---
id: "entity-panasonic-energy-north-america"
type: "entity"
entityType: "organization"
canonicalName: "Panasonic Energy North America"
aliases: ["Panasonic Energy"]
source_timestamps: ["§ 4. Data management"]
tags: ["manufacturing", "case-study"]
related: ["concept-unstructured-data-utilization", "entity-palantir"]
source_url: "https://hbr.org/2025/01/what-companies-succeeding-with-ai-do-differently"
source_title: "What Companies Succeeding with AI Do Differently"
sources: ["execution"]
sourceVaultSlug: "hbr-seg-execution"
originDay: 8
articleStem: "hbr-cl-89-companies-succeeding-with-ai"
sourceUrl: "https://hbr.org/2025/01/what-companies-succeeding-with-ai-do-differently"
sourceTitle: "What Companies Succeeding with AI Do Differently"
---
# Panasonic Energy North America

**Panasonic Energy North America** is a battery manufacturer cited as the flagship example of [[concept-unstructured-data-utilization|unstructured data utilization via GenAI]] (pillar #4 of [[framework-four-pillars-of-ai-success]]).

**Case narrative:** Using [[entity-palantir-d8]]'s **Artificial Intelligence Platform (AIP)**, Panasonic built a **maintenance assistant** trained on **1 million historical tickets** to help **350 maintenance technicians** produce **5.5 million batteries per day** — reducing machine downtime and accelerating onboarding by fusing machine telemetry with captured expert knowledge.

The general pattern is strongly validated; the specific metrics (1M tickets, 350 technicians, 5.5M batteries/day) are case-reported from HBR/Palantir sources, not independently audited.

*Canonical reference:* Panasonic Energy corporate site (region-specific North America pages).