Summary of Key Points
Midea, a manufacturing giant with annual revenue in excess of 400 billion yuan, has been actively moving in the AI field recently (such as integrating into WeChat's AI ecosystem and collaborating with Alibaba to develop a home AI platform). However, the actual changes in products, revenue, and user experience resulting from these high-profile initiatives are still limited. Midea's approach to AI is not merely following the trend; it has been making preparations since 2013 (by installing Wi-Fi modules, developing IoT platforms, and creating a voice assistant). The strategy was upgraded to "comprehensive AIization" in 2023 with the emergence of large-scale AI models. Nevertheless, due to the high cost of trial and error in manufacturing, the immaturity of AI technology, and the lack of established pathways in the industry, Midea has adopted a approach of "high-profile communication and gradual experimentation." Currently, the cost-saving and efficiency-enhancing benefits brought by AI account for only a small portion of its total revenue, and any improvements in products are more about enhancing user experience rather than complete disruption.
Detailed Analysis
1. Midea's AI Efforts Are Not a Last-Minute Trend
Midea's investment in AI has been much earlier than many expected. In 2013, while most home appliance companies were focusing on capacity and distribution channels, Midea established an IoT research center to equip its products with Wi-Fi modules, allowing users to control appliances remotely via smartphones. 2018 was a pivotal year: the company formed an IoT division, launched the "Mijia App" to unify all smart home appliance controls (previously, there were separate apps for different categories), and introduced the M·IoT industrial internet platform, extending intelligence from the consumer side to factory production (e.g., scheduling and quality inspection). In 2019, it introduced the "Xiaomei" voice assistant, enabling users to interact with appliances. It was not until 2023, with the rise of large-scale AI models, that Midea upgraded its AI strategy to a "smart brain" approach, developing the "Xiaomei AI intelligent agent" to enable appliances to proactively sense user needs (e.g., automatically adjusting the temperature). Midea's AI journey has progressed from simply connecting devices to using voice commands to making intelligent decisions.
2. Recent Collaborations with WeChat and Alibaba Are About Leveraging Existing Platforms
Midea's recent collaborations with WeChat and Alibaba are strategic moves:
- WeChat Collaboration: By integrating with WeChat's AI Agent, Midea has connected its appliances to WeChat's ecosystem, reaching over 1 billion users. Users can control appliances directly through WeChat without downloading the Mijia App, lowering the barrier to use and expanding its audience.
- Alibaba Collaboration: Midea leverages Alibaba's Qianwen large-scale AI model to develop a home AI platform. Although it has its own AI team, developing such models requires significant computing power and data. By partnering with Alibaba, Midea can quickly access this advanced technology, saving time and resources.
These collaborations are part of Midea's "open strategy" to create an interconnected ecosystem with other devices (such as smartphones, cars, and home appliances), aiming to expand usage scenarios.
3. Limited Actual Changes Despite High Profile
Despite the high-profile efforts, the actual impact of AI at Midea is still limited:
- Low Conversion Rate of Intelligent Tools: Although Midea has created 13,000 AI tools (e.g., for marketing and customer service), only 158 have contributed significantly, accounting for 95% of the value. The commercialization rate is just 0.2%.
- Minimal Financial Impact: By 2025, AI is expected to save Midea 700 million yuan in costs, but its total revenue that year was 458.5 billion yuan, meaning the cost reduction is only 0.15%. This is like saving 15 yuan from a yearly income of 100,000 yuan—almost negligible.
- No Fundamental Product Disruption: AI improvements are mainly about enhancing user experience (e.g., automatic temperature adjustment for air conditioners, food expiration alerts for refrigerators), but the core technologies (e.g., compression cooling for air conditioners, refrigerant preservation for refrigerators) remain unchanged. The most common features (voice control, remote access) have been around for decades, and "proactive decision-making" by AI is still limited to basic logic.
4. Why Not Speed Up? High Costs of Trial and Error in Manufacturing
Midea avoids the aggressive spending seen in tech companies due to the unique challenges of manufacturing:
- Low Tolerance for Errors: In tech, a wrong movie recommendation might be dismissed by users, but in manufacturing, a mistake in production planning could halt an entire line, resulting in millions or even billions in losses. Incorrect device settings could lead to defective products.
- Lack of Established Paths: There are no proven models for how to use AI in manufacturing, so companies must experiment on their own.
- Intense Competition: The home appliance industry is in a state of stagnation, with domestic retail sales declining by 4.3% and exports dropping by 3.3% in 2025. Companies cannot afford to invest heavily in risky AI projects without ensuring stability first.
5. A Rational Approach for Manufacturing
Midea's cautious approach is strategic:
- Strategic Positioning: AI is a future trend, and not investing in it could lead to being left behind. High-profile communication enhances its reputation as a tech-driven brand and gains market traction.
- Risk Management: The rigorous nature of manufacturing requires gradual experimentation, starting with low-risk areas (e.g., marketing, customer service) before moving to production and products.
This strategy is common among global manufacturing giants like Siemens and General Electric. A survey by Cheung Kong Graduate School of Business shows that the AI adoption rate in Chinese industries is only 10%, with most still in the pilot phase. KPMG data indicates that while 88% of companies have invested in AI, only 24% are making profits across multiple applications. This highlights the need for a cautious approach as disruptive technologies take time to be fully implemented.
Conclusion
Midea's AI transformation reflects the dilemma faced by traditional manufacturing companies: they want to seize opportunities but cannot afford significant risks. While the current results are limited, the "high-profile layout and gradual experimentation" strategy seems to be the most prudent choice for a company with annual revenue in the tens of billions. Whether AI will truly transform the home appliance industry depends on the maturity of technology and user demand, but Midea is certainly taking a leading role.