Implications of Generative AI for enterprise security
Energy firm Southern Company were satisfied customers of Symantec® DLP for on-premises data loss prevention. When Southern Company also needed a robust cloud security product, they turned again to Symantec DLP Cloud. Download this case study to learn how Symantec DLP protects their cloud applications and data, ensures compliance, and provides them with a comprehensive security solution, with features such as OCR in the cloud, risk and user behavior analytics, and threat protection.
Generative AI refers to a subset of artificial intelligence that focuses on creating new content, such as text, images, or music, based on existing data. Unlike traditional AI, which often analyzes and processes data, Generative AI can produce original outputs, reshaping our understanding of what AI can achieve.
How does Generative AI impact enterprise security?
The adoption of Generative AI in enterprises requires a rethinking of security protocols. As this technology can generate realistic content, it poses risks such as deepfakes and phishing attacks, necessitating enhanced security measures to protect sensitive information and maintain trust.
What should companies consider when implementing Generative AI?
Organizations should consider the ethical implications, potential security vulnerabilities, and the need for robust governance frameworks when implementing Generative AI. It's essential to establish guidelines that ensure responsible use while maximizing the benefits of this transformative technology.

Implications of Generative AI for enterprise security
published by TMM Enterprises Group, Inc
TMM Enterprises Group, Inc. (TMM) has combined its consulting, technology and training services with capabilities to distribute industrial products and services including pipes, valves, fittings, flanges, electrical, instrumentation and control products used in the, oil, gas, refining, industrial, mining and construction industries and in water and treatment systems
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