Keynote Outline
The adoption and application of AI is a hot topic, with many organizations anticipating that it can significantly reduce costs, provide insights, and create compelling customer experiences. However, AI/ML engines require data as the fuel for these outcomes to be realized and its imperative that this data is clean, trustworthy and without bias. Without a solid foundation of data management, AI is incomprehensible and unreliable. Learn how organizations are not only focused on providing data to AI to deliver outcomes, but are also leveraging AI to tackle issues of quality, accessibility, traceability, and democratization of data.
Key Takeaways
- The future of AI-powered data management
- Traditional approaches to data management are inefficient and can’t scale to meet today’s requirements
- AI needs data management! Learn how you can avoid unworthy AI/ML-generated insights
- EU AI Act and regulations. Learn how generative AI can assist regulatory compliance in architectures that self-document
- How AI can deliver automation and productivity to the data management landscape, enabling agility