The Data Gravity Problem: Moving Data to AI vs. Moving AI to Data
SUSE, Friday, April 10th, 2026
AI promises unprecedented insights, automation and business value. But as organizations move from experimentation to production, we're hearing more about a fundamental architectural challenge: data gravity.
Data gravity refers to the tendency of large datasets to attract applications, services and infrastructure toward them. As data volumes grow, moving that data becomes increasingly expensive, slow and operationally complex.
In the world of AI, this creates a critical question:
Should we move massive datasets to centralized cloud AI platforms - or move AI workloads closer to where the data already exists?
The answer has major implications for cost, latency, performance, scalability and compliance.