Robots detect anomalies, adjust parameters, stop lines. Decisions that were always human. How far does autonomy extend? Who is responsible when a system decision causes an incident?
Autonomous industrial robots make real-time decisions — stopping a production line, modifying a critical parameter, redirecting a logistics flow. These decisions have direct financial, operational and sometimes regulatory consequences.
In most deployments, this boundary has never been defined at executive level. It formed by default during technical configuration. Leadership does not know precisely what it has delegated to its systems.
The question is: did you decide to whom, and under what conditions? The EU AI Act classifies certain autonomous systems in critical industrial environments as high-risk AI systems, subject to human supervision obligations, technical documentation and audit trails according to the applicable regulatory timeline.
The decisional boundary — what the system decides alone vs what requires human validation. This definition must be explicit, documented and revisable.
The responsibility chain — in case of incident linked to an autonomous decision, who is responsible, at what level, with what evidence available.
Operational supervision — concrete mechanisms allowing humans to monitor, contest and correct autonomous decisions in real time.
We do not intervene to audit systems or validate code. We intervene to explicitly define what your organisation has decided to delegate to its machines — and under what conditions it maintains control.
We define autonomy boundaries, human supervision protocols and responsibility chains. Before the incident, not after.
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