In the ever-evolving digital landscape, Shadow AI has emerged as a critical cybersecurity challenge for organizations worldwide. Shadow AI refers to the unsanctioned use of AI tools and platforms by employees without oversight or approval from their IT or security teams. While these actions often stem from a desire to enhance productivity or solve problems swiftly, they expose organizations to significant risks.
Brijesh Patel, Founder and CTO of SNDK Corp, emphasizes the gravity of this issue, stating: “Shadow AI has rapidly emerged as one of the most pressing cybersecurity concerns in today’s technological-first workplace. It refers to employees who use AI platforms and tools without the authorization or supervision of an organization’s IT or security departments. While often well-intentioned, this practice can jeopardize data security, regulatory compliance, and the organization’s overall digital integrity.”
Recent findings from Cisco’s 2025 Cybersecurity Readiness Index paint a concerning picture: Unregulated AI deployments, or shadow AI, pose significant cybersecurity and data privacy risks, as it is hard for security teams to monitor and control what they can’t see. 60% stated they lack confidence in their ability to identify the use of unapproved AI tools in their environments.
“According to Cisco’s 2025 Cybersecurity Readiness Index, a staggering 45% of organizations lack confidence in their ability to detect unregulated AI deployments, commonly known as Shadow AI. Even more concerning, 95% of organizations globally have experienced AI-related security incidents in the past year, yet only 7% have achieved a ‘Mature’ level of cybersecurity readiness. These numbers reflect a critical readiness gap that organizations can no longer afford to ignore,” adds Patel on the report.
Why Shadow AI is Hard to Detect
Brijesh Patel says that the core challenge with Shadow AI is its invisibility. “Employees often turn to unauthorized AI tools to address immediate needs, inadvertently risking data security by uploading sensitive information to unregulated platforms. This behavior can lead to data breaches, intellectual property theft, and regulatory penalties, creating vulnerabilities that organizations can ill afford,” he stated.
In the same vein, the Cybersecurity Readiness Index adds that threats to AI systems and secure data processes remain a blind spot for many companies, as this lack of understanding is overshadowed by the increasingly widespread adoption of AI, particularly GenAI.
How Organisations Must Address The Issue
Brijesh Patel believes that addressing this issue requires a comprehensive approach. “To combat the risks associated with Shadow AI, organizations must adopt a multi-pronged approach. First, it is essential to establish and enforce clear AI usage policies that specify which tools are permitted and under what conditions they may be used. Equally important is providing regular training to employees about potential risks of unauthorized AI use and encourage responsible innovation. Creating a transparent and collaborative culture is also crucial, ensuring that employees feel comfortable consulting IT before implementing new tools. Lastly, organizations should invest in robust AI governance and monitoring systems to detect and manage unauthorized AI usage across their technological landscape,” he emphasises.
