独家对话交个朋友：今年618 用AI重做直播电商

This article explores how AI has become the core focus of live-stream e-commerce transformation during this year's 618 mid-year shopping festival. Drawing on practical experience from leading industry player Jiaoge Pengyou (Make Friends), it summarizes key insights and actionable takeaways as follows:

1. Avoid common AI deployment pitfalls: Do not blindly rush into front-end AI digital human livestreaming. Digital human technology is still immature in terms of legal subject status, real-time response capability, and commercial performance. Compared to digital human hosts, AI shopping assistants are a much better fit for in-store livestream scenarios, and improving back-end efficiency is currently the more pragmatic choice.

2. Three key factors for successful AI implementation for individuals and businesses: Core competitiveness comes from proprietary business data, followed by industry experience needed to filter out effective data, and continuous refinement of AI capabilities through real-world business applications.

3. Future industry shifts: Data-driven, standardized work will rapidly be replaced by AI, while roles requiring in-person interaction and emotional connection—such as hosts and business developers—are unlikely to be replaced. Industry practitioners must upskill their AI application capabilities to remain competitive.

AI is currently reshaping the live-stream e-commerce industry, bringing both new opportunities and new requirements for brand marketing and operations. Key takeaways for brands are as follows:

1. Prioritize the right AI implementation direction: Do not invest blindly in front-end digital human host projects. Instead, focus first on improving back-end efficiency: AI can be used to generate ad scripts, short videos, and optimize product titles to cut labor costs. For in-store livestream scenarios, AI shopping assistants deliver higher efficiency than digital humans, so they should be prioritized.

2. Core principles for AI deployment: Proactively accumulate full business data, leverage mature industry experience to improve AI output quality, and integrate AI into all business processes for continuous refinement. Jiaoge Pengyou has already achieved 20-30% annual revenue growth through AI transformation, with AI-related businesses accounting for 75% of its total GMV.

3. Risk warnings: Do not use AI to generate false product display content. Brands need to prepare for the impact of AI on industry trust, and focus their AI efforts on segmented scenarios relying on private data that large tech firms have not yet covered, to build AI-based competitive barriers early.

The AI wave has brought clear growth opportunities and actionable lessons for live-stream e-commerce sellers, summarized below:

1. Proven implementation path to learn from: Do not blindly follow the trend of front-end digital human livestreaming. Prioritize transforming back-end operations with AI to cut labor costs. For example, after AI transformation, Jiaoge Pengyou increased daily script output per person from 20 to over 100, and reduced staffing for vertical-category livestream rooms from 20-30 people to just a handful, delivering significant cost reduction and efficiency gains.

2. Core elements for successful AI implementation: First, accumulate full data from your own business. Second, filter effective data with industry experience. Third, continuously refine AI capabilities in line with your specific business scenarios—do not stop at just using generic AI tools.

3. Opportunities and risk warnings: Seize opportunities in segmented market spaces left by large tech firms, do not use AI to create false display content. Practitioners must improve their AI application capabilities to become hybrid talents proficient in both business and AI—those who fail to keep up will be eliminated. The industry will see a complete restructuring within the next five years.

Against the trend of AI reshaping live-stream e-commerce, new insights and opportunities have emerged for factories in production, digital transformation, and e-commerce expansion, summarized below:

1. Shifting requirements on the production side: E-commerce players now leverage AI for large-scale, fast-paced product selection and content generation, which raises higher requirements for product standardization and data maturity at factories. Factories need to organize full-dimensional product information to meet the needs of AI-powered product selection and marketing on the e-commerce side.

2. New business opportunities: The growth of AI-powered e-commerce has generated demand for segmented product data and vertical scenario services. Factories can leverage their own accumulated product data and industry expertise to meet the needs of AI e-commerce tool service providers, and open up new room for business growth.

3. Insights for digital transformation: When advancing AI plus e-commerce transformation, factories should not blindly chase front-end trendy concepts. Prioritize accumulating digital data for internal operations first, implement AI applications based on your own production expertise and industry experience, achieve cost reduction and efficiency improvement in back-end operations first, then gradually expand front-end e-commerce business.

Against the trend of AI restructuring the e-commerce industry, clear industry trends, customer pain points and development directions have emerged for e-commerce service providers, summarized below:

1. Industry development trends: AI has become a core efficiency improvement tool for the e-commerce industry during this year's 618 shopping festival. Leading industry players have progressed from adopting standalone AI tools to restructuring their entire business workflows. For leading player Jiaoge Pengyou, AI-related businesses already account for 75% of total GMV. The entire e-commerce industry will be completely restructured in the next five years, and market demand for AI e-commerce services will continue to grow.

2. Key customer pain points: Most merchants face high labor costs; large merchants struggle to keep up efficiency with their high volume of new product launches. Many merchants have blindly rushed into digital human host deployments and lost money, while still being unable to find AI implementation solutions suited to their own needs. They need AI services that can deliver tangible, measurable results.

3. Product development direction: Do not blindly develop front-end concept products centered on digital humans. Instead, focus on meeting merchants' back-end efficiency improvement needs, build products based on large volumes of vertical industry private data and refined with industry experience, prioritize segmented, specialized scenarios that large tech firms do not focus on, and build targeted implementation solutions on top of large firms' foundational AI capabilities.

Against the trend of AI-driven e-commerce development, the following core insights for platform operation, merchant recruitment and risk mitigation are summarized below:

1. Current core merchant demand from platforms: Merchants need platforms to open up foundational AI capabilities, improve data ecosystems, and help merchants accumulate their own business data. Leading platforms have already started relevant布局: Taobao has integrated Qwen to launch an AI shopping assistant, Douyin has positioned Doubao as a new AI shopping entry, and JD.com invested 6.9 billion yuan in AI research and development in the first quarter of this year.

2. Platform operation and merchant recruitment direction: Platforms can guide merchants to deploy AI correctly, dissuade merchants from blind investment in digital human hosts, encourage merchants to use AI for back-end efficiency improvement, and attract merchants focused on segmented AI scenarios to settle on the platform to enrich the platform's AI ecosystem.

3. Risk mitigation direction: Platforms need to quickly establish industry rules for AI-generated content, clearly distinguish between allowed marketing AI content and prohibited deceptive display AI content, crack down on false AI-generated content and AI-generated fake defect images used for fraudulent refund claims, prevent bad money from driving out good money, protect the platform's trust system, and prepare in advance for upcoming industry restructuring.

AI has now entered the deep implementation phase in live-stream e-commerce, bringing many new industry trends, new problems, and new business models, summarized below:

1. New industry trends: For the first time, AI has been integrated into all scenarios of the annual 618 grand promotion this year. AI has moved beyond the early hype of digital human concepts, and entered the phase of improving efficiency across entire back-end business processes. Leading MCN机构 have completed full-process AI restructuring, achieving 20-30% annual revenue growth, with AI-related businesses accounting for 75% of total GMV, and delivering clear industry-wide efficiency gains.

2. New industry problems: Technological development has outpaced the establishment of industry rules, bringing a series of new problems: unclear legal liability for digital human hosts, AI-generated false display content, and consumers using AI-generated fake defect images to fraudulently claim refunds. These issues threaten the e-commerce trust system and create a risk of bad money driving out good money.

3. New business models and research directions: A new model has already emerged among leading players: improving internal efficiency with AI while offering external AI e-commerce strategy consulting services. Core competitive barriers for this model lie in data, industry experience and application scenarios. The entire industry will be completely restructured within five years. Priority research areas include the development paths of small and medium-sized players focused on segmented scenarios, and the direction of industry rule construction.