For much of the past two years, the general belief in enterprise AI has been that more autonomy equals better performance. Build agents that can plan, decide, and act across multi-step workflows, and give them as much room to run as possible. That assumption is now being tested at scale, in real production environments — and in a lot of deployments it's failing. The companies that end up benefiting from agentic AI won't necessarily be the ones that have given their agents the most flexibility. They're the ones who create AI agents with specific responsibilities and make sure they operate within clear rules.Two numbers tell you almost everything about where agentic AI stands in mid-2026. By Gartner's own forecast, more than 40% of the agentic AI projects running today [...]
Across 116 enterprises, agents are in production and so are the incidents: A majority have already had a confirmed agent security event or a near-miss. Two-thirds of enterprises enforce scoped permiss [...]
Across 101 enterprises, the context feeding AI agents is failing often and repeatedly. Sixty-eight percent have traced a confident but wrong agent answer to missing or inconsistent business context in [...]
Across 107 enterprises, AI agents are being given real access to systems and data while the controls meant to contain them lag behind. More than half have already had a confirmed agent security incide [...]
Across 107 enterprises, agentic orchestration is not a choice of a single platform.The typical enterprise runs three orchestration platforms at once, and selects them for flexibility across models rat [...]
Across 170 enterprises, AI infrastructure has moved decisively into production — two-thirds now run AI workloads live and three in 10 run them at scale — while the ability to account for what that [...]
Visa's president of technology, Rajat Taneja, walked the VB Transform 2026 audience through aiming Anthropic's Mythos at Visa's own payment network. The model stitched minor weaknesses [...]
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 [...]
Across 107 enterprises, AI infrastructure spending is accelerating well ahead of the ability to see or steer its economics. Most organizations run their AI on a familiar base of hyperscalers and model [...]
Across 101 enterprises, the infrastructure that feeds AI agents their business context is being built faster than it can be trusted. Retrieval-augmented generation is already the default context sourc [...]