Recently, the State Council issued the "Opinions on Deepening the Implementation of the" Artificial Intelligence+"Action", which deployed the improvement of "Artificial Intelligence+" consumption quality as a key action and clarified multiple measures to expand new scenarios of service consumption. In recent years, the role of service consumption has become increasingly prominent. According to data released by the National Bureau of Statistics, the added value of China's service industry will account for 56.7% of the country's gross domestic product in 2024, contributing 56.2% to the national economic growth. However, the service consumption sector is facing deep-seated constraints such as uneven supply of high-quality services, difficulty in meeting personalized needs, difficulty in breaking through temporal and spatial limitations, and uneven service experiences. With its powerful data processing, intelligent pattern recognition, precise predictive analysis, and natural interaction capabilities, artificial intelligence provides a key to solving difficult problems. Artificial intelligence empowers service consumption in multiple dimensions. AI, based on natural language processing, computer vision, and deep learning algorithms, can provide highly anthropomorphic and precise interactive services, fostering new consumer desires. For example, platforms such as Tmall and JD.com use technologies such as virtual makeup and virtual fitting to make online shopping experience infinitely close to offline, creating a new interactive shopping scene of "what you see is what you get". AI has also created service categories that were previously unimaginable, opening up new areas of consumption. For example, in cultural and tourism consumption, some museums have created immersive cultural and tourism experience projects through technologies such as AI tour guides and VR virtual roaming, creating new growth points for cultural experience consumption. AI has also significantly reduced the cost and price of providing services by optimizing supply chains, predicting consumer trends, precision marketing, dynamic pricing, etc., enabling more high-quality services to reach a wider range of consumer groups in a more accessible way. In addition, AI has promoted the cross integration of different service formats, giving rise to a new model of "service+". For example, "car+entertainment" corresponds to a mobile intelligent cockpit, "retail+catering+experience" gives rise to a new generation of smart stores, and "home+health+safety" builds a whole house intelligent ecosystem. These fusion scenarios create a consumer value of "1+1gt; 2". We must also be aware that the consumption of "artificial intelligence+" services still faces a series of challenges. For example, the training and application of AI heavily rely on high-quality data. However, the current phenomenon of data silos is widespread, and data between different platforms and enterprises is difficult to legally and compliantly circulate and share, which limits the breadth and depth of AI model training. Meanwhile, issues such as information cocoons, algorithmic discrimination, and privacy breaches still exist, which constrain the healthy development of the service consumption sector. Effectively resolving these challenges and expanding new scenarios of "artificial intelligence+" service consumption require the joint efforts of the government, enterprises, and society. Improve legal protection and build a strong security barrier. Establish and improve the legal system for the development, provision, and use of artificial intelligence products and services, so that artificial intelligence technology can develop in a standardized manner. Strengthen the enforcement of laws such as Cybersecurity Law, Data Security Law, and Personal Information Protection Law, and crack down severely on data abuse and leakage. To establish a secure, controllable, inclusive and fair data element circulation system, promote the legitimate and compliant sharing and utilization of data resources while ensuring national security and personal privacy, and build a data utilization environment that consumers can trust. Tackle core technologies and deepen scene integration. Enterprises and research institutions should strengthen the collaboration between industry, academia, and research, focusing on breaking through the technological bottlenecks of AI in understanding complex contexts, generating empathy and interaction, and ensuring safety and controllability. We need to deeply explore the pain points and needs in key service areas such as healthcare, elderly care, education, and cultural tourism, develop AI applications that truly solve practical problems and create core value, improve the quality of life services such as entertainment, e-commerce, home economics, property management, travel, elderly care, and childcare, expand new service consumption scenarios such as experiential consumption, personalized consumption, cognitive and emotional consumption, deeply adapt technology to real consumption needs and specific service scenarios, and achieve a leap from "usable" to "easy to use" and "love to use". Multi party collaboration and linkage to improve digital literacy. Mainstream media should take on the social responsibility of popularizing AI knowledge and enhancing public awareness. By producing science popularization programs, publishing public service advertisements and other forms, interpreting the concept of AI, exposing and criticizing digital fraud methods, advocating rational consumption concepts, and creating a good atmosphere of understanding numbers, being good at technology, and ensuring safety in the whole society. Public cultural service institutions such as libraries should carry out inclusive digital skills training for key populations such as the elderly and low-income groups. Primary and secondary schools should offer general courses on digital literacy to enhance soft skills such as data ethics, algorithmic thinking, and network security. (New Society)