Industry Data

Lessons from Amazon Web Services (AWS): When Automation Fails & The Need for Human-in-the-Loop

2 min read

Oct 28, 2025 4:15:47 PM

In October 2025, a major AWS service disruption impacted thousands of platforms worldwide, from banking to retail. Amazon later attributed the issue to a rare software bug and “faulty automation” (GeekWire, 2025).

It was a humbling reminder that even the most advanced infrastructures can fail when automation runs unchecked. When AWS’s automated recovery system malfunctioned, engineers had to step in manually to restore services, proving that automation couldn’t fix automation.

The Lesson: Automation Needs Human Context

Photo: Forbes, https://www.forbes.com/sites/beatajones/2023/09/05/how-educators-can-leverage-generative-ai-to-promote-student-innovation/

For retailers, this story hits close to home. Many rely on fully automated dashboards and AI analytics to understand in-store behaviour. But when those systems misread data, the failure is often invisible.

Flawed Data: Dashboards mark campaigns as “successful” because of increased traffic, not knowing it’s mostly staff movement.
Flawed Conclusions: AI assumes a product is unpopular, when the real issue is poor placement.
Flawed Actions: Inventory is reduced when what’s actually needed is better display.

These silent automation errors slowly chip away at profits, just like an unseen outage. The AWS case shows us: automation is powerful, but without human validation, it’s incomplete.

An Era of Collaboration, Not Competition

Photo: Corporate Infotech Pvt. Ltd., https://www.cipl.org.in/amazon-web-services.php

The real takeaway isn’t that automation fails, it’s that humans and AI are better together. AI brings efficiency and scale, while humans add context, nuance, and judgment. Together, they produce insights that are not just data-driven, but truth-driven.

This approach is known as Human-in-the-Loop (HITL), where humans review, correct, and enhance AI outputs to ensure accuracy and relevance.

From Blind Automation to Ground-Truth Intelligence

At Tictag Insight, we’ve built this principle into our core technology. Our AI computer vision analyses customer behaviour inside retail stores, and every data point is validated by real humans. That combination turns everyday CCTV footage into a reliable source of ground-truth retail intelligence.

With Tictag Insight, you can:

Understand Customer Behaviour: Analyse customer journey paths and dwell time to gain accurate insights.
Staff Customer Engagement: Measure quality of interactions, not just frequency.
Optimise Product Placement: Detect customer-product interaction, not just shelf visits.