliance issues, operational inefficiencies, and possible leak of confidential information.
Organizations can manage Shadow AI by fostering open communication across the enterprise and establishing clear guidelines for AI adoption and usage. Implementing tools to discover, manage, and govern Shadow AI and shadow SaaS, like Grip, support compliance and a strong security posture.
AI Apps: A New Game of Cybersecurity Whac-a-Mole
Request a consultation and receive more information about how you can gain visibility to shadow IT and control access to these apps.
