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Category — Harmonic Security
Shadow AI Discovery: A Critical Part of Enterprise AI Governance

Shadow AI Discovery: A Critical Part of Enterprise AI Governance

Sep 02, 2025 Data Privacy / SaaS Security
The Harsh Truths of AI Adoption MITs State of AI in Business report revealed that while 40% of organizations have purchased enterprise LLM subscriptions, over 90% of employees are actively using AI tools in their daily work. Similarly, research from Harmonic Security found that 45.4% of sensitive AI interactions are coming from personal email accounts, where employees are bypassing corporate controls entirely. This has, understandably, led to plenty of concerns around a growing "Shadow AI Economy". But what does that mean and how can security and AI governance teams overcome these challenges? Contact Harmonic Security to learn more about Shadow AI discovery and enforcing your AI usage policy.  AI Usage Is Driven by Employees, Not Committees  Enterprises incorrectly view AI use as something that comes top-down, defined by their own visionary business leaders. We now know that's wrong. In most cases, employees are driving adoption from the bottom up, often without ov...
Overcoming Risks from Chinese GenAI Tool Usage

Overcoming Risks from Chinese GenAI Tool Usage

Jul 25, 2025 Artificial Intelligence / Data Privacy
A recent analysis of enterprise data suggests that generative AI tools developed in China are being used extensively by employees in the US and UK, often without oversight or approval from security teams. The study, conducted by Harmonic Security, also identifies hundreds of instances in which sensitive data was uploaded to platforms hosted in China, raising concerns over compliance, data residency, and commercial confidentiality. Over a 30-day period, Harmonic examined the activity of a sample of 14,000 employees across a range of companies. Nearly 8 percent were found to have used China-based GenAI tools, including DeepSeek, Kimi Moonshot, Baidu Chat, Qwen (from Alibaba), and Manus. These applications, while powerful and easy to access, typically provide little information on how uploaded data is handled, stored, or reused. The findings underline a widening gap between AI adoption and governance, especially in developer-heavy organizations where time-to-output often trumps policy ...
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