---
id: "action-evaluate-business-models"
type: "action-item"
source_timestamps: ["¶26", "¶27"]
tags: ["business-model-innovation", "localization"]
related: ["framework-hybridization-steps", "entity-procter-and-gamble"]
speakers: ["Amit Joshi", "Mark J. Greeven", "Sophie Liu", "Kunjian Li"]
action: "Analyze and adapt novel Chinese AI-driven business models, ensuring alignment with the underlying foundational technology stack."
outcome: "Unlocking new revenue streams and operational efficiencies by leveraging highly competitive, scale-tested business models."
source_url: "https://hbr.org/2025/09/how-savvy-companies-are-using-chinese-ai"
source_title: "How Savvy Companies Are Using Chinese AI"
sources: ["tail2"]
sourceVaultSlug: "hbr-seg-tail2"
originDay: 2
articleStem: "hbr-tail-123-using-chinese-ai"
sourceUrl: "https://hbr.org/2025/09/how-savvy-companies-are-using-chinese-ai"
sourceTitle: "How Savvy Companies Are Using Chinese AI"
---
# Adapt Hyper-Localized Chinese Business Models

**Action (Step 2 of [[framework-hybridization-steps]]):** Study the new business models and monetization strategies emerging from the Chinese AI ecosystem — e.g., **Douyin's 'interest-based e-commerce'** combining short videos, algorithmic discovery, and direct purchasing.

**The deeper move:** understand the **foundational tech stack** those models require, then adapt them to unlock performance and cost advantages. The cautionary case is **[[entity-procter-and-gamble|P&G]]**, which partnered with Douyin, co-created products via live-streaming feedback loops, and had to **rethink product-development timelines** to fit the platform's AI-driven cadence.

**Outcome:** new revenue streams and operational efficiencies from highly competitive, scale-tested business models — but only if the organization is willing to adapt its own processes to the model's underlying stack.