2025 Data Risk Report Reveals Billions of Sensitive Records at Risk from AI Tools

Billions of sensitive enterprise records are at risk as AI-powered tools and cloud platforms drive a surge in data exposure. The 2025 Data Risk Report reveals a dramatic escalation in data loss incidents linked to generative AI, SaaS, email, and file-sharing services.

AI apps like ChatGPT and Microsoft Copilot contributed to millions of data loss incidents in 2024, with social security numbers and other sensitive information frequently exposed. Enterprises now face unprecedented challenges in securing data as digital transformation accelerates.

How are AI tools like ChatGPT and Copilot fueling massive data loss?

Generative AI tools are a major source of data leakage, often unintentionally. Employees may input confidential prompts or share sensitive files, which can be stored or processed outside the organization’s control. In 2024, AI apps were responsible for millions of data loss events, especially involving personal identifiers.

Email remains a persistent risk, with nearly 104 million transactions leaking billions of sensitive records. File-sharing platforms also saw 212 million data loss incidents, highlighting the risks of widespread collaboration and remote work.

Did you know?
In 2024 alone, enterprises experienced more than 872 million SaaS data loss violations and billions of sensitive records leaked through email and file-sharing apps, according to the 2025 Data Risk Report.

What security strategies can enterprises deploy to counter AI-driven risks?

The report emphasizes the need for a unified, AI-driven approach to data security. Traditional tools are no longer enough. Enterprises should adopt platforms that provide full visibility, real-time monitoring, and automated data loss prevention across endpoints, cloud, and AI applications.

Zero Trust security models are now essential. By continuously verifying user and device trust, enforcing least-privilege access, and segmenting sensitive data, organizations can limit the impact of both accidental and malicious data leaks.

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AI-powered data loss prevention is critical for modern enterprises

AI-powered security tools can automatically discover, classify, and protect sensitive data in motion and at rest. Inline data loss prevention (DLP) inspects web, email, BYOD, and generative AI app traffic, blocking unsafe prompts and unauthorized sharing in real time.

Browser isolation and safe rendering technologies allow employees to use AI tools without risking data exfiltration. These controls restrict clipboard use, file uploads, and downloads, ensuring sensitive information never leaves the organization’s control, even during remote work.

Unified security and real-time monitoring are key in the AI era

Continuous monitoring of SaaS configurations, user behavior, and AI interactions is vital. AI-driven analytics can detect anomalies, flag excess permissions, and block risky activities before data is lost. End-to-end incident response, managed from a single console, streamlines defense against evolving threats.

With billions of records at risk and AI-powered attacks growing in sophistication, enterprises must rethink their security strategies. Only a unified, proactive approach can protect sensitive data and build digital trust in the era of AI.