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Journal of Management and Informatics (JMI)
Vol. 3 No. 2 August 2024
E-ISSN: 2961-7731; P-ISSN: 2961-7472, Pages 267-281
Received on May 24, 2024; Revised on June 16, 2024; Accepted on July 19, 2024; Published on August 23, 2024.
DOI: https://doi.org/10.27824/jmi.v3i2.34
Enhancing Customer Service Efficiency in Start-Ups with AI:
A Focus on Personalization and Cost Reduction
Edy Susanto*1, Zahra Dinul Khaq1
Email: edy224324@gmail.com (E. S.), zahradinul@stekom.ac.id (Z. D. K.)
Orcid: https://orcid.org/0009-0004-7864-2772 (E. S), https://orcid.org/0009-0001-3072-5825 (Z. D. Q)
1Dept. Management, Universitas Sains dan Teknologi Komputer, Semarang, Indonesia, 50192
*Corresponding Author
Abstract
This study investigates the impact of Artificial Intelligence (AI) implementation in customer
service within start-up companies, focusing on its effects on operational efficiency and customer
satisfaction. Through a mixed-method approach that combines case studies and surveys, data was
collected from customer service managers and customers of various start-ups utilizing AI
technologies. The findings reveal that the adoption of AI leads to a 20% reduction in operational
costs and significantly enhances customer service productivity by reducing response times and
improving information accuracy. Survey results indicate that customers are generally satisfied
with AI-driven services, particularly regarding the speed and relevance of recommendations.
Furthermore, the study highlights the importance of integrating AI with human interactions to
provide a holistic customer experience. This research contributes to the understanding of AI's
potential in optimizing customer service processes in resource-constrained environments,
offering valuable insights for start-ups looking to leverage technology for competitive advantage.
Keywords: Artificial Intelligence, Start-up Companies, Operational Efficiency, Customer
Satisfaction, Technology Integration.
I. INTRODUCTION
In the rapidly advancing digital era, start-up companies face significant challenges in their
efforts to meet customer needs. As new business entities that are often still in the early stages of
development, start-ups typically encounter limitations in terms of human resources, technology,
and finances (Ramesh et al., 2023). One of the primary challenges they face is delivering effective
and adequate customer service, which not only resolves customer issues but also helps retain their
loyalty. In this context, AI is increasingly seen as a potential solution to address these limitations,
particularly in automating customer service. The use of AI enables companies to not only improve
operational efficiency but also reduce the costs associated with daily customer interactions
(Enholm et al., 2022).
AI offers several capabilities that are highly relevant to the needs of start-up companies.
For example, AI technology can automate various routine tasks that previously required human
interaction, such as answering common questions, resolving customer issues, and providing
product information. Moreover, this technology enables companies to reach a larger number of
customers simultaneously without needing to increase their customer service staff (Wamba-
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Taguimdje et al., 2020). This capability is particularly beneficial for start-ups, which often operate
with small teams but are expected to serve customers quickly and efficiently.
According to a study conducted by Filieri et al (2021), the implementation of AI-based
chatbots in start-up companies has been shown to reduce customer service operational costs by
up to 25%. This cost reduction is achieved through the efficiency gained by using chatbots that
can operate 24/7 without the need for breaks. These chatbots can respond to customer inquiries
within seconds, allowing companies to provide timely and accurate responses. In situations where
human resources are limited, AI enables companies to maintain the quality of customer service at
a lower cost (Filieri et al., 2021).
Additionally, research by Nicolescu and Tudorache (2022) shows that companies using AI
in customer service have also experienced increased customer satisfaction. The study found that
AI can provide more responsive and personalized service, ultimately contributing to customer
loyalty (Nicolescu & Tudorache, 2022). AI not only delivers quick responses but also has the
ability to understand and adapt to the individual needs of each customer. For instance, some
companies have implemented AI to personalize promotional messages or product offers based on
customer preferences. This approach not only increases conversion rates but also strengthens the
relationship between the company and its customers (Bahoo et al., 2023).
The presence of AI in the customer service sector also allows companies to offer more
personalized services. By analyzing customer data, AI can understand their preferences and
behavioral patterns, making interactions more relevant and tailored to individual customer needs
(Xu et al., 2020). Technologies such as machine learning and big data enable AI to learn from
previous interaction patterns and apply them in new contexts. For example, if a customer has
shown interest in a particular product in the past, AI can recommend similar products in the future.
This approach allows companies to maximize the use of data, resulting in more proactive and
customer-preference-driven interactions (Li et al., 2021).
However, despite its numerous advantages, the implementation of AI in customer service
is not without challenges. One of the main obstacles is that AI still struggles to handle complex
problems that require a human touch to add value to interactions (Xu et al., 2020). While AI can
answer simple questions or provide basic information, more complicated issues or those requiring
empathy still require human interaction. For example, Sheehan et al. (2020) noted that some
customers feel that automation reduces the personal aspect of the service they receive, hindering
an ideal customer experience. There are concerns that an overreliance on AI could remove the
human touch that is often considered important in customer service (Sheehan et al., 2020).
Furthermore, data security and privacy concerns are critical in the implementation of AI,
particularly in the collection and analysis of customer data. Customer data is a valuable asset, and
the improper use of AI could pose privacy risks (Tawalbeh & Saldamli, 2021). In this context,
Journal of Management and Informatics (JMI)
Vol. 3 No. 2 August 2024
E-ISSN: 2961-7731; P-ISSN: 2961-7472, Pages 267-281
companies must ensure that customer data is well-protected and that AI usage complies with
applicable regulations. Moreover, efficient customer service plays a crucial role in reducing
operational costs, especially in start-up companies where resources are often limited. Research
has shown that automating customer service through AI technologies like chatbots and virtual
assistants can significantly reduce labor costs by up to 30% (Filieri et al., 2021). By handling
routine inquiries and simple customer interactions, AI allows companies to lower their
dependency on human agents, thereby reducing salary, training, and operational expenses (Javaid
et al., 2022). This is particularly beneficial for start-up companies, which often face financial
constraints in their early stages.
In addition to cost reduction, customer service in start-up companies plays a vital role in
building customer loyalty and satisfaction, which is essential for business growth. Start-ups often
rely on customer service to create a personalized and responsive experience, which can
differentiate them in competitive markets (Nicolescu & Tudorache, 2022). AI can help start-ups
offer faster and more accurate responses to customer inquiries, improving the overall customer
experience and contributing to long-term customer retention (Wamba-Taguimdje et al., 2020).
For instance, many start-ups use AI to personalize their customer interactions, which enhances
service quality and increases the likelihood of customer loyalty. These challenges require careful
approaches and the responsible application of technology, particularly when it comes to ensuring
that AI systems not only reduce operational costs but also maintain high standards of customer
service in start-up companies.
This research aims to explore the extent to which the use of AI in automating customer
service can contribute to reducing operational costs in start-up companies, as well as examine its
impact on efficiency and customer satisfaction. Based on case studies from several start-ups that
have implemented AI in customer service, this research will provide practical insights into the
benefits and challenges that companies may face when adopting AI. This analysis is expected to
fill a gap in the literature on the effectiveness and efficiency of AI in customer service within the
start-up sector, while also highlighting AI's potential as an innovative solution for overcoming
resource limitations.
II. LITERATURE REVIEW
Start-Up Companies
A start-up is a type of new company that focuses on developing a novel product or service.
These companies are often founded by a small group of individuals or teams with the aim of
penetrating the market with an innovative idea or product that can bring about significant changes
in the world. Start-ups are known for their adaptability, flexibility, and rapid growth
(Danarahmanto et al., 2020). One of the biggest challenges faced by start-ups is the limitation of
resources, ranging from financial capital to human labor. Most start-ups need to seek external
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270 Journal of Management and Informatics (JMI), Vol. 3 No. 2, August 2024
funding to finance their operations, often through venture capital investment (Hegeman &
Sørheim, 2021). Securing such an investment is risky and highly competitive. Additionally, start-
ups operate in environments characterized by high market uncertainty and the risk of failure.
These uncertain business conditions require companies to continuously innovate and adapt
(Montani et al., 2020). However, despite these challenges, start-ups also offer significant
opportunities. First, they have the potential to create revolutionary products or services that can
transform the way people work and live. Because start-ups often exist at the cutting edge of
technology, they are capable of introducing solutions that disrupt existing markets (Bae & Choi,
2021).
Customer Service Automation
Customer service automation refers to the use of technology, such as AI and chatbots, to
handle interactions with customers without direct human intervention. This technology can
respond to inquiries, provide information, and resolve customer issues efficiently and effectively
(Filieri et al., 2021). The primary advantage of customer service automation is the reduction of
operational costs. Since fewer human resources are needed to handle routine queries, companies
can allocate their resources to areas that require more direct attention. Moreover, companies can
serve a larger number of customers within the same timeframe, increasing potential revenue
(Nicolescu & Tudorache, 2022).
Customer service automation also plays a crucial role in improving customer satisfaction
(Huang et al., 2021). With fast and accurate responses, customers feel more valued and
appreciated, which can increase customer loyalty and enhance the company's brand image. A
well-designed automated system can also provide more accurate and relevant solutions for
customers (Huang et al., 2021). Despite its many advantages, the implementation of customer
service automation is not without challenges. One major challenge is ensuring that the technology
can properly understand and respond to a wide range of customer inquiries and complaints. There
is also concern that automation may reduce the human touch, which is considered important in
customer service interactions (Sheehan et al., 2020).
To address these issues, companies are encouraged to equip their automated systems with
advanced AI capabilities. This will assist in cases where the automated knowledge base is
insufficient to understand complex issues or where no relevant solutions are available in the
database. This approach requires continuous training and monitoring to ensure the system's
effectiveness. Additionally, merging automated systems with human agents in a hybrid model has
proven to be a rational solution, allowing both to work together in handling truly complex cases.
In the long term, customer service automation could lead to significant changes in how companies
interact with their customers. As technology adoption continues to grow, customers will become
increasingly accustomed to fast and efficient service. This not only shifts customer expectations
Journal of Management and Informatics (JMI)
Vol. 3 No. 2 August 2024
E-ISSN: 2961-7731; P-ISSN: 2961-7472, Pages 267-281
but also forces companies to continually innovate in their service offerings (Fernandes & Oliveira,
2021). Customer service automation offers numerous benefits, from reducing operational costs to
enhancing customer satisfaction. However, the challenges in implementation must be addressed
with appropriate technology and ongoing monitoring. By doing so, companies can maximize the
potential of automation to provide better and more efficient services.
Operational Costs
Operational costs refer to the expenses incurred by a company in conducting its day-to-
day activities. These costs include employee salaries, building rentals, utilities, and office
supplies. Managing operational costs effectively is essential to maintaining the financial health of
the company and ensuring that the business can function smoothly without financial constraints
(Anupriya et al., 2020). Good operational cost management helps companies identify areas
where expenses can be reduced without compromising the quality of products or services. This
enables businesses to increase profit margins and reinvest in business growth. Moreover, efficient
cost management enhances a company’s competitiveness in the market (Kostrzewski et al., 2022).
Several strategies can be employed to reduce operational costs. First, companies should
conduct direct reviews of their expenditures to identify unnecessary costs. Second, by utilizing
technology to automate business processes, labor costs can be reduced, and overall efficiency can
improve. Third, companies should consider outsourcing non-core business functions. One of the
major advantages of outsourcing is that it allows business units to focus on core activities,
enabling them to utilize resources more effectively (Kulembayeva et al., 2022). However, there
are several challenges associated with these strategies. The first challenge is reducing costs while
maintaining the quality of products or services, which is not always easy. Second, costs may
fluctuate due to broader economic or market conditions, making it crucial for companies to adapt
quickly. Managing operational costs is key to ensuring business sustainability and growth. With
the right strategies, companies can reduce unnecessary expenses, improve efficiency, and remain
competitive in the market. It is important for companies to continuously monitor and adjust
operational costs in response to changes in the business environment to achieve long-term success
(Ernayani et al., 2022).
AI Use in Customer Service Automation
The use of AI in customer service automation has led to significant improvements in
operational efficiency. Through the adoption of chatbots and virtual assistants, companies can
handle customer inquiries in real time without the need for human intervention. This allows
businesses to reduce response times, enhance customer satisfaction, and lower operational costs
(Wagobera Edgar Kedi et al., 2024). AI also offers the ability to personalize customer interactions.
With in-depth data analysis, AI systems can understand customer preferences and behaviors,
allowing for more relevant and timely recommendations. This personalization not only helps
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improve the customer experience but also increases customer loyalty and retention (Xu et al.,
2020).
Additionally, AI simplifies the automatic collection and analysis of data. AI systems can
gather data from various sources, analyze it, and provide valuable insights that help companies
optimize their customer service strategies. The use of predictive analytics enables businesses to
anticipate customer needs and respond more proactively (Enholm et al., 2022). As AI takes over
routine tasks without requiring human intervention, employees can invest more time in their core
responsibilities. Indirectly, the use of AI in this context enhances efficiency by allowing
employees to focus more on meeting customer needs. Furthermore, monotonous tasks are not
ideal for employee engagement and productivity (Sadhu et al., 2024).
Although the use of AI in customer service offers many benefits, it is crucial for
companies adopting AI to address challenges such as data security and system reliability. To
overcome these challenges, companies must implement stringent security protocols and
continually update their systems. Employee training is also important to ensure that customer
service remains prompt and effective. The use of AI in customer service automation has
transformed how companies interact with their customers, bringing greater efficiency,
personalization, and deeper insights. However, challenges remain, and companies must address
these to fully optimize the potential of this technology.
The Impact of AI on Reducing Operational Costs
One of the most significant impacts of AI implementation is the reduction in labor costs.
AI enables companies to decrease the number of employees required to manage daily operations.
For example, in the customer service sector, AI-based chatbots can replace human customer
service agents in answering common queries and resolving minor issues. This allows companies
to redirect human resources to more complex and strategic tasks, thereby reducing salary and
training expenses (Javaid et al., 2022).
Moreover, AI enhances operational efficiency through increased automation. Tasks that
are time-consuming and require human capabilities can be performed instantaneously with AI.
Automated processes include repetitive production activities where robots can replace human
workers. This accelerates production and reduces natural resource costs, thereby lowering overall
operational expenses (Helo & Hao, 2022), AI also facilitates the optimization of various
resources, including materials, energy, and time. AI algorithms can monitor and analyze real-time
data, identifying specific patterns and trends that lead to optimal resource usage. For instance, in
the logistics industry, AI enables the optimization of delivery route planning. This helps save fuel,
time, and long-term costs (Wamba-Taguimdje et al., 2020).
Another benefit of AI's ability to analyze big data is that companies can make faster and
better-informed decisions. As previously mentioned, AI provides deep insights into market trends,
Journal of Management and Informatics (JMI)
Vol. 3 No. 2 August 2024
E-ISSN: 2961-7731; P-ISSN: 2961-7472, Pages 267-281
consumer behavior, and operational performance. With this information, companies can identify
areas that require improvement and take steps to reduce costs. For example, AI-powered
predictive analytics helps companies manage inventory more efficiently, reducing storage and
product waste costs. AI also drives overall productivity improvements. By handling repetitive
tasks and minimizing errors, employees can focus on more value-added tasks. This increases
output while simultaneously reducing losses associated with repairs and maintenance. In turn,
companies can operate more economically, achieving high efficiency at lower costs, which
provides sustainable benefits to customers (Purva Grove et al., 2022). The use of AI has a wide-
ranging and profound impact on reducing operational costs. Through enhanced efficiency, labor
cost reductions, resource optimization, improved decision-making, and increased productivity,
AI offers significant opportunities for companies to enhance operational performance at lower
costs.
The Use of AI in Start-Up Companies
AI has become an increasingly important technological component in businesses across
various industries, including start-ups. AI aids start-up companies in optimizing operations,
reducing costs, and enhancing efficiency. By leveraging big data and valuable insights, AI enables
start-ups to make better and faster decisions (Weber et al., 2022).
Marketing and sales are among the areas where AI is particularly effective. AI allows
companies to analyze customer data to identify behavioral patterns that can be utilized to develop
more effective marketing strategies. For instance, AI algorithms can determine which products or
services are most likely to be purchased by certain customers, allowing companies to target their
advertising more efficiently. AI also supports the creation of chatbots, which provide post-sale
customer support that is quick and efficient. This can help improve sales mobility and customer
satisfaction (Wamba-Taguimdje et al., 2020).
A study on Fintech start-ups shows that AI can also be used to optimize internal
operations. Machine learning algorithms can automate routine tasks such as inventory
management, data processing, and financial analysis. This not only saves time and resources but
also reduces the risk of human error. For instance, AI systems can detect anomalies in financial
data that might indicate potential problems or opportunities (Almansour, 2023).
AI can also expedite product development for start-ups. It allows product development
teams to better understand their customers by analyzing data from external sources, thereby
increasing the likelihood of creating market-fit products. Specifically, AI helps start-ups save time
in testing product prototypes by reducing the need for multiple iterations.
However, before companies implement AI technologies, they must be aware of the
associated challenges and ethical considerations. The most apparent challenge is the cost of AI
technology, which can be prohibitive for companies with limited resources. Moreover, there are
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concerns about data privacy and the potential for bias in AI systems. Therefore, it is essential for
companies to understand that the benefits of AI can only be fully realized by adhering to best
practices and ensuring ethical use of the technology (Riya Widayanti & Lista Meria, 2023).
The use of AI offers numerous advantages to start-up companies, from marketing to
product development. However, it is crucial to address the challenges and ethical issues involved
to ensure that the technology is applied responsibly.
III. RESEARCH METHODS
This study employs a mixed-method approach to provide a comprehensive understanding
of AI usage in automating customer service in start-up companies. This approach combines both
qualitative and quantitative methods, namely case studies and surveys. The case study method
was chosen to explore in depth the implementation of AI in five start-up companies, particularly
in the context of customer service. These companies were selected through purposive sampling,
based on their extensive use of AI in customer interactions and their willingness to participate in
the study (Montani et al., 2020). Additionally, the survey method involved 150 customers from
these start-ups to measure their satisfaction with AI-based services, focusing on service
effectiveness, speed, and relevance (Huang et al., 2021). The customers were selected using
simple random sampling to ensure a broad and representative view of user experiences with AI-
driven customer service.
Data collection in this study involved several key steps to ensure the validity and reliability
of the findings. Primary data were collected through in-depth interviews with customer service
managers at start-ups utilizing AI. These semi-structured interviews allowed flexibility in
exploring the companies' experiences in using AI to enhance operational efficiency and customer
satisfaction (Sadhu et al., 2024). To complement the primary data, an online survey was
conducted with customers of the participating companies, using a 5-point Likert scale to assess
customer satisfaction. The survey aimed to capture customers' direct perspectives regarding their
experience with AI-based services (Montanaro et al., 2024).
In addition to primary data, secondary data were collected from financial reports and
internal company documents related to customer service operational costs. This secondary data
was used to assess the impact of AI on reducing operational costs over a specified period (Javaid
et al., 2022). This information allows researchers to objectively analyze significant changes in
operational costs before and after AI implementation, thus evaluating the financial impact of
automating customer service.
Journal of Management and Informatics (JMI)
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Figure 1. Research Framework
The collected data were then analyzed using two main approaches: thematic analysis for
qualitative data and descriptive statistical analysis for quantitative data. Interview data were
analyzed using thematic analysis, enabling researchers to identify key themes related to the
benefits, challenges, and experiences of companies using AI for customer service (Wamba-
Taguimdje et al., 2020). Survey data were analyzed using descriptive statistics to provide an
overview of customer perceptions, and simple regression was employed to evaluate the
relationship between AI usage and customer satisfaction levels. The analysis was conducted using
statistical software to ensure the accuracy of the results.
The framework of this study is outlined as follows figure 1.
IV. RESULT AND DISCUSSION
Result
Table 1 presents the reduction in labor costs following AI implementation, based on data
collected from in-depth interviews with 5 customer service managers from start-up companies
Research Design
(Mixed Methods)
Qualitative Data Collection
(In-Depth Interviews)
Quantitative Data Collection
(Online Survey)
Thematic Analysis
Integration of Qualitative and
Quantitative Results
Interpretation and Discussion of
Findings
Challenges in AI Adoption and
Recommended Solutions
Descriptive Statistical Analysis
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that have adopted AI technology. These managers provided detailed information on the changes
in labor costs before and after the introduction of AI in their customer service operations. This
study found that the implementation of AI in customer service at start-up companies had a
significant impact on operational efficiency and customer satisfaction. Based on data collected
through interviews with customer service managers, it was revealed that after the adoption of AI,
operational costs in customer service were reduced by up to 20%. This reduction was primarily
due to decreased labor costs, as AI took over routine tasks such as answering simple queries and
handling repetitive complaints (Javaid et al., 2022).
Table 1: Reduction in Labor Costs Following AI Implementation
Operational Costs (USD)
Before AI
After AI
Percentage Reduction
Labor Costs
50,00
40,00
20%
Figure 2 illustrates the comparison of average response times before and after AI implementation.
In addition to cost reduction, data analysis from the survey indicated that AI also had a positive
impact on customer service productivity. Based on responses from a survey of 150 customers, AI
was able to improve response times in customer service, reducing the average response time from
15 minutes to less than 1 minute.
Figure 2. Comparison of Average Response Times Before and After AI Implementation
The percentage of respondents who were satisfied with various aspects of AI services is
shown in Table 2. Regarding customer satisfaction, the majority of respondents expressed
satisfaction with AI-driven services. In a survey using a 5-point Likert scale, respondents gave
high ratings to aspects such as response speed, accuracy of information, ease of interaction, and
relevance of AI-generated recommendations.
Table 2: Customer Satisfaction with Various Aspects of AI Services
Journal of Management and Informatics (JMI)
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AI Service Aspect
Percentage of Satisfied Respondents
Response Speed
85%
Information Accuracy
78%
Ease of Interaction
82%
Relevance of Recommendations
75%
From this data, it is evident that AI received a positive reception from customers,
particularly in terms of speed and ease of use. This aligns with previous research findings, which
demonstrated that AI can provide faster and more accurate services (Huang et al., 2021).
Customer Data Security Concerns
During the qualitative interviews, 3 out of the 5 companies reported experiencing
customer concerns regarding data security, particularly in the context of service personalization.
These concerns primarily revolved around the potential misuse of personal data, with 60% of
customers expressing unease over how their data was being utilized by AI systems. Companies
mentioned that despite implementing data protection measures, customer trust was still a
challenge due to the perceived lack of transparency in AI-driven processes (Fernandes & Oliveira,
2021).
Discussion
The results of this study indicate that the implementation of AI in customer service within
start-up companies has a positive impact on operational efficiency and customer satisfaction,
supporting the findings of (Wagobera Edgar Kedi et al., 2024) that AI enables companies to
enhance service capacity without expanding staff numbers. Additionally, the 20% cost reduction
presented in Table 1 aligns with the findings of Javaid et al. (2022), which demonstrate that AI-
based automation can reduce labor costs (Javaid et al., 2022). In terms of customer satisfaction,
survey results indicate that response speed is the most appreciated aspect, with 85% of
respondents giving a positive assessment (see Table 2). AI provides uninterrupted service,
offering instant responses that directly impact the customer experience. This reinforces a previous
study by Nicolescu and Tudorache (2022), which stated that AI can enhance the speed and
efficiency of handling customer complaints (Nicolescu & Tudorache, 2022).
However, limitations exist in handling more complex issues. Interviews with customer
service managers revealed that AI sometimes struggles with inquiries requiring human judgment
or decision-making. As noted by Sheehan et al. (2020), AI-driven interactions still lack emotional
personalization and empathy, which are often needed to resolve complex complaints (Sheehan et
al., 2020). Furthermore, the study's findings show that AI’s ability to personalize customer
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interactions through data analysis has been proven to increase customer satisfaction. These
findings support a study by Xu et al. (2020), which asserts that AI can provide product
recommendations that align with customer preferences, thereby enhancing loyalty.
Recommendations based on customer data analysis can increase conversion opportunities, as
indicated by survey respondents who felt that AI provided recommendations tailored to their
needs (Xu et al., 2020).
Nevertheless, data privacy challenges remain an issue requiring attention. As reported in
the results section, several companies noted that they faced customer concerns regarding the
security of their data, particularly in relation to service personalization. These concerns were
highlighted by 60% of customers, who expressed unease about the potential misuse of their
personal data (Fernandes & Oliveira, 2021). In the future, start-up companies must ensure
compliance with data privacy regulations to build customer trust.
This research contributes new insights by exploring how AI can support relevant service
personalization on a small and limited scale without compromising the quality of customer
interactions. It emphasizes that AI implementation is not only effective on a large scale but also
relevant and beneficial for start-ups. In this context, this study provides insights into how small
companies can leverage AI technology to deliver competitive and efficient customer service. The
synergy between AI and human interaction can be an optimal strategy for start-ups in addressing
the challenges related to the complexity of customer service. By integrating AI to handle routine
tasks, human staff can focus on resolving more complex issues that require empathy, offering a
more comprehensive customer experience. This contribution offers a new perspective on how
technology and human services can complement each other to achieve more holistic and efficient
customer service, especially in the dynamic environment of start-up companies.
V. CONCLUSION AND RECOMMENDATION
Conclusion
This study demonstrates that the application of AI in customer service within start-up
companies has a significantly positive impact on operational efficiency and customer satisfaction.
The implementation of AI has successfully reduced operational costs by up to 20%, while also
enhancing customer service productivity by accelerating response times and improving the
accuracy of information provided. Survey results indicate that the majority of customers are
satisfied with their interaction experiences, particularly regarding the speed and relevance of
recommendations provided by the AI system. Additionally, this study highlights the importance
of synergy between AI technology and human interaction in delivering optimal customer service,
especially for start-up companies. By integrating AI to handle routine tasks, start-ups can
significantly reduce operational costs and improve efficiency without the need to expand their
workforce. This allows human agents to focus on more complex customer issues that require
Journal of Management and Informatics (JMI)
Vol. 3 No. 2 August 2024
E-ISSN: 2961-7731; P-ISSN: 2961-7472, Pages 267-281
empathy and critical thinking, ensuring a personalized customer experience. For start-up
companies with limited resources, this balance between AI and human interaction can provide a
scalable, cost-effective solution to maintaining high service standards while fostering customer
loyalty and business growth.
Recommendation
Several recommendations can be made for start-up companies considering the
implementation of AI in their customer service operations. First, companies must ensure that the
AI systems employed are designed to efficiently handle routine inquiries, allowing human staff
to focus on more complex tasks that require empathy. Second, companies should continuously
invest in training and development for customer service teams to enable effective collaboration
with AI systems. Third, it is crucial for companies to maintain transparency and safeguard
customer data in the use of AI, in order to uphold customer trust. Lastly, companies should
periodically evaluate the effectiveness of AI systems and make necessary adjustments to enhance
overall customer service performance. By following these recommendations, start-up companies
can maximize the benefits of AI technology and improve their competitiveness in an increasingly
competitive market.
Conflict of Interest
The authors declare no conflict of interest regarding the publication of this paper.
Acknowledgment
The authors would like to express their sincere gratitude to Dr. Ir. Agus Wibowo, M.Kom,
M.Si, MM., the founding coordinator, for his invaluable guidance and support throughout this
research. We also extend our appreciation to Universitas STEKOM for providing the necessary
facilities and resources that made this study possible.
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