Humanoids will have their ‘GPT-3.5’ moment within 5 years, says AGIBOT co-founder Yao Maoqing

AGIBOT co-founder Yao Maoqing said at the Fortune Leaders Forum in Macau on Sept. 8 that embodied AI will reach its "GPT-3.5" moment within a 3-to-5-year window, citing the 80%-90% everyday-task success rate of the model behind ChatGPT. AGIBOT shipped 9,700 humanoid robots in the first six months of 2026, making it the top seller by units according to Counterpoint Research data released in late August, and the startup is considering an IPO in Hong Kong. Yao said AGIBOT's robots hit a 99.99% success rate completing over 64,000 manufacturing tasks during a six-day livestream in late June, though he acknowledged factories judge robots on success rate, cycle time, stability and cost rather than the technology used.

Humanoid robots took center stage at the W orld Humanoid Robot Games https://www.reuters.com/pictures/faster-stronger-occasionally-upright-humanoid-robots-compete-beijing-games-2026-08-24/ in Beijing last August, winning over audiences by attempting—not always sucessfully—athletic feats like sprinting, weightlifting, and kickboxing. Yet one of China’s leading robot startup founders thinks there are still a few years before robots truly break into the public consciousness. “As models keep maturing, embodied AI will reach GPT-3.5,” said Yao Maoqing, co-founder of the Chinese robotics firm AGIBOT, during the Fortune Leaders Forum in Macau on Sept. 8. “People differ somewhat on timing, but overall it’s within the 3-to-5-year window.” Yao’s use of “GPT-3.5” was a reference to the model underinning ChatGPT; OpenAI’s chatbot was the first time an AI service could perform common, everyday tasks—and not just specialized ones—with a success rate between 80% and 90%. AGIBOT is part of a wave of Chinese startups https://fortune.com/2026/06/09/china-builds-85-percent-worlds-humanoids-robots-cheap/ developing humanoid and quadruped robots. With 9,700 units shipped during the first six months of the year, AGIBOT is the top seller of humanoid robots, according to data from Counterpoint Research https://counterpointresearch.com/en/insights/global-humanoid-robot-shipments-soar-nearly-300-percent-yoy-in-h1-2026 released in late August. The startup is considering an IPO in Hong Kong. While robot dance performances and boxing matches get headlines, manufacturers are frantically searching for real-world applications for their tech. Shanghai-headquartered Keenon Robotics https://www.scmp.com/tech/tech-trends/article/3319728/back-basics-softbank-backed-keenon-robotics-takes-pragmatic-approach-humanoids , for instance, has rolled out robots aimed at automating hotel services. Wan Bin, Keenon’s chief operating officer, noted that one Shanghai-based hotel is using five robots to greet guests, deliver room service, clean rooms, and manage the restaurant floor. “This scene is one that will become increasingly common in the future.” Other robot manufacturers hope to apply their products in more industrial settings. “We’ve invested very heavily in developing robots for the industrial sector,” said Jianxin Pang, UBTech’s vice president and vice dean of research. “But first, we’re starting with relatively common scenarios with a big enough market—that helps us ensure return on our investment.” Yet many humanoid companies acknowledge that building robots for industry is no simple task https://fortune.com/2025/11/28/china-warns-of-bubble-risks-in-booming-humanoid-robots-arena/ . “It’s genuinely difficult for today’s humanoid firms to develop a robot that can run stably inside a factory,” Yao acknowledged. “Industry players are brutally honest: They care about four metrics—success rate, cycle time, stability and cost—rather than what technology is used. From that standpoint, we absolutely have to train our robots to 100% efficacy first.” In late June, AGIBOT ran a six-day livestream that demonstrated that its robots hit a 99.99% success rate completing over 64,000 manufacturing tasks https://interestingengineering.com/ai-robotics/china-agibot-robots-hit-99-percent-success-during-six-day-live-factory-demo . Reaching that milestone required eight-hour sessions in the middle of the night for a month, Yao said on-stage. Still, Yao was optimistic that embodied AI would follow the same scaling law that transformed large language models. “Most industry teams believe that embodied AI will follow the exponential scaling law we discovered in digital intelligence and large language models,” Yao said. “As data volume rises and your model’s parameter count grows, there will definitely be a step-up in intelligence.” Exclusive: In a new sit-down interview with Fortune , OpenAI CEO Sam Altman explains safety standards are "not at a place" to push AI capabilities much further and warns AI beyond human control is "absolutely" possible. Watch or listen here.