Browser security’s buying spree rests on one engine, without a clear Plan B
Browser security spending is surging, but most products still rely on Chromium. Why browser isolation offers a different security model as AI agents raise the stakes.
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Browser security spending is surging, but most products still rely on Chromium. Why browser isolation offers a different security model as AI agents raise the stakes.
Twice as many companies use OpenAI's agent orchestration platform as Anthropic's, VentureBeat Intelligence found in its September survey on agent orchestration. OpenAI holds that lead even though Anthropic may lead OpenAI on other important indicators.
AI agents need more than process knowledge to execute work reliably. They need company-specific context, governed workflows and controls that travel across systems.
Agentic AI requires more than access to data. Learn how a borderless data foundation can provide the context, trust and processing needed for autonomous agents.
If you sit in enterprise boardrooms today, the pressure weighing on CIOs comes down to two things: Velocity and ROI. Boards expect a mature agentic AI strategy and a definitive timeline for deploying autonomous systems that deliver measurable business impact.Read more
In multi-agent systems, agents can be individually correct and still produce a wrong result when they work together. One agent’s output becomes another agent’s context.
AI agents often struggle to assess their own progress and decide what to do next. They can waste compute resources following failed approaches, or they might overlook promising results or stop before completing a task.
Generative AI image generation has come a long way from the early days of DALL-E and Midjourney in 2021-2022. But even with the most advanced models now supporting generated text and complex infographics, perceptive human beings can still detect and recoil from the "AI look" that many of these…
Enterprises are increasingly hesitant to give AI agents carte blanche ability to deploy code or system changes to production without human approval, even as they continue investing in tools designed to evaluate agent reliability.Read more
Google is unveiling a new universal AI agent for the workplace that can research information, create documents, write code, coordinate other AI agents and complete tasks lasting hours or days — all while maintaining the same memory, business context and identity across different applications and…
In the enterprise, a confidently wrong AI agent answer can come from something more basic than the model: the agent doesn't know what the business means by its own terms, like what counts as revenue or which customer record is current.Read more
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VentureBeat Intelligence surveyed respondents at organizations with 100 or more employees in August about how they secure AI agents. OpenAI's guardrails are now the most common primary security layer for enterprise AI agents.
VentureBeat Intelligence surveyed respondents at organizations with 100 or more employees in its August VB Pulse survey. We asked about AI agent evaluation and production failures, whether agents may push changes to production with no human review, and which evaluation platforms enterprises…
VentureBeat Intelligence surveyed respondents at organizations with 100 or more employees in August 2026. We asked where their AI agents get business context and whether those agents had given wrong answers traced to that context, once or more than once.
For the August VB Pulse, VentureBeat Intelligence surveyed respondents from organizations with 100 or more employees. We asked which agent orchestration platforms they run and why, what they plan to adopt next, where they expect agent control to sit and how they stop runaway agent spending.Read more
The race to make AI agents cheaper and faster is moving beyond the models that write their answers. In the two weeks since TypeSafe AI introduced Jev, a model that chooses among predefined options instead of generating prose, developers have released a rush of competing decision models, many with…
AI agents can improve their behavior by developing reusable skills from successful and failed task attempts. But the systems that evolve those skills can lose what they learned along the way, forcing them to rediscover old failures.Read more
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