Webinar Description
Key Takeaways
- Addresses the growing challenge of unauthorised AI tool usage within enterprise environments
- Focuses on data leakage risks from employee prompts, file uploads and third-party integrations
- Relevant for IT security, compliance and governance professionals
- Covers detection methods and policy enforcement strategies for Shadow AI
Introduction
As generative AI tools become increasingly accessible, organisations face a significant governance challenge: employees are adopting AI applications independently, often without formal approval or oversight from IT and security teams. This phenomenon, commonly referred to as Shadow AI, presents substantial data protection risks that many enterprises are only beginning to understand. This demonstration session addresses how organisations can identify unauthorised AI usage, strengthen governance policies and regain control over sensitive business information.
The Shadow AI Challenge in Modern Workplaces
Shadow AI represents a natural evolution of the Shadow IT problem that has concerned security professionals for over a decade. However, the risks are amplified considerably. When employees use unapproved AI tools, they frequently input sensitive business data through prompts, upload confidential documents for analysis, or connect these tools to corporate systems through integrations that bypass standard security controls.
The challenge is compounded by the sheer variety of AI applications now available. From browser-based chatbots to AI-powered productivity extensions, employees can access powerful language models and data processing capabilities with minimal technical knowledge. Many of these tools retain user inputs for model training or store data in jurisdictions that may conflict with an organisation’s compliance requirements.
Data Leakage Vectors and Visibility Gaps
Traditional security monitoring often fails to capture AI-related data flows. Employees may paste proprietary code into coding assistants, upload financial reports to document summarisation tools, or share customer information with AI writing assistants. These interactions frequently occur through encrypted web connections that appear legitimate to network monitoring systems.
Third-party integrations present additional complexity. Many AI tools offer connections to cloud storage, email platforms and collaboration software. Once authorised by an individual user, these integrations can access far more data than the employee intended to share, creating persistent exposure that continues long after the initial interaction.
Who Should Attend
This session is designed for information security professionals, IT governance teams, compliance officers and data protection practitioners responsible for managing enterprise risk. Those developing or enforcing acceptable use policies for AI tools will find particular value in understanding the detection and remediation approaches covered. Security architects evaluating their organisation’s exposure to unsanctioned AI adoption will also benefit from the practical demonstration format.
Building Effective AI Governance
Addressing Shadow AI requires more than policy documentation. Organisations must develop visibility into which tools employees are actually using, understand the data flows associated with those tools, and implement controls that balance security requirements with legitimate productivity needs. The most effective approaches combine technical detection capabilities with clear governance frameworks that help employees understand which AI tools are approved and how to use them responsibly.