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Netskope Embracing Generative AI: Business Transformation, Security, and Privacy Challenges

USA - North East
11:00 - 12:30 EST+118.07.24
Michael Ferguson


Generative AI presents significant opportunities for business transformation, but it also introduces substantial security and privacy challenges. This executive roundtable, led by Michael Ferguson, Director of Security Transformation, will address how organizations can leverage Generative AI to enhance business processes while ensuring robust security and data privacy. Discussions will cover governance of Generative AI, developing business-enabling use cases, handling regulated data with large language models (LLMs), controlling data flow, preventing legal issues such as copyright infringement, and protecting sensitive data. Participants will learn about strategic integration of AI, creating clear usage policies, and utilizing AI-driven security tools to counter evolving cyber threats. Join us to exchange insights and best practices for balancing AI innovation with cybersecurity resilience in today's digital landscape.

Discussion Points:

  1. Governance of Generative AI:

    • Establishing effective frameworks for safe and responsible AI use.
    • Developing comprehensive policies to manage AI-related risks.
  2. Creating Business-Enabling Use Cases:

    • Identifying and implementing AI use cases that drive business value.
    • Balancing innovation with risk mitigation.
  3. Handling Regulated Data with LLMs:

    • Best practices for managing regulated data in large language models.
    • Ensuring compliance with data protection regulations.
  4. Controlling Data Flow in LLMs:

    • Strategies for managing data flow in private and public environments.
    • Protecting sensitive information and maintaining data integrity.
  5. Preventing Legal Issues and Protecting Sensitive Data:

    • Addressing potential legal challenges such as copyright infringement.
    • Implementing measures to safeguard sensitive data from breaches.


Generative AI
Data Privacy
Large Language Models