The results show that the coefficient of the variable Ai is 0.0469 and that it passes the 1% significance test. First, as a general-purpose technology, artificial intelligence can accelerate learning and knowledge creation, increase investment in R&D and talent in manufacturing companies and promote technological progress in manufacturing companies, and promote technological progress in manufacturing companies, thus improving energy efficiency. In this way, it expands current research on the relationship between AI and the energy efficiency of manufacturing companies. The document clarifies both the impact of artificial intelligence on the energy efficiency of manufacturing companies and its mechanism of action; this will help provide a reference for future decision-making designed to improve the energy efficiency of manufacturing companies.
It shows that there is still a significant positive correlation between artificial intelligence and business energy efficiency variables. The results show that the era of manufacturing companies inhibits the promotion of artificial intelligence in terms of energy efficiency. Judging by the current state of business energy efficiency, the impact of artificial intelligence on corporate energy efficiency is due more to technological progress. The better the company's performance, the more sufficient funding manufacturing companies will have to play the role of intelligent transformation.
The conclusions drawn can only represent the short-term impact of artificial intelligence on the energy efficiency of manufacturing companies. Sech is the change in the efficiency of the scale, which indicates the influence of the economy of scale on the total energy efficiency of factors. Encourage high-tech manufacturing companies to vigorously develop artificial intelligence, make the most of the knowledge and technological repercussions provided by artificial intelligence, promote business technological innovation and improve energy efficiency. Other scholars believe that innovations in artificial intelligence and information and communication technology have led to a decrease in the unit cost of energy.
By taking advantage of the features and benefits of these devices, it is possible to reduce carbon emissions and, at the same time, improve energy efficiency. AI can have a significant impact on the food supply chain by optimizing sensors and data and reducing inefficiencies and costs. The second is that manufacturing companies with greater energy efficiency in production tend to be manufacturing companies with higher levels of artificial intelligence, so there are synergy biases.
