In April 2023, the government of Changshu City, in Jiangsu Province, China, announced that it would officially use digital Chinese Yuan (E-CNY) as a method of wage payment to the government and state-owned enterprises staff starting in May. With the gradual improvement and application of E-CNY technologies, such as no electricity, no internet payment (offline payment), and the programmability of smart contracts, E-CNY will be officially used in China. CNN said China is on the verge of a cashless society. The advantages of E-CNY have a positive role in promoting the Chinese government’s implementation of the development goals of a low-carbon and sustainable economy. However, artificial intelligence (AI) trust concerns are the primary bottleneck in the current development based on intelligent algorithms and digital information technology. AI trust concerns are affecting the scope of use of E-CNY, and it may need to achieve effective scale-use, making it promote low-carbon and sustainable development. From the industry perspective, this article selects the housing rental enterprises, which are challenging to develop and energy-intensive, to analyze the theoretical approach and practical impact of E-CNY in promoting the low-carbon and sustainable development of China’s rental housing economy. Meanwhile, from the perspective of Chinese consumers, the impact of AI trust concerns on E-CNY in promoting low-carbon and sustainable development is analyzed in this article.

The financial inclusion program in Asia has begun to be carried out intensively, focusing on increasing public access, especially for people who have yet to enjoy banking services. This makes financial inclusion one of the development focuses in the financial sector in various countries, especially in the Asian region. This study compares the financial inclusion level and socioeconomic variables’ influence on financial inclusion in Asian countries in 2010–2022. To compare the level of financial inclusion in several Asian countries, the Index of Financial Inclusion (IFI) analysis method was used, while to examine the relationship between socioeconomic variables on financial inclusion, the Ordinary Least Square (OLS) method was used with an estimation technique, in the Fixed Effects Model approach. The results of this study indicate that, in general, financial inclusion in several Asian countries is mainly influenced by the usability dimension. In addition, only the variable GDP per capita is partially influential. While other variables, namely, the unemployment rate and population in rural areas, significantly influence the financial inclusion index.