Discussion on the Application Status and Optimization Direction of

Artificial Intelligence Introduced into Enterprise Management and

Operation Systems

Zhibin Feng

College of Computer Science and Technology, Dongguan University of Technology, China

Keywords: Human-Machine Integration, Enterprise Management, Artificial Intelligence.

Abstract: Artificial intelligence (AI) technology, as the core driving force of the new round of scientific and

technological innovation and industrial change, impacts the market competitiveness of enterprises and the

composition structure of sustainable development conditions. Based on the current status of the application

of the new human-machine integration mode of AI technology introduced into the enterprise management

and operation system, this paper analyzes the existing technology application and drawbacks and explores the

optimization path of the enterprise's application of the new human-machine integration mode from the four

dimensions of the management object, attributes, decision-making and ethics. This paper concludes that the

introduction of AI technology resources in enterprises requires enterprise managers to reconfigure the

resource management model and coordinate the human-machine relationship. At the same time, managers are

required to improve their technical quality, combine technical theories and management frameworks, and

optimize the traditional management operation mode of enterprises. In addition, the participation of AI

technology in decision-making requires enterprise managers to coordinate the ratio of human-machine

decision-making, and proactively prevent possible risks in technology-assisted decision-making and

prediction. Finally, enterprises need to proactively prevent the legal and ethical risks that may exist when AI

technology is applied.

1 INTRODUCTION

According to the report of relevant market research

organizations, the global artificial intelligence market

size was valued at USD 279.22 billion in 2024 and is

projected to grow at a CAGR of 35.9% from 2025 to

2030, while the scale of China's core artificial

intelligence industry had reached 508 billion yuan in

2022 with a year-on-year growth of 18% (Grand view

research, 2025; People's Daily Online, 2023). The

commercialization of AI is accelerating against the

backdrop of AI technology and hardware and

software-related industries developing together and

rapidly penetrating various traditional and emerging

industries. The extensive introduction of AI

technology into enterprises and the in-depth

application in combination with different application

scenarios have become an inevitable trend to promote

fundamental changes in the management and

operation mode of global enterprises.

The development trend of the artificial

intelligence industry indicates that compared with

vertical artificial intelligence, general artificial

intelligence is no longer limited to handling a single

task, and is has gradually realized the application of

cross-domain, cross-discipline, cross-task and cross-

modal (People's Daily Online, 2023). The high-speed

iterative development of AI technology and its high

adaptability in different industries with a great span

of association indicates that the practical application

of human-machine integration mode in enterprises in

different industries is not limited to the "human-

oriented and machine-assisted" single-principle

development mode of manufacturing enterprises in

the traditional business environment proposed by Hui

Xu, Zepeng Wang, and Jindong Yang, et al. The

"human-oriented, machine-assisted" single subject

development model practiced by manufacturing

enterprises in the traditional business environment,

that is to say machines are only regarded as auxiliary

production tools (Xu et al, 2024). Instead, a new

human-machine integration model has been

Feng, Z.

Discussion on the Application Status and Optimization Direction of Artiﬁcial Intelligence Introduced into Enterprise Management and Operation Systems.

DOI: 10.5220/0014306800004718

Paper published under CC license (CC BY-NC-ND 4.0)

In Proceedings of the 2nd International Conference on Engineering Management, Information Technology and Intelligence (EMITI 2025), pages 17-22

ISBN: 978-989-758-792-4

developed that takes artificial intelligence technology

as a key technical condition for enterprise

management and operation. At the same time, Xu

Peng, Xu Xiangyi and others proposed that the impact

of artificial intelligence technology on the enterprise

management and operation system can be reflected in

the four dimensions of "management objects",

"management attributes", "management decisions"

and "management ethics". While promoting the

optimization of enterprise management and operation

systems and the reconstruction of human-machine

collaboration models, it also poses challenges to

managers in the era of artificial intelligence.(Xu et al,

2020). In this context, most of the traditional and

emerging enterprises still lack a lot of theoretical and

practical experience in the application of AI

technology to optimize the traditional management

and operation mode of enterprises, and there are still

problems that need to be solved, such as loss of

enterprise benefits due to improper application of the

technology, inefficient application, and poor

application of risk management.

The purpose of this paper is to explore the

optimization path of enterprise application of new

human-machine integration mode by combining the

related field research and the application of artificial

intelligence technology introduced into the enterprise

management and operation system. On the one hand,

this paper discusses the application of existing

artificial intelligence technology in enterprises. On

the other hand, this paper discusses the existing

drawbacks and shortcomings of the technology

application and the feasible optimization direction

from the above four management dimensions.

2 IMPACTS AND CHALLENGES

OF THE HUMAN-MACHINE

INTEGRATION MODEL ON

ENTERPRISE MANAGEMENT

AND OPERATION METHODS

The new human-machine integration model driven by

artificial intelligence technology is becoming a key

driver for the development of international

enterprises. Many enterprises have made significant

progress in process optimization and technology

application and accumulated valuable practical

experience by deeply integrating AI technology with

management and operation processes.

The high degree of integration of AI technology

with machine learning, big data, cloud computing, the

Internet of Things, blockchain and other technologies

has enabled it to gain efficient and powerful

information processing and analytical learning

capabilities. This integration makes the various

management and operation processes of the

enterprise have the ability of self-perception, learning

and decision-making (Chen et al, 2024), which has

become an important driving force to help enterprises

achieve significant results in decision support,

process optimization, cost control, innovation and

development (Shao, 2024). Taking the supply chain

logistics industry as an example, through the

integration of blockchain and AI technology, two

enterprises, Jingdong and Alibaba, the enterprise has

realized the automation, intelligence and efficiency

improvement of supply chain logistics, thus realizing

the reduction of logistics management costs, the

improvement of process efficiency and the

enhancement of overall market competitiveness

(Chen et al, 2024). At the same time, artificial

intelligence technology also assists enterprises to get

rid of the limitations of manual data processing, and

enables enterprises to obtain powerful market data

analysis, simulation and prediction capabilities, in

order to assist enterprises in making more accurate

and high-quality decisions in internal management

and external market interaction. For example, deep

learning, an advanced branch of artificial intelligence

technology, applies a model design similar to neural

networks, and through the construction of a

hierarchical structure, it can simultaneously

understand and analyze the appearance and internal

logic, thus realizing a deep understanding and

simulation of the market trends, user needs and the

internal operation mode of the enterprise, and thus

helping the enterprise to solve deeper and more

complex problems (Sun et al, 2024). For example, the

Jinghui supply chain system researched by Jingdong

Logistics utilizes AI for optimal solution derivation,

algorithm scheduling, and model prediction, and

ultimately employs simulation analysis for intelligent

decision-making (Pan et al, 2024). Alibaba, on the

other hand, uses a digital supply chain control tower

driven by AI technology to predict risks through data

mining and provide decision support for supply chain

management (Chen et al, 2024). The introduction of

artificial intelligence technology has brought the

traditional management and operation model of

enterprises to a more lean and intelligent level. It can

not only provide valuable auxiliary information for

corporate decision-making, but also assist enterprises

in exploring management pain points and market pain

points, assist enterprises in reconstructing and

optimizing management and operation models, and at

the same time guide enterprises to make lower-risk

EMITI 2025 - International Conference on Engineering Management, Information Technology and Intelligence

decisions and choose a more suitable development

direction for the enterprise, so that enterprises can

maintain strong market competitiveness and internal

innovation capabilities in their industry fields.

Although the new human-machine integration

mode of applying artificial intelligence technology

can bring great management and operation benefits to

enterprises, most enterprises are still suffering from

the high cost of applying the technology, shortage of

related technical personnel or the conflict of

adaptation with the traditional enterprise

management and operation mode, so there is still a lot

of room for optimization of the practical application

of this technology in the management and operation

system of enterprises.

The traditional human-machine integration model

pays less attention to human-machine interaction

design and machine performance improvement,

which leads to frequent human-machine conflicts (Xu

et al, 2024). Analyzed from the level of the

technology users, the reasons for the emergence of

human-machine conflict events are mainly

manifested in the weak digital foundation of the users,

and the technical quality of the enterprise users is

difficult to practice the technology in the actual work.

And at the level of machine technology, the reason

mainly appears in the lack of effective and high-

quality data collection when the technology is

applied, and it is difficult for the machine to optimize

the algorithm through data training and machine

learning, which leads to the inability of the machine

to match with the corresponding business, resulting in

the misuse and waste of data and technology.

At present, professional talents are scarce in the

field of artificial intelligence within China, especially

composite talents who have both a deep technical

background and can combine AI technology with the

practical aspects of industry management (Huang,

2019). Enterprises often face a shortage of relevant

technical talents in the process of digital

transformation, or are limited by the technical level of

managers, making it difficult to maximize the

effectiveness of AI technology resources, and failing

to truly achieve the deep integration of the

management and technical layers. Most enterprises

still rely on ready-made experience from other

enterprises, or rely on imported hardware and

software, technology and other phenomena, these

dependence phenomena for the enterprise to bring the

low degree of technology adaptation, data leakage

risk, imported technology monopoly and other

problems.

At the same time, the actual application of

enterprise technology due to the negligence of data

security issues, or lack of standardized management

of data, data leakage, data forgery and other data

security incidents often occur. The frequent

occurrence of enterprise data security incidents

demonstrates the risk of improper application of

technology, and how to effectively protect enterprise

data security when applying technology poses a

challenge to both enterprise managers and the

security optimization of the technology itself.

The problems mentioned above have become

obstacles to the application of the human-machine

integration model in enterprises, and have also

dampened the enthusiasm of enterprises to deploy AI

technology in practice, making it an urgent challenge

for enterprises and the AI field to carry out synergistic

development at present.

3 DISCUSSION ON THE

FEASIBILITY OPTIMIZATION

DIRECTION OF NEW

HUMAN-MACHINE

INTEGRATION MODEL IN

ENTERPRISE APPLICATION

With the introduction of artificial intelligence

technology, enterprises have achieved all-round

optimization and breakthroughs in various

management and operation processes, such as

accuracy, stability and high efficiency. However,

while this technology has brought technological

innovation and huge opportunities to enterprises, it

has also had a subversive impact on traditional

enterprise management theories and human-machine

relationships. Artificial intelligence innovation

management refers to the strategic deployment,

application and monitoring of artificial intelligence

technology within an organization, aiming to

optimize enterprise operations and enhance

competitiveness (Yi et al, 2024). According to the

research of Xu Peng, Xu Xiangyi and others, the

change logic and optimization direction of artificial

intelligence technology affecting enterprise

management and operation systems can be

specifically divided into the following four

dimensions, namely "management objects",

"management attributes", "management decisions"

and "management ethics" (Xu et al, 2020).

First of all, in the dimension of management

object, the gradually mature artificial intelligence

technology is no longer limited to being a tool to

assist corporate business. With the development of AI

Discussion on the Application Status and Optimization Direction of Artiﬁcial Intelligence Introduced into Enterprise Management and

Operation Systems

technology, its role in corporate management

continues to evolve. From being an auxiliary tool to

improve efficiency, it has gradually developed into a

"virtual workforce" with autonomous learning and

execution capabilities and has partially replaced

traditional human labor in some areas. Changes in

management objects require managers to reshape the

corporate management framework, break away from

dependence on traditional management theories and

management experience, and use artificial

intelligence technology as a low-cost, high-efficiency

technical resource in the corporate management

system. Managers should coordinate the collaborative

relationship between human employees and artificial

intelligence systems, give full play to the data

processing advantages of machines and the logical

decision-making capabilities of humans, achieve

complementary advantages, and promote the digital

transformation of enterprises and the optimization of

human-machine integration management models.

Secondly, in terms of management attributes, the

introduction of artificial intelligence technology into

the management system of enterprises has made the

technical nature of enterprise management the

dominant attribute. The first and most basic

requirement is proficiency in the use of digital

technology, enterprise managers need to combine the

knowledge of related fields and the actual application

scenarios of the enterprise to maximize the

capabilities of artificial intelligence technology. At

the same time, it also puts forward quality

requirements for other employees who participate in

the human-machine integration work mode of the

enterprise, requiring employees to be able to operate

the human-machine integration mode efficiently and

improve the overall competitiveness of the enterprise

in the era of digital transformation. Secondly, it is a

requirement for the management technology

optimization ability of enterprise managers.

Enterprise managers are required to master the ability

to allocate resources, flexibly adjust the management

structure according to the resource situation of the

enterprise, reasonably allocate human resources and

technical resources, and maximize the respective

advantages of resources. At the same time, enterprise

managers are also required to have the ability to

regulate enterprise resources and combine the data

analysis ability of artificial intelligence technology to

conduct macro-control and risk prevention of

possible risks and enterprise losses in resource

planning. In order to improve the technical nature of

enterprise management, enterprises should cooperate

with scientific research institutions or universities,

actively introduce compound management talents,

and make up for the talent gap in combination with

the situation of the enterprise. In addition, enterprises

should also organize technical training internally to

improve the overall quality of the enterprise and adapt

to the intervention of artificial intelligence

technology with the overall high technical strength of

the enterprise.

Thirdly, in terms of management decision-making,

artificial intelligence technology can assist human

beings in breaking through the limitations of human

technical processing and analytical capabilities,

combined with complex, multi-dimensional data to

give simulation prediction results, assisting business

managers to make decisions. Changes in management

decision-making require enterprise managers to have

the logical ability of innovative thinking so that they

can analyze the actual situation according to the data

fed back by the machine, and make optimal decisions

by combining the actual data and the auxiliary

suggestions of artificial intelligence. There are two

main optimization paths: first, enterprise managers

need to use artificial intelligence technology to assist

decision-making at the same time pay attention to the

ratio of human-machine decision-making, do not rely

excessively on technology to assist decision-making,

should be combined with the actual situation of the

enterprise to carry out a reasonable analysis, to make

the optimal decision for the interests of the enterprise.

Enterprise managers should strengthen the cultivation

of decision-making thinking, reduce technological

dependence, and regard artificial intelligence

technology as an auxiliary tool rather than a decision-

maker. Secondly, the technology applied to the

enterprise needs to be continuously strengthened and

optimized algorithmically. The core of artificial

intelligence depends on data, and the quality, quantity

and management level of data will directly affect the

effect of the application (Shao, 2024). Enterprises

should cooperate with scientific research institutions

in related fields, provide real and high-quality data for

scientific research institutions, train and algorithms

through data, conduct more in-depth research on the

application of technology in the process, customize

enterprise application scenarios, adapt to the

management process of the enterprise, and promote

the optimization of human-machine integration mode

with the enterprise's self-research and experience

system without relying on the ready-made experience

of other enterprises. In this way, the accuracy of the

algorithm prediction can be improved, and the risk of

bias that may occur when enterprises use AI

technology to make predictions and assist in decision-

making can be reduced.

EMITI 2025 - International Conference on Engineering Management, Information Technology and Intelligence

Fourth, in terms of management ethics, the

development of artificial intelligence technology has

put forward new requirements for the soundness of

the legal system and also put forward management

ethical constraints on the application of this

technology by enterprises, which should always pay

attention to not touching the legal boundaries and

industry taboos in the practical application of

artificial intelligence. Enterprises should pay

attention to data security design when applying the

technology to avoid enterprise data leakage caused by

improper technology application or management.

Enterprise managers can strengthen enterprise data

security from the following two points. First,

managers should formulate standardized processes

for technology use applicable to enterprises to avoid

risky operations with higher uncertainty and potential

negative consequences for enterprise employees

using AI technology due to the lack of normative

constraints; second, enterprise managers should

manage permissions for AI technology and its users

to protect the access and use permissions of important

enterprise data, and strictly control.

4 CONCLUSIONS

This paper discusses the main reasons for the

emergence of human-machine conflict events in

enterprises and analyzes the feasible optimization

direction of enterprise human-machine integration

mode, and draws the following conclusions:

At the level of artificial intelligence technology,

the main optimization direction at this stage is to

adapt to the application scenarios of various

industries and develop enterprise customized in-

depth application modes to match the enterprise

business and improve the degree of integration with

human employees; secondly, the artificial

intelligence technology should also continue to

strengthen and optimize the algorithms using data

training, so as to improve the accuracy rate of

assisting managers in decision-making, and to reduce

the risk of prediction bias and decision-making errors.

At the level of enterprises and their managers,

firstly, enterprise managers should actively improve

their technical ability in the field of artificial

intelligence, and combine it with enterprise

management theory to reconstruct and improve the

management and application system of enterprise

human-machine integration mode, so as to transform

the enterprise's human-machine conflict state into a

human-machine integration mode; secondly,

enterprise managers should also reasonably allocate

enterprise resources and optimize the application of

human and machine resources; third, enterprises

should actively improve the overall quality of

enterprise employees, to adapt the technology

introduced and applied to the actual business, to play

the maximum benefit of artificial intelligence

resources. Finally, enterprises should strengthen

enterprise data security management to avoid data

security incidents caused by improper application of

technology.

At the legal and ethical level, enterprises should

work with resources from all walks of life to comply

with the legal boundaries of technology application,

assist in the improvement of legal regulations in

related fields, clarify the main body of responsibility,

and jointly maintain the market environment for the

legitimate application of AI resources by enterprises.

In-depth application and development of

enterprise-customized human-machine integration

mode has become a key condition for enterprises to

have sustainable market competitiveness. In the

future, enterprises should grasp the opportunities

brought by the development of technology, actively

face the challenges at all levels, synchronize and

actively explore the theory and practice level, and

open up the development path of enterprise

management and operation system highly integrated

with high technology.

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