In Depth: E-Commerce Giants Step Up AI Rollouts to Boost Sales

China’s 2024 Double 11 shopping festival marked a new era in e-commerce by transforming from a mere discount event into a large-scale real-world experiment for artificial intelligence (AI) technologies[para. 1]. Leading e-commerce platforms—including Alibaba, JD.com, and ByteDance—actively integrated AI solutions not only to optimize pricing, advertising, and customer service, but also to accelerate shoppers’ journey from browsing to checkout[para. 2][para. 3]. This ambitious AI deployment provided the clearest picture yet of how generative AI is revolutionizing the $2 trillion Chinese e-commerce market, pushing platforms to automate operations and marketing in the face of softened consumer spending[para. 4]. However, while e-commerce firms and merchants eagerly embraced these new technologies, consumer trust and adoption lagged behind, driven by concerns about AI’s reliability and privacy[para. 5].

Alibaba, under new CEO Wu Yongming since September 2023, undertook a sweeping restructuring with AI at its core[para. 6]. During Double 11, running from October 15 to November 14, Alibaba used AI engines to allocate 50 billion yuan ($7 billion) in coupons, which raised conversion rates by 15% compared to previous methods[para. 8]. For merchants, AI-managed promotions delivered over a 30% year-over-year improvement in return on investment for more than one million products[para. 9]. Alibaba’s AI-powered “business manager” tool, introduced to over 13 million merchants, handled tasks like data analytics, marketing, and customer interactions, delivering a 30% reduction in manual work and a 1.5-fold boost in operational efficiency during the festival[para. 10]. Its generative AI-driven customer service system addressed 300 million user queries, reducing human agent intervention by 20% annually, and resolved around 100 million cases end-to-end without human support[para. 11]. On the international front, Alibaba advanced specialized AI tools such as the Accio search engine and Marco translation model—both enhancing overseas merchants’ sourcing and multilingual communications, with Macro outperforming major global language models in translation quality in November 2024[para. 13][para. 14].

JD.com focused on boosting efficiency through AI, with its LLM-powered customer service handling 4.2 billion interactions and resolving 85% of cases during Double 11[para. 17]. It invested heavily in AI-driven livestreaming, with digital avatars streaming five million hours and generating 2.3 billion yuan in merchandise value at just one-tenth the cost of human hosts[para. 18]. But despite these improvements, analysts—such as a November report from Morgan Stanley—questioned whether JD.com’s vertical, efficiency-focused AI strategy could secure a competitive edge, noting weak prospects for user growth, monetization, and long-term shareholder returns[para. 20][para. 21]. JD.com has also launched food delivery to counteract e-commerce slowdowns, falling to fourth place in China’s market by 2024[para. 22].

ByteDance, meanwhile, integrated its Doubao chatbot with Douyin E-commerce (China’s TikTok Shop), creating a “product card” feature that answers shopping queries with direct purchase links. Though this remains limited in scope, it signals a pivot toward AI-driven content-fueled sales[para. 23][para. 24].

Merchants themselves report major efficiency gains: AI tools have slashed manual workloads and raised sales conversion rates—like a slipper trader on Alibaba.com who doubled conversion rates and another whose transaction volumes rose 30% after using AI for multilingual customer service[para. 28][para. 29]. WorldFirst found that by mid-2025, 90% of small and midsize businesses surveyed used AI for core operational improvements[para. 32].

Despite these advances, consumer adoption of AI shopping tools remains modest. A November Accenture survey indicated only 37% of Chinese consumers had used AI in shopping—mainly for brand comparison or unfamiliar purchases—with most wary about AI’s privacy, reliability, and lack of personalization. As a result, consumer enthusiasm has not yet matched supply-side innovation, underscoring the ongoing challenge of building trust in the new AI-driven retail era[para. 35][para. 36][para. 37][para. 38].