Generative AI Raises Enterprise Privacy, Security Risks Globally

The widespread adoption of generative AI across enterprises is accelerating rapidly, bringing significant benefits but also exposing new privacy and security risks. Companies often use customer data by default to improve AI models, raising concerns about data leakage and unauthorized use, especially as employees increasingly utilize public AI tools for sensitive work. Edge computing, critical for real-time AI applications like autonomous vehicles, introduces additional vulnerabilities, as edge devices are often less secure than centralized cloud infrastructure and more exposed to public access. Surveys indicate that nearly 70% of IT and security professionals view the evolving generative AI ecosystem as their top security concern, with data integrity and trustworthiness becoming paramount as attackers may inject false or biased data into AI models. Despite growing investments in AI-specific security tools, many organizations are adopting AI faster than they can secure it, underscoring the need for clearer data flow knowledge, stricter contract terms, and more robust monitoring and control mechanisms. Industry leaders emphasize the importance of knowing where data flows, limiting AI model access, and implementing strong data protection strategies to mitigate the risks posed by AI’s rapid integration into business processes.