Digital Human/AI Live-Streaming E-Commerce Cost-Reduction Model

📌 Background

With fierce competition in China's live-streaming e-commerce sector—where human hosts are costly, inconsistent, and unable to provide 24/7 coverage—digital human live streaming has expanded from top merchants to small and medium-sized enterprises (SMEs) by 2026. However, compliance requirements have rapidly escalated: within 50 days of the new AI content labeling regulations taking effect, regulatory spot-checks revealed that major live-streaming rooms failed to prominently label AIGC content. By the end of 2025, eight e-commerce platforms jointly signed the 'Letter of Commitment to Promote the Standardized Application of AI Technology,' stating that suspected AI digital human live streams lacking labels will have their links directly blocked after review (based on platform rule interpretations).

👤 Target Customers

SME e-commerce merchants and local life service providers who pay for digital human live-streaming SaaS under conditions of labor shortages, the need to extend streaming hours, or routine product display and explanation scenarios. End consumers do not pay directly, but the model is sustained through live-streaming transaction commissions and sales volume.

💰 Revenue Streams

1) SaaS Subscriptions: Digital human live-streaming SaaS platforms charge annual subscription fees, with digital avatars billed annually; 2) Product Commissions: A commission is extracted from the transaction volume of goods sold in digital human live-streaming rooms; 3) Group-Buying Revenue Sharing: A sales share is extracted from local life group-buying transactions; 4) Agency Operation Service Fees: Fees are charged based on projects for digital human live-streaming agency operations.

🧮 Cost Structure

Main expenses include AI computing power and model inference fees, SaaS platform R&D and maintenance, compliance filing and content audit costs, as well as customer acquisition, traffic boosting, and market education expenditures.

🛡️ Moat

First-mover merchants have already navigated the three layers of compliance—national regulations, platform rules, and category access—forming operational templates and filing channels, while latecomers face policy uncertainty and platform ban risks. In addition, the stable streaming hours and transaction data accumulated through 24/7 operations accelerate model optimization, forming a two-sided moat of efficiency and reputation.

🔑 Keys to Success

• Cost reduction and efficiency enhancement (one digital human ≈ output of 12 full-time hosts)
• Three layers of compliance: National -> Platform -> Category
• Combined operations with human hosts/local life

⚠️ Risks

• Platforms and new regulatory rules tightening restrictions on digital human live streaming
• Ceiling on content recognition and emotional interaction experience
• Customer acquisition and traffic boosting costs swallowing profits

🏢 Cases

• Zhixiang AI Digital Human
• JD Cloud Digital Human AI-BB
• Various SaaS live-streaming tools

📊 SWOT Analysis