AI在机器人领域的承诺在于降低编程复杂度与成本门槛，赋予机器人自主学习与多工处理的能力。然而，当前阻碍此一愿景实现的首要挑战是制造业数据的匮乏，因为机器人软体模型需要大量且多样化的实际生产数据来进行训练，而这需要制造商愿意共享数据。
尽管面临数据短缺与安全防护等挑战，自动化仍是美国重回制造业强国并解决未来劳动力短缺的关键。随著技术进步，未来的机器人将从工厂与仓库走向餐厅、医院甚至营建工地等更多日常场景，逐步实现经济成长与人口成长的脱钩。
The US industrial robot industry is currently facing a growth bottleneck due to low expansion rates and highly customized projects, but the integration of artificial intelligence (AI) offers hope for a significant transformation. Despite the widespread excitement surrounding humanoid robots and autonomous operations, the reality on factory floors remains complex and challenging, leading to a post-pandemic decline in robot orders.
The promise of AI in robotics lies in reducing programming complexity and cost barriers, thereby giving robots the ability to self-learn and perform multiple tasks. However, the primary challenge hindering this vision is the scarcity of manufacturing data, as robotic software models require vast amounts of real-world production data for training, which requires manufacturers to share their proprietary information.
Despite challenges such as data scarcity and safety concerns, automation remains critical for the US to reshore manufacturing and address future labor shortages. As technology improves, future robots are expected to expand beyond factories and warehouses into daily settings like restaurants, hospitals, and construction sites, eventually decoupling economic growth from population growth.