Enterprises Must Rethink Data Architecture as AI Governance Complexity Grows

Executive Briefing

• Centralized data models are failing enterprises due to rising cloud egress costs, compliance risks, and AI-driven data volumes.
• Regulations like GDPR and the EU AI Act, fully enforced from August, complicate cross-border data movement for AI workflows.
• Experts recommend bringing compute and AI models to the data, rather than moving data to centralized repositories.
• Hybrid and multi-cloud architectures are becoming the default, requiring embedded governance from the start of AI projects.
• Decentralizing data storage while centralizing access management reduces latency, cuts costs, and supports sovereign AI strategies.