Accelerating the deep integration of AI and the real economy is an important engine for China to achieve leapfrog development of science and technology, industrial optimization and upgrading, and supply-side structural reform. How to use AI for the transformation and upgrading of traditional industries and the transformation of economic development mode has become an important issue in China′s economic development. Based on the perspective of cost stickiness, this paper empirically examines the impact and mechanism of AI on enterprise cost stickiness by taking A-share listed companies in Shanghai and Shenzhen from 2011 to 2018 as research samples.

     The main conclusions are as follows: First, AI has a restraining effect on enterprise cost stickiness and can play a role in reducing costs. Second, in the enterprises with higher adjustment cost and more serious agency problem, AI has a more significant inhibition effect on cost stickiness, indicating that AI can affect cost stickiness through reducing adjustment cost and alleviating agency problem. Third, the inhibition effect of AI on enterprise cost stickiness mainly comes from the commercial application of AI, and there is no significant relationship between AI research and development and cost stickiness. Fourth, after distinguishing different cost factors, AI will restrain the cost stickiness of material resources and increase the cost stickiness of human resources, indicating that AI will increase the demand for high-end technical talents while reducing the cost of materials.

     The possible research contributions of this paper are as follows: First, it innovatively adopts the method of combining text mining and artificial research and judgment to construct enterprise-level AI data, and distinguishes AI research and development from AI application mode, so as to provide reference for AI research at enterprise micro-level. Second, existing literature has explored the impact of AI on labor market and economic development from the macro level, while some literatures have focused on the impact of AI on micro enterprises. Different from previous studies, this paper discusses the cost reduction effectiveness and path of AI enabling real enterprises from the perspective of cost stickiness, which not only provides new ideas for promoting the rapid development of real enterprises, but also extends the relevant research on the economic consequences of AI. Third, cost reduction is an important part of the transformation and upgrading of real enterprises in the context of big data. Different from the perspective of internal governance mechanism and external environment, this paper explores the impact of AI on cost stickiness from the perspective of micro enterprises, which not only enriches the research on the influencing factors of cost stickiness, but also adds new evidence for scientific and technological progress to promote the reduction of cost, improvement of quality and efficiency of real enterprises.

     Based on the above research conclusions, this paper puts forward the following countermeasures and suggestions for accelerating the deep integration of AI and physical enterprises:

    At the national level, we will, on the one hand, continue to strengthen the promotion of AI research and development and commercial implementation, improve the penetration rate of AI, use AI and other new information technologies to drive high-quality economic development, and create a good innovation environment for the high-quality development of traditional enterprises. On the other hand, we should establish and improve AI incentive policies, give enterprises preferential policies related to AI, encourage enterprises to speed up the process of AI research and development and commercial landing, and promote the transformation and upgrading of traditional enterprises, so as to transform the mode of economic development and promote high-quality economic development.

      At the enterprise level, we can see that firstly, according to their own development needs, traditional entities can speed up the deep integration with AI, especially the application of AI in production, operation and management activities, so as to help them optimize cost management, accelerate transformation and upgrading and improve the quality of development. Secondly, in the process of accelerating the deep integration with AI, traditional enterprises should continue to increase the research and development of AI to maintain their core competitiveness. Thirdly, the research and development and application of AI cannot be separated from the support of high-end information technology talents. Therefore, enterprises should focus on cultivating and recruiting high-level talents related to AI to provide talent support for the entity enterprises with AI empowerment.