JD.com Pivots to ‘Industrial AI’ in Bid to Revitalize Growth and Challenge Rivals
JD.com is launching a major strategic pivot toward “industrial AI” under the direct leadership of its founder, Richard Liu, a move designed to overhaul its core e-commerce operations and intensify its rivalry with competitors like Alibaba in China’s high-stakes technology race.
At its 2025 Global Tech Explorer Conference, the e-commerce giant announced it would invest billions over the next three years to integrate AI across its business. In a significant show of commitment, founder Liu Qiangdong will personally serve as head of the group’s research arm. This signals a new sense of urgency as JD.com seeks to reverse a period of slowing growth and reposition itself in a fiercely competitive market.
The timing, coinciding with the critical "Double 11" shopping festival, underscores the escalating battle for dominance in an AI-powered retail landscape. The move follows a recent pledge by arch-rival Alibaba to invest 380 billion yuan (approximately $52.6 billion) in AI over three years, highlighting the massive capital being deployed to capture leadership in this next wave of innovation.
Analysts view JD.com's pivot as putting the company on a "wartime footing" to fundamentally reshape its supply chain and retail logic through technology. The strategy highlights an accelerating efficiency race among China's tech giants, where the ability to master and deploy AI will be a key determinant of future market share and investor confidence.
A Harder Path to Revive Growth
JD.com’s aggressive AI push stems from a period of significant business pressure. Founder Richard Liu recently acknowledged a growth slump, describing the last five years as a period of decline. This anxiety is fueled by mounting competition from Pinduoduo, which has captured a significant user base with its price-focused strategy, and Douyin Commerce, which excels at content-driven shopping experiences. Consequently, JD.com's retail revenue growth has slowed to single digits, its market share has been surpassed by Pinduoduo, and its advertising and service income growth has lagged behind rivals.
In response, JD.com is deliberately shunning the path of general-purpose large models, such as Alibaba's Tongyi Qianwen or Baidu's Ernie Bot, which are built first and then applied to various scenarios. Instead, JD.com is pursuing a "scene-first" industrial AI strategy, focusing on developing tailored solutions to enhance efficiency within its existing business operations.
This philosophy is captured in the company's value formula: AI Value = Model × Experience × (Industry Depth)². By giving "Industry Depth" an exponential weight, JD.com argues that even with comparable model capabilities, a company with deeper industrial integration will achieve an outsized competitive advantage. "Large model capabilities are no longer scarce," explained JD.com CEO Sandy Xu. "The real barrier is making models truly work to drive industrial efficiency."
Doubling Down on Supply-Chain Strengths
The choice of an industrial AI path is deeply rooted in JD.com's core identity. The company's competitive advantage has always been its vast and complex physical infrastructure, including a catalog of 57.1 million industrial SKUs and a network of over 5 million warehouses worldwide. This provides a rich foundation of real-world data across retail, logistics, health, and industrial sectors that is difficult for competitors to replicate.
However, this heavy-asset model has become a double-edged sword. Without AI-driven optimization, its scale risks becoming a hindrance, with massive data sets turning into information overload and a large employee base translating into burdensome labor costs. By embedding AI into its operations, JD.com aims to transform these potential liabilities into fortified strengths.
This "long march," as some describe it, is not without obstacles. Industrial AI demands deep domain expertise and has much longer implementation cycles than general-purpose AI. Furthermore, challenges such as data silos among merchants, the high cost of developing customized models, and the weak digital infrastructure of some partners could slow down the process.
Rebuilding the Value Chain With AI Tools
At its conference, JD.com unveiled a suite of new AI products centered on its JoyAI large model brand, including tools designed to systematically reconstruct its e-commerce value chain. These applications are already demonstrating tangible efficiency gains in internal operations, product monetization, and fulfillment.
In operations, the use of AI-powered digital humans is being scaled across the platform. Following the success of Richard Liu's "AI avatar" in an April 2024 livestream, the company reports that digital host costs are just one-tenth of human broadcasters, with production costs per avatar falling to double-digit yuan figures.
For merchants, AI is accelerating the path from product to profit. An AI agent named "Jingdiandian," built on JD.com's Oxygen architecture, analyzes market data to automatically generate content for new products, reportedly boosting material creation efficiency by over a thousand times and significantly shortening a product’s time-to-market.
In logistics, JD.com's traditional stronghold, its "Super Brain 2.0" platform is improving standardization by 15% and human-machine collaboration efficiency by over 20%. The technology is being deployed across more than 500 warehouses to address issues like inconsistent fulfillment and high last-mile delivery costs. Despite these advances, the company acknowledges AI is not a panacea, noting the limitations of digital avatars in complex interactions and the continued need for human intervention in logistics during extreme weather or non-standard scenarios.
An 'Operating System' for Future Commerce
Beyond internal improvements, JD.com's ultimate ambition is to position its AI capabilities as the foundational "operating system" for the next generation of e-commerce. By first refining its AI tools within its own retail, logistics, and health units, the company plans to externalize these proven solutions, offering platforms like the open-source JoyAgent and the developer-focused JoyCode to its ecosystem of partners.
The strategic intent is clear: by encouraging merchants and developers to build on its platforms and adhere to its data standards, JD.com seeks to evolve from a mere retail marketplace into an indispensable provider of intelligent business infrastructure, thereby creating a powerful and lasting competitive moat.
This ecosystem strategy carries profound implications. For merchants, it offers immediate access to powerful cost-saving tools but raises long-term concerns about platform dependency and data autonomy. For the industry, it signals a competitive shift away from price and traffic wars toward a sophisticated, all-encompassing race for AI-driven efficiency.
However, JD.com faces a contentious road ahead. Competitors including Alibaba, Tencent, PDD, and ByteDance are all aggressively building their own AI ecosystems, ensuring the fight for industry standards will be prolonged. As the battle for China's e-commerce future intensifies, one thing is certain: AI is no longer an option, but the new language of survival for all participants.