According to Alibaba’s Taobao and Tmall Group, the company released AI Xiaomi on May 11, the e-commerce industry’s first customer service agent with both pre-sale and after-sale capabilities. Real-world data shows that after merchants integrate AI Xiaomi, the average transfer-to-human rate drops 45%, while ‘AI+human’ collaborative conversion rates exceed pure human customer service by over 10%, marking the first time AI-assisted service surpasses manual-only operations.
As of March, AI Xiaomi processes nearly 10 million daily conversations and has been adopted by over one million merchants.
Disclaimer: The information on this page may come from third parties and does not represent the views or opinions of Gate. The content displayed on this page is for reference only and does not constitute any financial, investment, or legal advice. Gate does not guarantee the accuracy or completeness of the information and shall not be liable for any losses arising from the use of this information. Virtual asset investments carry high risks and are subject to significant price volatility. You may lose all of your invested principal. Please fully understand the relevant risks and make prudent decisions based on your own financial situation and risk tolerance. For details, please refer to
Disclaimer.
Related Articles
B.AI Announces Strategic Partnership with CoinAnk to Enhance AI Agent Trading Capabilities
According to ChainCatcher, AI Agent financial infrastructure B.AI announced a strategic partnership with CoinAnk to provide AI agents with enhanced data-driven decision-making capabilities. The collaboration will leverage CoinAnk's derivatives analytics and market intelligence to supply trading
GateNews13m ago
AI Agent Completes Bounty Task, Earns $16.88 After Burning $2,000 in Computing Costs
According to Beating, developer Chris recently instructed his AI Codex agent to earn $5. Over 22 hours, the agent autonomously completed the entire workflow—identifying code vulnerabilities, fixing bugs, communicating with maintainers, and verifying payment—ultimately earning $16.88. However, develo
GateNews5h ago
Google Cloud and PayPal executives: AI agent business will run on the crypto payments rails
At Consensus Miami, Google Cloud’s Widmann and PayPal’s Zabaneh said that AI agents cannot use traditional bank accounts and must take a crypto payment route. Google introduced the AP2 open protocol as the payment foundation for AI agents, and donated it to the FIDO Foundation; agents must access via key sharding and cannot transfer funds on their own. PayPal’s PYUSD is seen as a programmable payment layer, and merchants need to have machine-readable directories. Although AI agent traffic is common, the proportion of merchants with machine-readable directories remains low; accountability and multi-party custody issues still need to be defined.
MarketWhisper5h ago
Google Cloud and PayPal Launch AP2 Protocol with 120+ Partners; Execs Say AI Agents Will Run on Crypto Payment Rails
According to CoinDesk, Google Cloud and PayPal executives said at Consensus today that AI agents will operate on crypto payment rails due to structural limitations preventing them from accessing traditional bank accounts. Google Cloud's Web3 strategy lead Richard Widmann stated that crypto payment r
GateNews8h ago
Google Launches AI Agent Payment Protocol with 120+ Partners Including PayPal
According to CoinDesk, Google Cloud and PayPal executives discussed how cryptocurrency payments will underpin AI Agent-driven commerce. Google Cloud Web3 strategy lead Richard Widmann announced that Google has launched the Agentic Payments Protocol (AP2), donated to the FIDO Foundation, with
GateNews18h ago
Stanford launches Agent Island: AI models in Survivor-style games carry out strategic betrayals and vote out targets in counter-alliances
Stanford digital economy lab researcher Connacher Murphy launched a new AI evaluation environment, “Agent Island,” on May 9, enabling AI agents to compete, ally, betray, and vote out rivals in a Survivor-style multiplayer game—so as to measure strategic behavior that traditional static benchmarks can’t catch. Decrypt’s report summarizes: Traditional AI benchmarks are becoming increasingly unreliable—the models ultimately learn to solve the tasks, and benchmark data is also likely to leak into th
ChainNewsAbmedia18h ago
