AI-Enabled Shopping Surges, But GMV Disclosures Avoided as Market Saturation Risks Emerge

The Double 11 festival showcased undeniable momentum in the AI-powered retail engine, with Alibaba reporting 589 brands hitting RMB 100 million in GMV-a 46% surge from 2023-thanks to tools that generated over 100 million merchant content pieces, according to a Technode analysis. Yet beneath this headline vigor lies a troubling signal: platforms are suddenly retreating from granular GMV reporting. While they flaunted the 100M-RMB brand milestone, they withheld broader GMV disclosures that were routine in prior campaigns. This selective transparency isn't neutral; it aligns with the growing saturation in China's hyper-competitive e-commerce market. When platforms stop publishing comprehensive GMV data, it often indicates discomfort with the full picture-particularly when growth drivers like AI and livestreaming (already reaching 597 million users by late 2023) are no longer moving the needle decisively. The omission raises questions about whether top-line growth is being propped up by increasingly aggressive tactics rather than organic demand, a red flag for investors prioritizing cash flow sustainability over hype.

The disconnect between AI-powered efficiency and actual brand growth is stark, particularly when contrasted with the volatility surrounding AI infrastructure plays like CoreWeave and Core Scientific. Alibaba's ecosystem demonstrates a clear focus on operational optimization rather than explosive top-line expansion. Their AI toolkit enabled a massive scale-up in content creation, with 4 million merchants generating over 100 million marketing assets during the critical Double 11 period, as noted in the Technode analysis. JD.com complemented this with significant hardware momentum, reporting tenfold growth in AI learning device sales and doubling for AI-enabled computers and smartphones, alongside a 3.8-times surge in livestream orders, according to the Technode analysis.

. Yet, despite this sophisticated infrastructure and engagement (livestreaming reached 597 million users by late 2023), the headline brand performance was surprisingly tepid. The number of brands hitting RMB 100 million GMV grew just 46% year-over-year to 589 brands. This modest gain, especially given the intense promotional environment and technological investment, underscores how AI is functioning primarily as a cost and reach amplifier rather than a direct driver of dramatic share gain for top-tier players. The efficiency gains are real – more content, better targeting, higher engagement – but translating that into significantly higher growth rates for established giants appears increasingly challenging, suggesting market saturation or intense competitive pressure at the very top.

Despite the headline-grabbing numbers-livestreaming reached 597 million users representing 54.7% of China's internet population by late 2023-according to the Technode analysis, the growth engine is hitting a structural wall. The sheer volume of users masks a critical imbalance: the digital divide between urban and rural areas is acting as a hard ceiling on future expansion. While logistics networks have expanded, their impact remains limited; doubling transaction volumes for just 519 product categories fails to move the needle for the 45.3% of internet users still outside the livestreaming ecosystem, primarily those in underserved regions lacking reliable broadband and digital infrastructure, as noted in the Technode analysis.

This infrastructure gap isn't just a minor hurdle; it fundamentally constrains the market's addressable size. The 597 million users represent penetration within the current connected population, not the total potential. The 45.3% unpenetrated segment isn't merely a passive audience-it represents a substantial pool of potential consumers whose exclusion is directly tied to physical limitations, not lack of product interest or marketing reach. For investors assessing the long-term scalability of livestreaming platforms and their supply chains, this ceiling effect demands serious consideration. The doubling of transactions in 519 categories, while impressive on a category basis, underscores that scaling remains confined to the existing, already-served user base rather than unlocking new, massive markets. Until rural connectivity improves significantly, the market faces a tangible growth boundary dictated by infrastructure, not consumer appetite.

The narrative around AI in retail often centers on explosive growth narratives. Yet from a risk defense perspective, the real defensive value lies not in aspirations but in demonstrated cost reduction and operational resilience. JD.com's 2024 Double 11 performance offers a clearer lens: the company reported a tenfold surge in AI learning device sales alongside doubled sales for AI-enabled computers and smartphones, while JD Live orders exploded 3.8 times, according to the Technode analysis. This demonstrates tangible, incremental adoption of efficiency tools where merchants leverage AI for content generation and consumer traffic analysis, driving engagement among livestreaming's 597 million users (54.7% of China's internet population as of December 2023, according to the Technode analysis).

This efficiency focus is critical. AI-powered tools reduce merchant acquisition costs and optimize inventory through predictive analytics-objectively lowering operational friction. For investors prioritizing downside protection, this translates to potentially smoother earnings under stress. However, the absence of disclosed Gross Merchandise Value (GMV) figures for JD this year is a significant red flag. Without this key performance indicator reappearing in disclosures, the link between device sales growth and overall platform revenue sustainability remains unverified. It's a classic case of cost control offering defensive value while growth drivers lack transparent validation. Until GMV transparency returns or concrete evidence of rural infrastructure expansion supporting deeper market penetration emerges, the prudent stance remains cautious. The efficiency gains are real, but they don't automatically guarantee top-line momentum-and in risk-averse portfolios, that distinction matters.