Scaling Enterprise AI: From Bottlenecks to Breakthroughs | Step SF 2025

Описание: As enterprises move from pilot projects to full-scale AI deployments, challenges around data quality, compliance, and performance become unavoidable.

In this Step San Francisco 2025 panel, Gabriela de Queiroz (F02 Labs) moderates a deep discussion with Anand Vallamsetla (Resilience AI, The Why Man) and David Hefter (BlackRock) on how leaders are overcoming bottlenecks in enterprise AI - from synthetic data and governance frameworks to model validation and real-world deployment.

The panel explores:
• Overcoming data scarcity, bias, and high labeling costs.
• Using synthetic data and secure collaborations to accelerate AI training.
• Navigating privacy, HIPAA, GDPR, and governance frameworks.
• Closing the trust gap with explainability and human-in-the-loop systems.
• Future strategies for scalable, ethical enterprise AI adoption.

⏱️ Timestamps
00:08 - Introductions: Scaling Enterprise AI panel opens
02:31 - Biggest overlooked challenges in scaling AI
04:21 - Data bottlenecks, synthetic data & compliance
14:56 - From prototypes to deployment: guardrails & trust
20:54 - Aligning AI with business goals & startup challenges
30:13 - Future trends: AI agents & personalized healthcare

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