As the adoption of AI technologies increases and matures, the focus will shift from exploration to time to market and productivity. Governing Enterprise data, scaling AI model development, providing a complete, collaborative platform and tools for rapid solution deployments are key focus areas for growing data scientist teams tasked to respond to business challenges. The drive for performance, productivity acceleration, smarter infrastructure resource utilization and management efficiencies can be seen in Enterprises across all industries and modernization initiatives. This talk will cover the challenges and innovations for AI at scale for the Enterprise focusing on the modernization of data analytics, the AI ladder and AI lifecycle, infrastructure considerations and conclude with Data and AI architecture use case scenarios.
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