An enterprise AI agent answers with total confidence, but the number is wrong. Nobody catches it until someone traces it back to a stale metric definition or a document the retrieval system never pulled. The model did not fail. The context it was given did.In the past six months, 57% of enterprises traced a confident but wrong AI agent answer to missing or inconsistent business context, and 31% said it happened more than once, according to a VB Pulse June 2026 survey of 101 qualified enterprises with more than 100 employees.The reason is not hard to find. Retrieval over documents is the default way agents get business context for 38% of enterprises, nearly double the next closest approach. The way most enterprises choose a retrieval system compounds the problem. Ease of ingestion and opera [...]
Enterprise companies are running AI agents ahead of the controls needed to manage them — and they deployed that way knowingly. That is the central finding from VentureBeat Research's June surve [...]
New VB Pulse data shows Microsoft and OpenAI leading enterprise agent orchestration, but Anthropic’s first measurable foothold points to a larger fight over who controls the infrastructure where AI [...]
Enterprise AI agents have a new production failure mode, and it is not the model. As enterprises move from single-layer RAG to hybrid retrieval architectures, the same underlying data produces differe [...]
Redis built its name as the caching layer that kept web applications from collapsing under load. The problem it is targeting now has the same structure but is harder to solve: production AI agents fai [...]
For the first time on a major AI platform release, security shipped at launch — not bolted on 18 months later. At Nvidia GTC this week, five security vendors announced protection for Nvidia's a [...]
When Miro’s data team pointed AI agents directly at its Snowflake environment, the agents got the wrong answer more than 65% of the time. The problem wasn’t the model — it was context. With more [...]
Building a context layer between enterprise data stores and AI agents is bespoke work, with no standard service to automate or maintain the graphs over time. Amazon is making a direct play to change t [...]
Amazon Web Services on Tuesday launched one of the most consequential enterprise AI plays in the company's 20-year history, simultaneously bringing OpenAI's most powerful models to its Bedro [...]
A rogue AI agent at Meta passed every identity check and still exposed sensitive data to unauthorized employees in March. Two weeks later, Mercor, a $10 billion AI startup, confirmed a supply-chain br [...]