Models, margins and the business decisions behind applied AI. Reporting and analysis from Fathom Tech.
As organizations rush to deploy AI systems across operations, security leaders warn that governance structures are lagging dangerously behind adoption rates, creating vulnerabilities in data protection and system oversight.
As AI coding assistants become standard across enterprise development teams, the need for high-quality test data has surged—but most synthetic data vendors haven't caught up with what agentic workflows actually require.
Artificial intelligence workloads are forcing data center operators to rethink infrastructure design across four critical subsystems, each facing distinct challenges in power, cooling, density and deployment speed.
As AI accelerates software development and deployment, organizations face a critical challenge: how to grant autonomous systems production authority without losing control. Trust in AI agents requires evidence, context, and governance—not just smarter models.