The rise of Generative AI has transformed the enterprise landscape, with Large Language Models (LLMs) powering SaaS copilots and custom-built applications. Yet, two years into this GenAI revolution, businesses face a key challenge: balancing innovation with robust security.

From data privacy concerns to unintended information exposure, early adopters like Microsoft Copilot have revealed critical gaps in managing complex access permissions. Building enterprise-grade AI applications only adds to the complexity, requiring rigorous data controls and governance to mitigate risks.

In this session, we’ll explore:

• Emerging security challenges in AI and their impact on cybersecurity teams

• OWASP Top 10 for LLMs: What’s hype, and what’s real?

• Why traditional approaches, like LLM Firewalls, fall short.

• The essential controls and frameworks needed to secure GenAI deployments.

Whether you’re deploying AI in SaaS platforms or building in-house solutions, this session will arm you with the knowledge to address the toughest security challenges and unlock the full potential of Generative AI – without compromise.