Challenges of AI Adoption in China Public Service and its Impact on Efficiency and Performance

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INTERNATIONAL JOURNAL OF ACADEMIC RESEARCH IN BUSINESS AND SOCIAL SCIENCES
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Challenges of AI Adoption in China Public Service
and its Impact on Efficiency and Performance
Li Xiaoyan, Dr. Reynaldo Gacho Segumpan
City Graduate School, City University Malaysia
Email: 598475107@qq.com, dr.reynaldo@city.edu.my
Abstract
AI is one of the most discussed technologies and is anticipated to reshape public services in
the future in China to enhance the quality of services and thus promote the growth of the
economy in the respective country. This paper aims to assess the current position, potential
and challenges of implementing AI in the Chinese public sector. The research adopted the
interpretative research philosophy and inductive research approach to investigate the
implications of AI in organizations and the sociopolitical, economic and ethical concerns
through interviews, questionnaires and case analysis. From the review, it is apparent that the
development of AI has continued to enhance in the current world especially in aspects such
as health, learning institutions, and transport through cities, this is due to the support from
companies such as Alibaba, Tencent, and Baidu. However, the study also reveals that several
barriers prevent AI from being implemented, namely some of these are about the job, tools,
competencies and professionalism such as data and algorithms. The consequences of these
challenges on efficiency and performance of public services are tremendous, which can cause
problems such as workforce breakdown, decrease in productivity, and loss of public
confidence. The study suggests how AI can be effectively integrated into talent management,
government-industry-academia partnerships, effective policies, data sharing, and investment
in AI infrastructure. Future work should aim at carrying out research to determine the effects
of implementing AI in the long run, examine ways of dealing with job losses and evaluate the
efficacy of measures that have been put in place to ensure the use of AI is ethical. This way of
thinking is designed to tap into the maximum capacity of AI as a tool for improving the quality
of public services and supporting the development of China’s economy and society.
Keywords: Artificial Intelligence Adoption, Public service, Efficiency, Performance
Introduction
AI (artificial intelligence) has taken centre stage in the area of technology that is changing
multiple sectors and public services as well. In the case of China, AI implementation in the
public sector is expected to be beneficial in terms of increasing efficiency, improving service
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Published Date: 08 June 2024

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provision and eventually contributing to economic growth (Chen et al., 2021). However, all
the benefits of these emergent technologies including but not limited to technological, socio-
economic, and ethical realms cannot be fully realized. By presenting the current problem in
AI adoption of state services in China, the researcher will spot the main difficulties and
prospects this process presents.
China as one of the most developed countries in artificial intelligence has a lot to show while
the private and public sectors go in the race for innovation. Having the widest population in
the world, and owing to its dynamic technology domain, it presents a fertile region where AI
is being designed, developed, and applied. Similarly, the top tech giants of China like Alibaba,
Tencent and Baidu spearhead the development of the AI sector ranging from data analysis to
innovative AI applications (Keane et al., 2020). The impact on Public Services in China is vast.
AI plays the role of a game changer, from the field of healthcare and education to
transportation and urban management. It has promising potential to alter the way public
services are rendered and experienced. For instance, AI-driven medical diagnosis is very
possible and will be better in terms of patient care. On the other hand, smart transport
systems will lead to easy urban mobility and less congestion. But these advantages
nevertheless need to be achieved while the problems are being conquered.
It is one of the main issues that automating jobs in public services in China may pose to
millions of employees as tasks may be automated. Machines in the production of half of the
work activities, day-to-day jobs with predictable programming and routine tasks will be
threatened by automation by AI technologies. Thus, this automation might worsen the
problem of income differences and concern about the relevance and stability of these jobs
for people working in the affected sectors. Technological feasibility, likewise, stands out
among the key factors shaping the success of AI implementation. While China has made
significant strides in AI research and development, challenges remain in nurturing a
supportive ecosystem necessary for sustained innovation. The lack of a robust data-sharing
framework further hinders progress, as access to diverse datasets is essential for training AI
systems effectively (Gaonkar et al., 2020).
The shortage of workers with practical skills is a major problem in the Chinese AI engineer
and AI adopter development. In the USA, the substantial number of experienced data
scientists is more than those in China which is not well positioned to cover the AI talent need
(Lundvall & Rikap, 2022). Besides, the integration of AI technologies may further profit the
digital skills but the wages for low and medium-skilled labour will decrease. From ethical and
social standpoints, the AI acceptance is even more demanding. The AI technologies-driven
shift of workers' positions raises serious moral queries about employment security and the
well-being of society. Moreover, in addition to that the problems that may arise with data
privacy, algorithmic bias, and legal liability are the primary barriers to its adoption.
AI integration in the public services of China is a complex issue that has technical and socio-
economic dimensions and to successfully face racism requires a broad strategy. Policies of
governments have an extremely important function to fulfil by building up an AI environment
for development and adoption. For AI growth in China to be sustainable, initiatives that help
to close or bridge the AI talent gap and create sharing frameworks for data are essential
(Aljohani et al., 2022). For instance, the cooperation in AI development between government,
companies and academic institutions must be assured to deploy the technology responsibly
and ethically. Through the solution of those issues, AI technology will ensure that the public
administration works perfectly, boost GDP and improve the citizens' lives.

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AI, maintenance of the public services in China, brings the promise of a revolution in service
delivery that leads to economic growth. However, the main achievements can be reached
only through thorough consideration of numerous existing problems in the field such as
technical feasibility, talent deficit, ethical issues, and capital constraints. Through the
promotion of a creation-favorable environment for AI development and acceptance, China
can disclose the entire capacities of AI that would result in enhanced public services and a
more satisfied population.
Objectives
● To understand the recent trends of AI in China
● To identify the challenges in the adoption of AI in public services in China.
● To identify the impact of AI adoption challenges on efficiency and performance.
● To recommend certain ways for the successful adoption of AI in the public sector in
China.
Method
The researcher picked an interpretivism research philosophy for this research because it
recognizes the complicated social-economic and ethical aspects involved when introducing AI
in China's public services apparatus. On the contrary, instead of reducing humanity to positive
phenomena and measurable events, interpretivism distinguishes the subjective nature of
human experiences, taking into account the meanings that people give their actions and
interactions (Sanchez et al., 2023). AI-related absorption allows to look into the phenomenon
extensively from the perspective of the authorities, representatives of businesses and
workers who might be affected by the disruption. This kind of thinking calls for alertness to
AI implementation forcings and a sophisticated assessment of the kinds of effects that success
and public services ' provision would have afterwards. As a result, the study can provide the
most relevant information and advice on how to stylize the implementation of AI in the
Chinese civil service by the interpretive approach.
Furthermore, an inductive approach is critical in this undertaking because it helped close up
the observation and computation of data which, in turn, yielded research findings. On the
contrary, with deductive methods that rely on propositions as the guidelines for either
confirming or disproving them, the inductive approach involves data-gathering and analysis
to enable to identify underlying types, connections or trends (Siponen & Klaavuniemi, 2020).
Since AI adoption by the public sector in China has certain characteristics such as multi-
dimensionality and variation, the inductive method allows the researchers to discern the
reasons and the factors that cannot be assumed at first glance. Through process-oriented
analysis of various qualitative data, interviews, surveys and case studies, a comprehensive
study can produce in-depth and insights-rich findings. Under this approach, AI researchers
can uncover complex understandings about the challenges and opportunities for AI adoption
that will address the most viable recommendations for a successful implementation of AI in
the public sector.
The structure of the research with explanatory design is key to the study which will clarify the
core issues and the cause impact of the artificial intelligence (AI) application in public services
in China. Unlike descriptive research designs that simplistically describe phenomena or
predictive research designs that tell future outcomes, explanatory research is about
explaining the occurrence, and this relation (Haydam & Steenkamp, 2020). As AI is very
complex and multi-dimensional, an explanatory approach is the only method that will help

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the researchers dive into the fundamental components that cause these challenges. The
analysis of causal links and factors such as workforce displacement, ethical considerations,
and technical feasibility will aid in revealing the bottom-line problems that can be tackled.
The information acquired through these analyses helps public authorities, business leaders,
and other players design and carry out tailored approaches to AI adoption which leads to
higher implementation success in the AI-governance field.
The involvement of bringing people who gathered qualitative data for research is beneficial
for many reasons. Secondary data gives access to a very wide selection of already existing
information in many different places such as academic journals, government reports or
industry publications (Mazhar et al., 2021). Varied data sources enable encompassing
investigation of complex AI-related issues and prospects in China’s government sector.
Furthermore, secondary data collection is cost cost-saving and time-saving method for
primary data collection techniques like interviews and surveys as it eradicates the need to
start all processes afresh. Furthermore, usage of the secondary data gives researchers access
to extraordinary information and opinions from different directions which only increases the
information depth and richness of studies. Through a systematic review and an examination
of available literature and data, the analysis will deliver an inclusive insight into the factors in
play that may influence AI adoption, eventually serving as a basis for recommendations to
policy-makers, industry leaders, and other stakeholders.
Choosing a thematic data analysis method for this research allows to explore ideas/concepts
in the data and establish themes, patterns and trends in the data. Thematic analysis provides
researchers with the systematic process of organizing and interpreting qualitative data hence
aids in the meaning of information and findings (Peel, 2020). The application of thematic
analysis helps in discovering the hidden patterns and trends that exist in the complicated
issues facing AI implementation in the Public sector of China. Thematic analysis helps in
recognizing the reoccurring patterns and familiar themes across different types of
information sources, including interviews, reports and literature. This way the researcher will
be able to achieve a holistic appreciation of the elements shaping the AI uptake. Moreover,
mathematical analysis allows researchers to look for new themes that contribute to a better
understanding of the data. Thus, no relevant information is lost. Finally, using thematic
analysis, the study may evolve in tones of more advanced and scenario-based findings, which
will result in more appropriate recommendations to meet the challenges and benefits of
artificial intelligence adoption in the administration of China.
This study’s ethics in employing the secondary data would address maintaining originality and
crediting relevant sources. Researchers must appropriately credit the sources and original
authors of the data and the right to intellectual property because among others uphold
honesty and intellectual property. In addition, it should be considered to give a critical
assessment of the second source’s reliability and consistency to avoid an immoral
propagation of inaccurate or biased meanings. Thus, the researcher needs to also ensure the
privacy and confidentiality of the data presented in the report, paying so much attention to
it, is highly essential (Far & Rad, 2022). In addition, scholars must be careful to ensure that
they do not unintentionally misreport or mistranslate the data findings from the secondary
data. The upfront disclosure of the shortcomings and the built-in biases in secondary data
sources is necessary so that the trustworthy and credible findings of the survey can exist. To
sum up, the following ethical principles serve as a guardrail for the ethical and responsible
use of secondary data for research activities.

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Findings
Recent Trends of AI in China
Current AI development in China shows China’s aim to acquire higher-level technology and to
be innovative. China has occupied itself with the AI leadership project, with the support of
major state and non-state investments. There is clear evidence of the growing presence of AI
in the different sectors of society like medicine, education, transport, and urban
management. AI-powered medical diagnostic systems have gradually become widespread in
Chinese hospitals, and as a result, more patients are treated effectively, while healthcare
delivery is rapidly enhanced (Thangam et al., 2022). On the other hand, Artificial Intelligence
in China has seen an unprecedented expansion of research and developer activities, fuelled
by the likes of Alibaba, Baidu and Tencent who are the leading companies in the space. AI
companies, with the aid of massive data, develop intelligent AI applications that can go from
recognizing voice, and natural language processing, to facial recognition and autonomous
vehicles. The flourishing of China's technology-focused business environment alongside a
large population and governmental backing for the development of AI has created a very
suitable environment for AI innovation and business start-ups.
Figure 1: Recent trends of AI in China
(Source: Thangam et al., 2022)
The other significant trend is the more than increased focus on AI persons training and
studying. Understanding human capital as an instrument for AI innovation, China has spent
huge money to develop its skilled workforce in AI-related fields. The country runs many
universities, labs, and training programs that are artificial intelligence-smart and that train
young people. Besides, talent recruitment programs and international collaboration activities
effectively retain AI superstars on a global scale and also boost the development of AI in China
(Mukherjee, 2022). China, moreover, is seeing AI being used mainly to stimulate economic

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growth and national development. The Chinese government has made very clear its
intentions of becoming the world leader in AI not later than the year 2030, through several
initiatives designed to engender innovative ideas, heighten investment, and expand the
application of AI technologies.
On the one hand, this can lead to various opportunities, while on the contrary, it creates some
hindrance and reservation in China's AI outreach. These are the societal and ethical issues
relating to data privacy, algorithmic bias, ethical consideration and geopolitical tensions. The
other aspect in this regard is that the impending use of AI technologies leads to uncertainty
regarding society’s effects with some of their consequences, like job displacement, inequality,
and social disruption (Khogali & Mekid, 2023). Therefore, the recent tendencies in AI in China
confirm this country’s readiness to usher in the age of AI for economic growth and social
development. As China makes impressive progress on the front of AI research, development
and application, responding to the related challenges and ethical dilemmas will be pivotal for
the positive societal impact of this technology.
Challenges in the Adoption of AI in Public Services in China
With the Chinese public administration facing some major obstacles related to the
introduction of AI technology, the latter remains unable to fully realize the desired effect. The
primary issue is that advanced robots introduce the dilemma of job displacement. AI keeps
developing to the point that it can take over and automate even a large amount of regular
work tasks for example some categories of jobs that are situated in manufacturing, transport,
and customer service (Benbya et al., 2020). The employment situation after the automation
of some human activities may worsen and irrevocably lower living standards for people who
have been affected. The question concerning which professions are amenable to automation
will be important. As another important impediment to the integration of AI, technical
feasibility is mentioned. China has shown determination to capitalize on AI research and
development, but obstacles have surfaced in the context of creating a climate that is
conducive to the continuity of innovation. Moreover, the absence of a strong data-sharing
structure impedes in terms of progress in the development and teaching of AI, because access
to diverse data sources is extremely important to effectively train such systems.

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Figure 2: Challenges in successful AI adoption
(Source: Benbya et al., 2020)
On the other hand, the lack of relevant human manpower is a great impediment to the use
of AI not only in China but also around the globe. While in the USA, due to the relative
shortage of data scientists with over a decade of experience, companies face a problem of
finding a sufficient number of talent, China has severe difficulties meeting its requirements
for AI experts (Li et al., 2021). Adoption of AI technologies may also be a source for deeper
income inequality, by creating a premium for digital skills but leaving the scope for the
reduction of demands for low-skilled and medium-skilled workers. AI’s ethical and social
worries only help build more challenges around it. The dislocation of workers by AI
technologies gives rise to moral issues regarding work security and the betterment of social
ties. Likewise, other matters about data privacy, algorithmic bias, and legal liability are
imposed by adopting AI.
The solution to these obstacles lies in a holistic policy that is integrated and takes into account
the technological and economic aspects of this problem. Government policies are
fundamental to building up an environment that favours AI into being broadly and extensively
used and initiatives like bridging the AI talent gap and promoting the data-sharing mechanism
are vital for AI growth in China (Dwivedi et al., 2021). Collaboration between government,
business, and academia is the necessary precondition for sending AI technologies into public
services on an ethical and fair basis.
Impact of AI Adoption Challenges on Efficiency and Performance
A major problem related to introducing AI to the process of delivering public services in China
is a drop in efficiency and performance among the sectors. There could be a displacement of
some jobs which as a result dents workforce dynamics. AI advances will start to substitute
routine and automated tasks, that may threaten the employment of low-skilled workers
(Nissim & Simon, 2021). Consequently, leaders of organizations will encounter a reduction in

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overall productivity and efficiency levels, since the nature of the workforce will involve a
frequent need for adjustment. To worsen the matter, the lack of skilled AI talents in the
workforce adds to these efficiency problems. Without a relevant workforce with a bearing on
AI technologies, companies might not succeed in putting into place and optimising AI systems
to the best of their ability. This can result in inefficiencies in AI deployment, hindering the
potential benefits of automation and data-driven decision-making.
Additionally, technical feasibility problems that arise from the data availability and quality
may deteriorate the performance of the AI system. Lack of good quality data may badly hinder
the ability of AI algorithms to deliver the best results that are less biased (Cheng et al., 2021).
In this case, the lower quality of the product may become a result of it. Such requirements
come from the standpoint of personal data as well as data protection, which might result in
uncertainty of making data available for training, and consequently decrease the system
performance. Along with that, various ethical aspects related to emergent AI use often centre
around productivity and work efficiency. The example of AI technology footprint being
embedded with human factors implies that the aspect of bias and fairness is being
questioned, thus all new systems of AI will no longer be used to a smaller extent. By extension,
these regulatory matters and legal liabilities might prove to be the lawful restraint that can
limit a company's use of AI technology in its quest to be efficient and effective.
Further, AI's deployment in China's public service sector does not only display the efficacy
side but also other fields concerning the performance of AI. Overcoming these issues requires
collective efforts involving governments and scholars to come up with good policies, train
workers who will use AI, prepare good data and to consider ethical and social issues (Dwivedi
et al., 2021). In this way, the Institutions will navigate these obstacles and then climb down
AI for the great purpose of bettering service delivery and innovation.
Certain Ways for the Successful Adoption of AI in the Public Sector in China
Successfully incorporating AI into the public sector in China calls for a systemic plan that
identifies the challenges as well as takes advantage of available opportunities to implement
AI successfully. The foremost strategy is to target the development of AI in terms of skills and
education. AI systems that are effectively integrated into organizations require skilled
workers with technological competencies to get over the deficiency of AI talents and the
delivery of the processes (Mukherjee, 2022). However, formalizing supportive mechanisms,
such as collaboration and partnerships between governments, organizations and academia,
is also a crucial point for the adoption of AI in the public sector. Unlike opting for individual
approaches, stakeholders can collaborate in working together to share resources, which
include expertise and best practices of the trade, as a result of the transfer of knowledge.
Besides, writing detailed regulations and rules for AI use is also important in the context of
the rightful and reasonable use of AI. Strict regulations are significant in addressing data
privacy issues, algorithmic discrimination along with legal liability, thus providing an ideal
situation for AI development and implementation (Rodrigues, 2020). In addition, the act of
advancing data sharing and interoperability among the different levels of government and
departments can facilitate the transmission of data and better its quality for AI projects. By
eliminating data silos and enabling data exchange, enterprises become fully oriented towards
using AI for intelligence insights and making more information-driven decisions.
Overall, together with infrastructural and technological investment, these are key supports
to enable AI adoption in the public sector. The infrastructure of the IT system can be enhanced
by procuring the cloud computing infrastructure and using AI-ready hardware and software

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solutions that are compatible with each other and also scalable (Seidelson, 2021). Generating
an innovative and experimental environment can help the public sector achieve AI
development. Promoting, accepting, and compensating for risks, and errors as learning
opportunities and innovation are tools that can be used to overcome the resilience to change
and to accelerate the implementation of AI solutions. In general, through allocating resources
towards talent development, forging together, implementing suitable regulations, advocating
for the use of data, investing in infrastructure, and creating an innovative climate, China could
effectively adopt AI in the public administration and be of service to implementing innovation,
simplification, and delivery efficiency.
Discussion
In the discussion section, the researcher brought up the latest developments, difficulties,
burdens brought about, and a few measures of the implementation of AI in public
organizations in China. It finally turns its critical eye to the findings that have been exposed in
the previous sections and picks out the most important insights and resulting policy matters
for policymakers, industry leaders, and other stakeholders. While addressing recent
tendencies, the strategic plan of China to grow AI by way of high investments in the area and
crossing sectors is demonstrated. The fact that AI tools are created to improve the healthcare,
education, transportation, and urban systems doesn't only mean an increase in the quality of
service, but also it is a great opportunity for development on all fronts. Major tech companies
from Alibaba and Tencent to Baidu are leading this innovative wave of technology, tapping
into a vast data resource together with intense government support to nurture AI
development. The AI strategy is designed not only to create a talent base but also to educate
the population to generate a workforce that is capable of sustaining AI development and
innovation.
However, even though these chances are obvious challenges can be still found in artificial
intelligence in public services. The growing automation of workplaces overshadows a whole
category of jobs, which in turn leads to income distribution disparities and a lack of job
security. Technological issues related to data access and quality, together with labour
shortage, as two major obstacles to the rapid pace of AI adoption, impede the industry
development. Ethical and social dimensions in AI integration, for instance, data protection
and bias in algorithms, entail extra complexity for adoption. The effect of those problems on
the missing functions and efficiency is diversified. Workforce disruptions; as well as talent
shortages impede the effectiveness of organizations and their productivity. The performance
of AI systems is stilted by technical feasibility problems resulting in fewer satisfactory
outcomes and the long-run loss of public confidence. Furthermore, ethical and social
concerns place barriers by setting regulatory restrictions and giving legal liabilities that in the
end do not let AI fully reach its potential to promote efficiency and innovation in public
services.
To tackle this issue, accordingly, some specific approaches are presented for the smooth
disclosure of AI in the public sector of China. A significant amount of resources (investment)
should be allocated for the development of talents and education to reduce the AI skill gap
and facilitate the utilization of AI systems skillfully. Collaboration between government
bodies; the industrial sector; and the research sector is vital for the betterment of knowledge
dissemination and AI deployments. A solid regulatory mechanism that provides direction on
ethical and legal issues is needed for AI innovation to be sustained and the environment to
be favourable. Besides, the integration and the exchange of data could enhance the access to

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information of AI applications and the enrichment of their findings and the quality of the
decisions. Along with investment in infrastructure and technological capacities, more AI
adoption is possible because it grants smooth integration of AI solutions that are scalable.
Regarding this, embracing the culture of innovation and experimentation implies risk-taking
and incites innovation, which is a process to resist change and supports the adoption of AI-
based solutions.
Thus, the discussion critically judges the recent tendencies, problems, influence, and certain
ways of the successful introduction of AI in the public sector in Chinese through the prism of
the given items. It emphasizes the possibility of AI being a revolutionary force that can
modernize public service delivery, engender economic growth, and enhance social welfare.
Alongside these benefits, the path to achievement is riddled with challenges, thereby calling
for calculated action to tackle them and seize opportunities. By putting talent first,
encouraging teamwork, clarifying regulation, leading data sharing, investing in infrastructure
and creating an innovative culture, there is a way for China to implement AI in the public
sector to its maximum capacity.

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