Artificial intelligence seems to be creating increasingly interconnected enterprise ecosystems, expanding the complexity of how organizations govern technology across their operations. As AI becomes more deeply embedded in critical workflows, maintaining visibility into system dependencies appears to emerge as a significant leadership consideration. According to an AI sovereignty study, 91% of surveyed executives said they do […]<br /> This story continues at The Next Web [...]
Traditional software governance often uses static compliance checklists, quarterly audits and after-the-fact reviews. But this method can't keep up with AI systems that change in real time. A mac [...]
Here is a scenario that should concern every enterprise architect shipping autonomous AI systems right now: An observability agent is running in production. Its job is to detect infrastructure anomali [...]
Salesforce launched a suite of monitoring tools on Thursday designed to solve what has become one of the thorniest problems in corporate artificial intelligence: Once companies deploy AI agents to han [...]
The most expensive AI failure I have seen in enterprise deployments did not produce an error. No alert fired. No dashboard turned red. The system was fully operational, it was just consistently, confi [...]
Presented by RubrikEnterprise cybersecurity is facing a fundamental speed problem. Frontier AI models are now enabling autonomous attacks that can move from initial access to full system breakout in a [...]
Two-thirds of enterprises have hedged their AI model strategy, and the past few weeks of controversy around Anthropic’s Claude Fable 5 model showed why that posture has gone mainstream. On June 12, [...]
Over the past two decades, technical debt meant outdated architecture, messy code, and poorly maintained documentation. That definition is no longer sufficient in the AI era, where failure modes are m [...]