Controlling the AI Sprawl: Role-Based Guardrails and Governance with Airia
Most organizations already have an AI problem, they just do not know how big it is. See how to get visibility and control before shadow AI becomes a headline.
Watch On Demand – Controlling the AI Sprawl: Role-Based Guardrails and Governance with Airia
Lock AI down too hard and teams find workarounds. Open it up completely and you lose visibility into what data is moving and who has access to what. Either way, the real problem is not policy, it is visibility. You cannot govern what you cannot see.
This session shows what governed AI looks like in practice. Using a live demo, Airia and Bitovi show how the same AI assistant can serve two different roles safely, and how one gateway change is the difference between a data leak and a controlled, auditable workflow.
Key Takeaways:
- Shadow AI is a visibility problem, not a rule breaking problem. You cannot manage risk you cannot see.
- Access should be scoped by role, not by banning tools. One assistant, two employees, two completely different levels of access.
- Real time guardrails beat after the fact audits. Catching a leak in a log after the data is gone does not help. Blocking it at the gateway does.
- Governance belongs at the build layer, not in a policy memo. Route AI traffic through a governed gateway from day one, do not retrofit controls after adoption.
Watch on demand and see how to move from unmanaged AI use to actively governed AI, without slowing your teams down.