Challenges and Takeaways of Managing AI Workloads on Cloud

Explore the complexities of deploying and managing AI workloads in cloud environments through this 17-minute conference talk from Conf42 LLMs 2025. Discover the fundamental challenges that arise when transitioning AI models from development to production, including data management issues, workflow optimization, and the critical gap between development and production environments. Learn about essential tools for cloud-native AI deployment, with particular focus on Kubeflow for seamless AI model deployment and management. Examine best practices for data governance and organizational culture changes needed to support AI initiatives effectively. Understand how AI gateways and model monitoring systems can enhance your deployment strategy, while exploring the role of platform engineering in scaling AI operations. Gain insights into emerging trends and future developments in AI development workflows, concluding with actionable takeaways for successfully managing AI workloads in cloud environments.