GenAI Adoption Challenges in the Enterprise

Challenges in adapting GenAI in the enterprise

Overview

GenAI has quickly moved from concept to reality, with AI-powered apps often developed using GenAI itself. The C-suite now sees that GenAI's value lies in its data. Managing data ingestion, protecting privacy and integrating AI into InfoSec programs have become key priorities.

This whitepaper explores how GenAI can enhance customer experience, create personalized content, speed up DevOps and analyze data for trends. It also highlights the challenges, including security risks like data poisoning and model exfiltration. Whether developing proprietary GenAI models, licensing them or using third-party applications, securing AI usage is essential.

As the attack surface expands with hybrid work and cloud migration, security leaders face the dual challenge of more sophisticated cyberattacks and tighter budget constraints. This whitepaper provides insights into navigating these issues in the new era of GenAI.

Download the whitepaper

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