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Explore the critical challenge of trusting AI model decisions in enterprise environments through this 19-minute conference talk that examines the invisible risks behind automated decision-making in safety-critical and revenue-sensitive applications. Discover how explainability, traceability, and robust guardrails drive AI adoption while protecting enterprise value through real-world case studies spanning manufacturing, telecom, and industrial IoT sectors. Learn a practical 3-step framework for operationalizing AI trust, gain insights from building guardrails in on-premises and hybrid systems, and master tools and techniques for debugging and explaining inferences at scale. Acquire a comprehensive blueprint for establishing trust between AI models, engineers, and executive stakeholders to ensure successful enterprise AI implementation.
