---
id: "prereq-real-time-data-infrastructure"
type: "prereq"
source_timestamps: ["§ They Train People in the Context of Real Work", "¶13", "¶14"]
tags: ["infrastructure", "data-engineering"]
related: ["concept-learning-in-the-flow-of-work", "action-shift-to-in-flow-training"]
reason: "Without real-time data capture, supervisors cannot monitor where work stalls or confidence drops, making in-flow coaching impossible."
sourceUrl: "https://hbr.org/2026/05/the-best-manufacturers-build-ai-with-workers-not-for-them"
sourceTitle: "The Best Manufacturers Build AI with Workers, Not for Them"
sources: ["adoption"]
sourceVaultSlug: "hbr-seg-adoption"
originDay: 9
articleStem: "hbr-cl-78-build-ai-with-workers"
---
# Real-Time Data Infrastructure

**Prerequisite:** To implement [[concept-learning-in-the-flow-of-work]] and to track operational signals of human-AI collaboration, a manufacturer must already have the underlying data infrastructure to support **real-time analytics, operational-twin data, and edge computing**.

**Why it is required:** without real-time data capture, supervisors cannot see where work stalls or where confidence drops — which makes in-flow coaching (and, by extension, [[action-shift-to-in-flow-training]] and the measurement in [[action-track-human-ai-handoffs]]) impossible. This is the technical floor beneath Pillars 2 and 3 of the [[framework-building-ai-with-workers]].