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 survey of 573 technical leaders at companies with 100 or more employees, fielded across five parallel surveys of the agentic stack. Enterprises are now retrofitting to catch up with their own standards, and they are budgeting for it: Roughly six in 10 enterprises plan to switch or add vendors in each of five control layers within the next 12 months, and roughly a third — depending on the layer — plan to move within the quarter, the research finds.There are five main layers where enterprises are building: identity for agents (which agent is allowed to do what, under whose credentials); evaluati [...]
Enterprises can't fix their GPU waste problem because the fix makes the problem worse. Releasing idle capacity would improve utilization, but the same shortage driving GPU prices up is exactly wh [...]
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, [...]
Share one API key across five AI agents, and a single compromised agent inherits the reach of all five. The attacker immediately benefits from the accumulated permissions of every workflow that the ke [...]
On a recent work trip, I had plenty of things to worry about — but being able to recharge my two smartphones, laptop and iPad were not among my concerns. In my carry-on luggage, I had two medium-cap [...]
AI portfolios are expanding far faster than the ability to govern them across enterprises. Most organizations run a contested field of platforms, each claiming to be the “primary” AI layer; few co [...]
For the last 24 months, one narrative justified every over-provisioned data center and bloated IT budget: the GPU scramble. Silicon was the new oil, and H100s traded like contraband. Reserve capacity [...]