---
id: "question-agentic-quality-control"
type: "open-question"
source_timestamps: ["§ Myth 3"]
tags: ["risk-management", "quality-assurance"]
related: ["concept-agentic-ai-sales", "claim-agentic-scale", "evidence-agentic-scale-caveats"]
resolutionPath: "Case studies detailing the human-in-the-loop (HITL) or automated guardrails implemented by enterprise companies deploying agentic AI for financial transactions."
sources: ["attention"]
sourceVaultSlug: "hbr-seg-attention"
originDay: 4
articleStem: "hbr-cl-90-genai-myths-sales-marketing"
sourceUrl: "https://hbr.org/2025/02/5-gen-ai-myths-holding-sales-and-marketing-teams-back"
sourceTitle: "5 Gen AI Myths Holding Sales and Marketing Teams Back"
---
# How is quality controlled at scale with Agentic AI?

## Open Question: How is quality controlled at scale with Agentic AI?

**The gap:** The source highlights an equipment manufacturer whose Gen AI agents generated **over a million quotes in a month** ([[claim-agentic-scale]]), but does not detail the quality-assurance mechanisms, error rates, or liability frameworks ensuring those autonomous quotes were accurate and legally sound.

**Why it's unresolved:** Autonomous generation of financial documents raises disputes, misquotes, and regulatory obligations that the article leaves unaddressed. See [[concept-agentic-ai-sales]].

**Resolution path:** Case studies detailing the **human-in-the-loop (HITL)** or automated guardrails enterprises implement for agentic AI in financial transactions. External discussion of guardrails, monitoring, and failure modes is summarized in [[evidence-agentic-scale-caveats]].