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As AI agents move from answering questions to making decisions and acting, businesses face a growing challenge of keeping accountability in step with the pace of change.
The social media giant tries to capitalize on, monetize its successful personal agent and maybe crack the business market. Chinese models go astray, like their U.S. counterparts.
A new case of an out-of-control AI model shows that enterprises should treat models and agents as toddlers that need supervision and explicit instructions.
The company’s new releases point to an AI market becoming more personal, with agents and models completing tasks, but enterprises still aren’t ready for this new phase of AI.
As agents take on more work for users, companies are deciding whether to let outside AI systems act on their platforms.
The agent can use enterprise business context for knowledge work. However, questions about cost and integration with other tools could be difficult for enterprises.
Process Intelligence helps organizations provide AI agents with the right context and data needed to know how their businesses run.
AI adoption in the public sector is on the rise, but data, legacy systems and governance remain barriers to effectively scaling the tech.
The AI chipmaker’s new safety platform adds controls around AI agents, while enterprises remain responsible for defining their authority and setting boundaries.
As a top cloud provider, Google has deep experience integrating its infrastructure with the other Google products that enterprises use.
The move comes as agentic AI plays an increasingly big part in business operations, sparking oversight concerns.
The generative AI vendor delayed the release of GPT-6.1 Astra after testing exposed new safety concerns, showing why AI models need continued evaluation and enterprise runtime controls.
It seems nearly everyone is calling for regulation. Chief among them is Anthropic, whose AI agents are also key troublemakers.
Nvidia’s new system is designed to contain rogue AI agents as companies race to secure increasingly autonomous systems. But it has not been proven yet.
As AI agents gain more authority to act on their own, recent incidents are exposing gaps in how enterprises monitor, control and intervene when agents cross established boundaries.
The neocloud vendor provides AI agents with access to data from its infrastructure management platform, helping developers troubleshoot slow or underperforming AI workloads.
Anthropic and OpenAI released new models this week, expanding the range of models enterprises can use for different workloads and raising new considerations for multi-model management.
While many organizations are accelerating their use of AI, they need to focus on governance and invest in trust, security and alignment.
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