As high-end scientific instruments are crucial for a nation, they are currently undergoing intelligent and precise upgrades through 'AI+' technology. At the 19th China Conference on Scientific Instrument Development, the demand for instrument intelligence among researchers became a focal point. Traditional research relies on manual experimentation, which is prone to issues such as large errors, low efficiency, and data silos. In contrast, AI-driven robotic platforms can automate complex calculations and experimental operations, ensuring efficient and accurate data integration. Li Jinghong, an academician of the Chinese Academy of Sciences, pointed out that AI is reshaping the research paradigm. By combing through vast amounts of literature, conducting intelligent data analysis, and constructing pre-trained models, AI can carry out massive experiments and material screenings to obtain high-quality data. For example, the full-process robotic chemist developed by the University of Science and Technology of China shortened the discovery cycle of high-entropy catalysts from 1,400 years under traditional methods to just five weeks. The integration of AI and scientific instruments has transitioned from concept to implementation, becoming a core driver for enhancing research efficiency and transforming research paradigms. Tang Haixia, the organizer of the conference, stated that 'AI4S' (AI-driven scientific research) promotes data-driven scientific discovery, significantly elevating the strategic importance of instruments as data acquisition gateways. AI technology has penetrated into data acquisition, processing, decision-making, and other aspects, driving the transformation of instruments from 'measurement tools' to 'intelligent analysis platforms' and enabling rapid applications in high-throughput experiments, automated laboratories, and other scenarios. Currently, instruments such as mass spectrometers and spectrometers are widely integrating AI-assisted analysis functions amid accelerated localization efforts, while upstream core components are upgrading from 'supporting roles' to 'performance hubs'. The development of scientific instruments is characterized by long cycles, small-batch production, multiple varieties, and high entry barriers, requiring collaborative breakthroughs from industry, academia, and research. To this end, Beijing has introduced the Action Plan for Innovative Development of High-End Scientific Instruments (2025-2027), leveraging funds, universities, and incubation platforms to bridge the 'last mile' of technology transfer (technological achievement commercialization) and establish an innovative landscape featuring 'pilot testing in the north and incubation in the south' to support the implementation of original innovations.