The local life service industry is setting off an AI boom, and giants such as Meituan and Ele.me have applied AI technology to merchant operations, rider scheduling and user recommendations. However, despite the potential of AI in improving efficiency, it still faces problems such as lack of understanding, lack of professionalism, and unreasonable interaction design in practical applications, which is evaluated as “a bit tasteless” by users and merchants.
Following AI e-commerce, AI has also begun to roll into the local life service industry.
On June 26, Meituan officially released the first AI digital employee to serve retailers, and will equip each store with professional AI management assistants. At the same time, Wang Puzhong, CEO of Meituan’s core local life business, revealed that Meituan invests more than 10 billion yuan in AI every year.
Coincidentally, on June 24, Ele.me announced the launch of China’s first rider-end agent based on a large model, Ele.me’s AI assistant “Little Hungry”, to provide comprehensive support and services for millions of blue riders.
Douyin Life Service is not idle, and has launched an AI product called “Tanfan”, which uses AI technology to recommend local life restaurants to users.
It is clear that local life giants are collectively pounce on AI, implanting technology into every link from merchant operations, rider scheduling to user recommendations.
01 Use AI to fill the whole chain of local life
This AI competition covers the entire chain of merchants, riders and users.
On the merchant side, AI mainly plays the role of digital employees to reduce costs and increase efficiency, helping merchants carry out daily operations.
Meituan released the first AI digital employee service retailer terminal, providing multiple services such as business diagnosis, growth opportunity identification, operational support, intelligent scheduling and customer service reception; Recently, he is also in the internal testing of Kangaroo Staff, relying on massive information covering 4 million stores across the country and more than 10 years of catering online operation experience to provide merchants with industry insights and practical business advice. It mainly covers the intelligent operation of four types of scenarios: track selection, store site selection, dish research and development, and store operation.
Ele.me launched the “AI assistant for merchants”, from early settlement, to store decoration, to later operation, AI assistant can help merchants intelligently select products, intelligent beautiful pictures, and diagnose store operations.
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Douyin Local Life Service’s Douyin visitors and Kuaishou Local Life are all providing relevant AIGC intelligent marketing and creation services for merchants, capable of intelligent editing, intelligent graphic creation, etc., Kuaishou Local Life has also launched Nuwa digital humans, which can broadcast live around the clock and interact with the audience.
In addition, Kuaishou Local Life plans to launch the “AI Intelligent Quality” and “AI Intelligent Product Selection” tools in 2025 to intelligently judge when, where, and what to go.
On the rider side, AI is committed to ensuring the safety of delivery. Ele.me launched the AI “Little Hungry”, which can directly complete operations such as taking orders, confirming arrival at the store, querying activities, etc., and can also push, weather warnings, route closures and other content prompts to help riders improve operational efficiency and reduce delivery risks. In addition, “Little Hungry” can also realize the “heat map warning” function based on the rider’s historical data and peripheral order heat maps, and provide intelligent analysis such as “where there are more orders” and “current revenue estimates”.
At the same time, the country’s first takeaway delivery vehicle equipped with “AI brain” built by Beidou and Yadea was unveiled, which is equipped with Beidou dual-frequency chip to realize intelligent management of human-vehicle binding. It has functions such as identity recognition, automatic speed reduction, route optimization, and full traceability, aiming to solve the problem of “difficulty in entering the community” for delivery people.
On the user side, intelligent customer service should be a relatively common application of AI technology, which can quickly respond to user inquiries, answer common questions, and improve the service efficiency of the platform.
In addition, the platform is also exploring more grass functions, allowing AI to become a decision-making assistant.
Meituan’s “Ask the Pouch” can provide users with catering recommendations, gift suggestions and other services; On the Shenhu Channel, some dishes labeled “AI Smart Selection” will be accompanied by AI-generated short reviews; Meituan’s “Dian Zai” in Dianping’s internal test integrates functions such as store finder helper, dish matching suggestions, and even AI help with note-taking.
Douyin has launched a “rice exploration” based on the bean bag model, which can recommend nearby restaurants based on the user’s geographical location, and can also carry out multi-dimensional comparisons, after determining the restaurant, users can jump to the AutoNavi map with one click to navigate, realizing a seamless connection from “finding a store” to “arriving at the store”.
It is worth mentioning that Ele.me has also launched the “Holographic Shield” system, which is mainly used in the platform’s compliance governance. Specifically, the system can scan the whole network of stores 24 hours a day, and use image recognition technology to find out those “ghost restaurants”, and the processing speed of problem merchants is directly shortened from half a day to 1 minute, and the efficiency is rapidly improved.
It is not difficult to see that AI technology is being implemented in various application scenarios in the field of local life.
But are these AIs with diverse names and rich functions really useful?
02 It’s still a bit tasteless
It is undeniable that the investment and application of these AIs do show the potential to improve efficiency in specific links. For example, intelligent customer service can effectively share manual pressure in the rapid response to standardized problems; Route optimization and basic information push on the rider side can theoretically improve delivery efficiency.
However, when it comes to key links such as core user experience, merchant operating efficiency and rider workflow optimization, “chicken ribs” have become feedback from many users.
First, AI lacks understanding. On the merchant side, an independent coffee shop owner said that although AI can quickly generate copy, AI’s understanding of localized, personalized, emotional, and unstructured information is not deep enough, and it is difficult to capture subtle “human touch” and scenario-based needs, resulting in advertising copy being difficult to impress people, and it actually attracts very few customers.
On the user side, some consumers pointed out that AI recommendations are keen on piling up gorgeous adjectives, repeatedly beautifying products, lacking real insights, and even sometimes false information.
Second, the professionalism of AI is insufficient. A chain brand operates frankly that the AI functions of most local life platforms are used with average results. Taking beautification pictures as an example, the generated dish graphics and texts are often misaligned with their needs, and they are more inclined to choose more professional AI tools to beautify the pictures.
Moreover, the platform’s AI tools are difficult to match in terms of professionalism, flexibility and output quality in vertical fields, but because of their coercion, they destroy the merchant’s original workflow, make the operation interface bloated and messy, and increase the risk of accidental touch.
A deeper concern comes from the ambiguity of traffic rules. Many merchants pointed out that whether it is consumers’ active AI search recommendations or passive “AI smart selection” logos, there is a lack of transparency standards. “What kind of products and merchants can be put in the forefront? Will this evolve into new traffic pools for an additional fee? ”
Finally, the interaction design of AI fails to meet the principle of “efficiency first” in the delivery scenario. For example, a crowdsourcing rider said, “For example, sometimes there will be a situation where the merchant is stuck in the meal, once you leave the store, the AI assistant will keep broadcasting that the food has not been picked up, but what kind of noise is made, the AI will judge that the food is successful, which is very troublesome.”
In general, the user’s perception of the value brought by AI is not clear.Merchants have not seen significant revenue growth or significant cost reductions, riders have not found delivery safer, order acquisition easier, and consumers have not received disruptive experience improvements. Therefore, the essence of the “tasteless” evaluation is that there is a certain gap between the current AI capabilities and the expectations of all parties for “intelligence” and the need to solve core pain points.
03 Finally
AI applications in the field of local life are undoubtedly a major trend in the current development of the industry.
Judging from the actions of Meituan, Ele.me, Douyin, and Kuaishou, everyone also hopes to tell the new story of AI, but the key to making this story truly beautiful is to solve the current “tasteless” dilemma, so that AI can go from “have” to “useful”, and finally to “easy to use” and “love to use”.
As Jack Ma said, the future is not to let AI replace humans, but to let AI liberate humans, understand humans better, and serve humans well. In the AI competition of local life, who can take the lead in crossing the “tasteless” stage and let technology truly solve practical problems, who can truly tell this new AI story about efficiency, experience and trust.
