Enterprise AI Will Be a Network, Not a Monolith`

Enterprise AI is argued to be better served by networks of specialized language models and agents than by a single large, centralized model, because domain-specific tasks can use less compute, lower costs, and more targeted context while reserving larger models for complex work. As these agents simultaneously read, update, and act on shared business data, database performance becomes central to maintaining current, consistent information and avoiding latency that can compound across automated workflows. The passage presents SingleStore’s distributed SQL architecture as suited to this high-concurrency mix of transactional and analytical workloads. It also advocates retaining enterprise data in open formats such as Apache Iceberg rather than moving all information into proprietary platforms, allowing models, agent frameworks, and operational systems to evolve independently. Overall, it favors a composable AI architecture intended to balance real-time performance, accuracy, cost management, and data portability over tightly coupled AI monoliths.

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