Geoffrey Laissus

Geoffrey Laissus

Senior Director of Product Management Iron Mountain

Geoffrey Laissus is a product leader specializing in automation, AI, and enterprise software. With over a decade of experience in workflow automation and intelligent document processing, he focuses on building platforms that help organizations streamline complex operations and adopt emerging technologies.

Originally from France and based near New York City, Geoffrey brings a practical perspective on how AI, automation, and agentic systems can transform the way work gets done inside enterprises.

Agenda

9:00 AM The ROI of trust: Why secure AI is faster AI

The massive promise of AI in the back office, from automated invoices to employee records, is often clouded by security concerns. In today’s landscape, trust is the essential foundation for data integrity and operational speed. With models changing daily, the risk of sensitive and proprietary data leaking into public training sets has made data sovereignty a boardroom priority.

Mounting regulatory demands like GDPR and the rise of Agentic AI mean safety must go beyond a firewall; it requires a "security-by-design" framework that protects your intellectual property while maximizing the value of the latest technologies. True safety involves keeping data under your control, shielding sensitive information from public models, and maintaining the integrity of the information driving your organization's decisions.

In this session, GigaOm and Iron Mountain partner to explore how to leverage cutting-edge automation without compromising data sovereignty. You will discover how to build an AI ecosystem that remains secure, allowing your organization to scale agentic automation with confidence.

What you’ll learn:

  • Securing AI value: Isolate sensitive data to leverage the latest AI technologies while maintaining privacy.
  • Enforced integrity: Secure output quality and accuracy by enforcing human reviews at key process stages.
  • Agentic automation: Delegate "human-in-the-loop" tasks to self-learning agents via governed automation.