The piece also highlights the role of back-office modernization in building trust in data, as well as the symbiotic relationship between AI and data. While AI can automate data management tasks and uncover patterns in data, data remains valuable even without AI. Understanding this dynamic is key to harnessing the true transformative power of AI, the article concludes.
Key takeaways:
- The quality and quantity of data ingested by an AI system are crucial to its effectiveness. Bad quality data can lead to incorrect outputs and negatively affect future computations and predictions.
- Data doesn't inherently need AI to exist or be valuable. Organizations should not ignore the importance of data management and data quality in the pursuit of AI.
- Trust in data comes from real-time, indisputable data observability. It's important to reexamine back-office data management systems to bring trust and transparency to the entire data life cycle.
- The relationship between AI and data is symbiotic. While AI relies heavily on data for its operation and evolution, data can also benefit from AI in several ways, such as automating data management tasks and uncovering patterns and insights in data.