AgentsAugust 31, 2026via SiliconAngle
As AI agents take on enterprise tasks, companies face a new battle over access and control
Why it matters
As AI agents move from proof-of-concept to production workflows, the core tension isn't capability—it's governance. Platform teams now face a critical decision: how to give agents the access they need without creating security and compliance nightmares. This is reshaping how enterprise AI infrastructure gets built.
Key signals
- Enterprise private AI agents past pilot stage and into production
- Agents performing multi-step tasks: code generation, claims processing, business workflows
- New platform requirement: 'deny by default' runtime isolation and access control
- Broadcom/VMware introducing access-control mechanism for agent sandboxing
- Core problem: agent autonomy vs. infrastructure security and governance
- Platform teams now gatekeeping agent permissions and resource access
The hook
Not a pilot anymore. Enterprise agents are live — but companies are locking them down with 'deny by default' runtimes because nobody trusts unsupervised autonomous software.
Enterprise private AI has moved past the pilot stage, and the shift is exposing an awkward gap. Agents that write code, process claims and run business workflows need models, tools and data to be useful, yet few organizations want autonomous software wandering across their infrastructure unsupervise…