Three enterprise AI leaders from Archer, Demandbase, and Highspot reveal how top companies are implementing AI responsibly while navigating data privacy, bias prevention, and regulatory compliance challenges.

Topics Include:

• AWS Security GM Brian Shadpour hosts three AI leaders discussing responsible enterprise deployment
• Demandbase's Umberto Milletti explains tenant-based models ensuring first-party customer data remains confidential
• Highspot's Oliver Sharp uses behavior-specific feedback frameworks to eliminate bias in sales assessments
• Real-time AI evaluation proves challenging when assessing dynamic sales conversations and customer interactions
• Companies create "second-party data" networks where customers opt-in to share insights collectively
• Open-source models gain traction but require significant expertise for enterprise-grade implementation
• EU AI Act mandates human oversight, reshaping how companies design AI systems globally
• Archer's Kayvan Alikhani extends identity management principles from web applications to AI agents
• Unattended AI agents performing tasks autonomously create new security and accountability challenges
• Human-in-the-loop oversight remains essential, especially for high-stakes decisions affecting customers
• Future challenge: Determining when AI accuracy justifies removing costly human oversight
• Enterprise data hygiene becomes critical as AI systems need clean, reviewed internal data

Participants:

• Kayvan Alikhani - Global Head of Engineering- Emerging Solutions, Archer Integrated Risk Management
• Umberto Milletti - Chief R&D Officer, Demandbase
• Oliver Sharp - Co-Founder & Chief AI Officer, Highspot
• Brian Shadpour - General Manager, Security, Amazon Web Services

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