Currently, a new round of technological revolution and industrial transformation is accelerating, and data has become a key production factor after land, labor, and capital. With the intensive implementation of the national "Artificial Intelligence+" initiative and market-oriented policies for data elements, how to make massive data "live, usable, and compliant" has become the core proposition for promoting high-quality development of the digital economy. The industry generally believes that the marketization of data elements, the coordinated development of artificial intelligence and trusted data space, are the three pillars of the transformation of the digital intelligence industry. The relationship between these three can be likened to a car: the marketization of data elements is like an 'oil supply system', connecting the conversion path of data from resources to assets and then to capital; Artificial intelligence plays the role of the 'engine', forming a positive cycle of 'data model application'; The trusted data space is the 'security foundation', building a cross subject and cross industry data collaboration network. ”Wang Yong, founder and chairman of Evan Technology, stated in an interview with reporters that the synergy of the three is necessary to drive the stable operation of the digital economy. The road from laboratory to industrialization is not an easy one for the marketization of data elements. Wang Yong believes that the current data factor market in China still faces the dual challenges of "more data but less useful" and "weak AI basic theory and underlying algorithms". On the one hand, massive amounts of data are difficult to form high-quality "data fuel" due to the lack of standardized governance; On the other hand, there is a stubborn problem of "not daring to use, unwilling to use, and not knowing how to use" in public data, which restricts the release of data value. To overcome these bottlenecks, not only do we need breakthroughs in technology, but we also need collaborative innovation in systems and ecosystems. He believes that the future competition will be about "competing for comprehensive strength", which means building a high-quality data supply ecosystem, cultivating rich application scenarios, and tackling core technologies in computing power and algorithms to solidify the foundation of digital development. In recent years, China has intensively introduced top-level designs such as data infrastructure systems, marketization of data elements, and trustworthy data spaces, laying out a path for compliant circulation and efficient value release of data resources. The industry has broken through with technological innovation and scenario implementation, exploring practical paths for marketization of data elements. As an AI driven data intelligence service provider, Evan Technology's practice provides evidence for the above viewpoint. According to Wang Yong, in the financial field, the company helps banks build a cross institutional risk control collaborative system through IP positioning, device fingerprinting, and privacy computing technology, increasing the fraud transaction interception rate by 40%; In the medical field, relying on a trusted data space to achieve multi-party data that is "available but invisible, and traceable throughout the process", supporting new drug research and multi center scientific research; In the field of education, using behavior modeling to assist in campus student safety warning; In the field of enterprise services, AI generated bidding documents and environmental impact assessment reports can help enterprises improve efficiency and reduce costs. These cases demonstrate that the integration of data and AI has released measurable value in areas such as social governance and livelihood services. Looking ahead to the next three to five years, Wang Yong predicts that the deep integration of AI and the real economy will present three major trends: data governance will move from "optional" to "essential", and high-quality industry datasets will become the core competitiveness; Vertical intelligent agents have become the mainstream form, forming a closed loop of "perception analysis decision execution iteration"; The construction of industrial ecology relies more on the collaborative mining of data value between leading benchmark enterprises and users. We should accelerate the release of policy signals, promote the reform of majors in universities, cultivate 'composite and multi-level' talents, and build a solid foundation for the development of the digital economy. ”Wang Yong suggested. (Looking into the New Era)