The scenario clearly describes a model where the AI system operates independently for routine, well-defined tasks, but escalates exceptions or high-risk cases to humans for oversight. This is the defining characteristic of Supervised Autonomy.

In CAIPM, collaboration models between humans and AI are categorized based on the level of autonomy and oversight:

AI Assists Human: AI provides recommendations, but humans make all decisions

Human-Led Collaboration: Humans remain in control, using AI as a support tool

Full Automation: AI operates independently with no human intervention

Supervised Autonomy: AI executes tasks autonomously within defined boundaries, while humans intervene for exceptions, anomalies, or high-impact decisions

Key indicators in the scenario:

AI automatically processes routine invoices autonomous execution

Predefined rules govern when AI can act controlled autonomy

Exceptions are escalated to humans human oversight for risk management

Balance between efficiency and control hallmark of supervised autonomy

This approach is widely recommended in enterprise AI adoption because it allows organizations to scale operations while maintaining governance, compliance, and risk mitigation.

Therefore, the correct answer is Supervised Autonomy, as it best represents a system where AI operates independently within defined limits and humans oversee exceptions.

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