INVESTIGATING AI IMPACT ON CUSTOMER SATISFACTION
A Dissertation
SEPTEMBER, 2023
SIGNED STATEMENT
I declare that this dissertation has not already been accepted in substance for any degree and is
not concurrently submitted in candidature for any degree. It is the result of my own independent
research except where otherwise stated.
_______________________
Name
i
ACKNOWLEDGEMENTS
All glory…
ii
ABSTRACT
This research delves into the dynamic landscape of artificial intelligence (AI) and its profound
impact on customer satisfaction in contemporary businesses and organizations. It investigates
five critical research questions to uncover the prevalence of AI, its advantages, customer
acceptance barriers, the role of AI in customer service, and the significance of customer
education in shaping satisfaction and acceptance of AI-driven solutions in today’s businesses
and organizations.
The study employed a descriptive survey design with a questionnaire as the primary data
collection tool. It ensured research instrument validity and reliability through a pilot study,
yielding a Cronbach's Alpha coefficient of r = 0.874 for the questionnaire. The diverse sample
included participants aged 18 to 54 from six industries, and data analysis used tables, charts,
simple percentages, cumulative frequencies, and descriptive statistics for presentation.
This study underscores AI's increasing prevalence in modern businesses and its collaborative
advantages when combined with human efforts for enhanced efficiency. Despite these benefits,
challenges persist in gaining customer acceptance, attributed to issues like language
comprehension, transparency, insufficient communication about AI implementation, trust
erosion due to errors, and potential information overload from AI-driven services. The research
highlights AI-driven customer service's crucial role, with its quick responses and effective issue
resolution significantly boosting customer acceptance. Additionally, educating customers
about AI and shaping their satisfaction and acceptance within businesses is essential for
fostering trust in this technology-driven era.
The recommendations emphasize the importance of continued investment in AI technologies
to enhance operational efficiency, foster data-driven decision-making, and drive innovation. It
is crucial to align AI initiatives with both business objectives and customer needs, promoting
a collaborative work environment for AI to complement human skills. Organizations should
train employees to effectively collaborate with AI, emphasizing the unique value of human
abilities. Proactive measures to address customer concerns about AI, privacy, and job
displacement, including transparent communication and robust security, are essential.
Prioritizing AI-driven customer service solutions, combining AI with human agents, and
educating customers about AI’s benefits and limitations are steps to empower informed choices
when interacting with AI solutions.
Keywords: AI, Customer Satisfaction, Customer Education, Ai-driven services
Word Count: 340
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CONTENTS
SIGNED STATEMENT ............................................................................................................. i
ACKNOWLEDGEMENTS .......................................................................................................ii
CONTENTS .............................................................................................................................. iv
LIST OF ABBREVIATIONS ................................................................................................... vi
LIST OF TABLES ...................................................................................................................vii
LIST OF FIGURES ............................................................................................................... viii
CHAPTER ONE ........................................................................................................................ 1
1.0
Introduction ................................................................................................................. 1
1.1
Background to the Study ............................................................................................. 1
1.2
Statement of Problem .................................................................................................. 3
1.3
Purpose of the Study ................................................................................................... 3
1.4
Research Questions ..................................................................................................... 4
1.5
Significance of the Study ............................................................................................ 4
1.6
Operational Definition of Terms ................................................................................. 5
1.6.1
Artificial Intelligence (AI) ................................................................................... 5
1.6.2
Customer satisfaction ........................................................................................... 5
CHAPTER TWO ....................................................................................................................... 6
2.0
Literature Review ........................................................................................................ 6
2.1
Overview of Artificial Intelligence ............................................................................. 6
2.2
History and Evolution of Artificial Intelligence (AI).................................................. 6
2.2.1
The Origins of Artificial Intelligence (AI) .............................................................. 6
2.2.2
The Rise of Machine Learning ................................................................................ 7
2.2.4
Artificial Intelligence (AI) in the Present and Future .............................................. 7
2.3
Key Components of Artificial Intelligence (AI) ......................................................... 8
2.4
Applications of Artificial Intelligence (AI) ................................................................. 8
2.5
Challenges and Limitations of Artificial Intelligence ................................................. 9
2.6
AI and corresponding technologies in businesses and organizations ......................... 9
2.7
Overview of Customer Satisfaction .......................................................................... 10
2.7.1
Importance of Customer Satisfaction .................................................................... 10
2.8
Relationship Between AI and Customer Satisfaction ............................................... 11
2.9
AI and Human Efforts in Today’s Businesses and Organizations ............................ 12
2.10 Factors Impeding Customer Acceptance of AI’s Services........................................ 13
2.11 The roles of AI-driven customer service interactions in shaping customer
satisfaction ............................................................................................................................ 13
2.11 Customer Education and AI ...................................................................................... 14
2.12 Previous Studies on AI impact on customer satisfaction .......................................... 15
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CHAPTER THREE ................................................................................................................. 24
3.0
Research Method ....................................................................................................... 24
3.1
Research Design ........................................................................................................ 24
3.2
Population of the Study ............................................................................................. 24
3.3
Samples and Sampling Techniques ........................................................................... 24
3.4
Instrument for Data Collection .................................................................................. 25
3.5
Validity and Reliability of the Instrument................................................................. 25
3.6
Procedure of Data Collection .................................................................................... 27
3.7
Method of Data Analysis........................................................................................... 27
CHAPTER FOUR .................................................................................................................... 28
4.0
DATA ANALYSIS AND DISCUSSION OF FINDINGS ....................................... 28
4.1
Data Analysis ............................................................................................................ 28
4.2
Discussion of Findings .............................................................................................. 44
CHAPTER FIVE ..................................................................................................................... 51
5.1
Conclusion................................................................................................................. 51
5.2
Recommendations ..................................................................................................... 52
APPENDICES ......................................................................................................................... 54
REFERENCES ........................................................................................................................ 57
v
LIST OF ABBREVIATIONS
1.
AI
-
Artificial Intelligence
vi
LIST OF TABLES
Tables
Page
1.
Characteristics of Sample
2.
Simple Percentage responses on the Prevalence of AI and corresponding
technologies in today’s businesses and organizations.
29
3.
Descriptive Statistics table for research question 1
4.
Simple Percentage Responses on the Advantage of Ai and human efforts
in today’s businesses and organizations
32
5:
Descriptive Statistics table for research question 2
33
6.
Factors Impeding Customer Acceptance of AI’s Services
35
7.
Descriptive Statistics table for research question 3
36
8.
Roles of AI-driven customer service interactions, including response
time and issue resolution, in shaping customer satisfaction
38
9.
Descriptive Statistics table for research question 4
39
10.
Role of customer education and understanding of AI play in shaping
their satisfaction and acceptance of AI-driven solutions
41
Descriptive Statistics table for research question 5
43
11.
26
vii
30
LIST OF FIGURES
Figures
1.
2.
3.
4.
5
Pages
Bar chart showing the frequency distribution for each parameter on
the prevalence of AI and its corresponding technologies in today’s
businesses and organizations
30 – 31
Bar chart showing the frequency distribution for each parameter on
the Advantage of AI and human efforts in today’s businesses and
organizations
33 – 34
Bar chart showing the frequency distribution for each parameter on
the Factors Impeding Customer Acceptance of AI’s Services
37
Bar chart showing the frequency distribution for each parameter on
the roles of AI-driven customer service interactions, including
response time and issue resolution, in shaping customer satisfaction
40
Bar chart showing the frequency distribution for each parameter on
the role of customer education and understanding of AI play in
shaping their satisfaction and acceptance of AI-driven solutions
43 - 44
viii
CHAPTER ONE
1.0
Introduction
Artificial Intelligence (AI) has emerged as a powerful tool across various industries,
revolutionizing the way businesses interact with their customers. In other words, Artificial
intelligence (AI) has made remarkable strides in recent years, revolutionizing many industries
and altering how businesses run. Customer service is one industry where AI has made
significant progress. Predictive analytics, chatbots, and other AI-based technologies open new
opportunities for enhancing customer interactions and overall customer satisfaction. In today's
highly competitive marketplace, understanding the impact of AI on customer satisfaction is
crucial for organizations seeking to deliver exceptional customer experiences, gain a
competitive edge, and foster long-term customer loyalty. To better understand how businesses
use AI to deliver individualized experiences, seamless support, and effective service, this study
will look at the effect of AI on customer satisfaction. Companies can make educated decisions
to maximize customer satisfaction and loyalty by understanding the implications of AI
adoption in customer service. Thus, this study aims to investigate the impact of AI on customer
satisfaction and the numerous benefits it brings.
1.1
Background to the Study
Due to the increasing demand for better customer experiences, the integration of AI in
customer service has quickly advanced. Artificial intelligence (AI)-powered chatbots and
virtual assistants that use machine learning and natural language processing are now
commonplace tools for automating customer interactions and offering quick support. These
tools provide round-the-clock assistance, effectively handling common questions and
straightforward problem-solving (Liao et al., 2021). Furthermore, AI-driven recommendation
systems use consumer data to offer tailored suggestions, enhancing product discovery and
customer satisfaction (Chen et al., 2021).
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A company’s ability to satisfy its customers is crucial to success in all industries.
Satisfied customers are more likely to repurchase products, show greater loyalty, and spread
favourable word-of-mouth, improving brand reputation and boosting profitability (Kim and
Lee, 2020). Therefore, understanding how AI affects customer satisfaction is essential for
businesses looking to improve their customer service strategies. The ability to provide
personalized experiences, seamless support, and increased efficiency made possible by AI
technologies has the potential to increase customer satisfaction significantly. AI algorithms can
provide individualized recommendations, foresee customer needs, and provide pertinent
information by analyzing enormous amounts of customer data. AI-enabled chatbots and virtual
assistants can respond to queries quickly, guaranteeing clients get assistance immediately and
cutting down on wait times (Liao et al., 2021). Additionally, AI-driven analytics can improve
the precision and effectiveness of customer service processes, resulting in shorter response
times, fewer errors, and higher levels of customer satisfaction (Jiang et al., 2020).
While using AI in customer service has a lot of potential advantages, there are also
some possible drawbacks and worries. Customer data collection and processing raise privacy
and security concerns, calling for strong security measures to protect sensitive data (Bughin et
al., 2021). Additionally, the acceptance and trust of users in AI-powered systems may be a
barrier, necessitating that businesses focus on transparency, unambiguous communication, and
user education to promote user confidence in AI technologies (McKnight et al., 2020).
This study aims to offer valuable insights for companies looking to optimize their
customer service strategies by thoroughly investigating the effect of AI on customer
satisfaction. The results will help organizations make decisions to improve customer
satisfaction, brand loyalty, and overall business performance by shedding light on the benefits,
challenges, and implications of adopting AI.
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1.2
Statement of Problem
The rapid advancement and widespread adoption of Artificial Intelligence (AI) have
raised questions about its influence on customer satisfaction. While AI offers promising
capabilities for personalization, recommendations, and customer service, its impact on
customer satisfaction remains unclear. It is imperative to investigate the extent to which AI
strategies effectively enhance customer satisfaction, considering factors such as the accuracy
and relevance of AI recommendations, the quality of AI-driven customer service interactions,
and the adaptability of AI systems to changing customer preferences. Additionally, ethical
considerations and customer perceptions of AI usage must be examined to establish trust and
ensure a positive impact on customer satisfaction. By understanding the impact of AI on
customer satisfaction, businesses can optimize their AI strategies and deliver exceptional
customer experiences, thereby fostering long-term customer loyalty.
1.3
Purpose of the Study
The study aimed to investigate AI's impact on customer satisfaction. The specific
objectives of the study were to:
1.
Identify the level of prevalence of AI and corresponding technologies in today’s
businesses and organizations.
2.
Compare the importance of AI and human efforts in today’s businesses and
organizations
3.
Ascertain factors impeding customer acceptance of Ai’s services.
4.
Identify the role of AI-driven customer service interactions, including response time
and issue resolution, in shaping customer satisfaction.
5.
Examine the role customer education and understanding of AI play in shaping their
satisfaction and acceptance of AI-driven solutions
3
1.4
Research Questions
This research was geared towards answering the questions below:
1.
What is the level of prevalence of AI and corresponding technologies in today’s
businesses and organizations?
2.
What is the advantage of AI and human efforts in today’s businesses and
organizations?
3.
What are the factors impeding customer acceptance of Ai’s services?
4.
What are the roles of AI-driven customer service interactions, including response
time and issue resolution, in shaping customer satisfaction?
5.
What is the role of customer education and understanding of AI play in shaping
their satisfaction and acceptance of AI-driven solutions?
1.5
Significance of the Study
Investigating the impact of Artificial Intelligence (AI) on customer satisfaction holds
immense significance in today's business landscape. As AI technologies continue to evolve and
integrate into various industries, understanding their effects on customer satisfaction becomes
essential. Investigative efforts in this area provide businesses with valuable insights and
opportunities to optimize their AI strategies, enhance customer experiences, and ultimately
drive long-term customer loyalty. The significance of AI on customer satisfaction cannot be
overstated. AI technologies offer opportunities for businesses to deliver highly personalized
experiences, improve customer service, analyze vast amounts of data, provide accurate
recommendations, streamline problem-solving processes, engage customers proactively, and
continuously improve their offerings. By harnessing the power of AI, organizations can
enhance customer satisfaction, foster long-term loyalty, and gain a competitive edge in today's
customer-centric marketplace. Embracing AI-driven solutions is essential for businesses
4
aiming to meet the evolving needs and expectations of their customers and deliver exceptional
experiences that drive customer satisfaction.
1.6
Operational Definition of Terms
1.6.1 Artificial Intelligence (AI)
AI represents a field of study and technology that aims to create intelligent machines
capable of performing tasks that typically require human intelligence, with the potential to
bring significant advancements and benefits to various aspects of our lives.
1.6.2 Customer satisfaction
Customer satisfaction refers to the measurement and evaluation of a customer's overall
contentment, fulfillment, or happiness with their experience, interaction, or transaction with a
product, service, or organization. It is a subjective assessment that reflects the customer's
perception of whether their expectations were met or exceeded based on their interactions and
the value received from the company.
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CHAPTER TWO
2.0
Literature Review
2.1
Overview of Artificial Intelligence
Artificial Intelligence (AI) is a field of computer science focused on creating intelligent
machines that can simulate human cognitive abilities (Russell & Norvig, 2016). It traces its
origins back to the 1950s when pioneers like Alan Turing proposed the concept of machines
capable of human-like intelligence (Turing, 1950). Over the years, AI has evolved
significantly, with key components such as Machine Learning (ML), Natural Language
Processing (NLP), and Computer Vision (CV) playing vital roles in its development (Mitchell,
1997). Today, AI finds diverse applications across industries, transforming healthcare,
transportation, and daily life (Topol, 2019).
2.2
History and Evolution of Artificial Intelligence (AI)
The history of Artificial Intelligence (AI) is a fascinating journey that spans several
decades, marked by significant milestones, breakthroughs, and paradigm shifts. The quest to
create machines with human-like intelligence dates back to the 1950s, and over the years, AI
has undergone various phases of development, leading to its current state as a transformative
technology that permeates many aspects of modern life. AI's history began with the Dartmouth
Conference in 1956, marking its formal emergence as an academic field (Nilsson, 2014). Early
AI research focused on symbolic reasoning, leading to expert systems in the 1980s. The 1990s
saw the rise of neural networks and machine learning algorithms, which laid the foundation for
modern AI (Nilsson, 2014).
2.2.1 The Origins of Artificial Intelligence (AI)
The birth of AI as an academic discipline is attributed to Alan Turing’s 1950 paper
introducing the Turing Test, which assesses a machine's ability to exhibit human-like
intelligence. The Dartmouth Conference in 1956 coined the term "Artificial Intelligence,"
6
envisioning machines capable of reasoning and problem-solving. However, the 1970s and
1980s brought challenges, leading to the "AI Winter" due to unrealistic expectations, limited
computing power, and inadequate funding. This period saw a shift towards specialized
applications, with expert systems utilizing rules and heuristics to solve specific problems.
Though successful in certain domains, they also highlighted AI's limitations for complex realworld challenges. Despite setbacks, AI research gained momentum during the AI Winter,
paving the way for further progress and exploration of different approaches.
2.2.2 The Rise of Machine Learning
In the 1990s, AI research experienced a revival fueled by machine learning
advancements. Algorithms enable machines to learn from data, without explicit programming.
Neural networks, inspired by the brain, excelled in pattern recognition and language
processing. Machine learning found applications in data mining, language processing, and
image recognition. Reinforcement learning facilitated AI systems to learn from feedback in
dynamic environments, making strides in game-playing agents and robotics.
2.2.3 Big Data and Deep Learning
The 2010s marked a turning point for AI, largely driven by the abundance of big data
and advances in computational power. Deep learning, a subset of machine learning, gained
prominence for its ability to create artificial neural networks with numerous layers, enabling
the processing of vast amounts of data and achieving state-of-the-art performance in areas such
as image recognition, speech synthesis, and language translation.
2.2.4 Artificial Intelligence (AI) in the Present and Future
Today, AI is an integral part of various industries, including healthcare, finance,
transportation, and entertainment. AI-powered systems and applications are continuously
evolving, contributing to autonomous vehicles, personalized recommendations, virtual
assistants, and more. The field of AI continues to progress rapidly, with ongoing research and
7
development in areas like explainable AI, reinforcement learning, and quantum computing.
However, challenges persist, including ethical considerations, potential bias in algorithms, and
concerns about the impact of AI on the job market and society at large. As AI continues to
advance, the future promises exciting possibilities and transformative changes that could shape
how we live, work, and interact with machines in the years to come.
2.3
Key Components of Artificial Intelligence (AI)
Artificial Intelligence (AI) encompasses various technologies enabling machines to
simulate human intelligence. Machine Learning (ML) lets machines learn from data without
explicit programming, while Natural Language Processing (NLP) enables computers to
understand and generate human language. Computer Vision (CV) allows machines to interpret
visual information, and Robotics integrates AI into physical robots. Knowledge Representation
and Reasoning encode information for AI systems to reason and decide, and Planning and
Decision-Making involve algorithms optimizing actions in dynamic environments. Expert
Systems mimic human experts' decision-making in specific domains, aiding in tasks like
medicine and engineering. These components form the foundation of AI, enabling its diverse
applications across industries and domains.
2.4
Applications of Artificial Intelligence (AI)
Artificial Intelligence (AI) has transformative applications across various sectors. In
healthcare, AI aids disease diagnosis, treatment, and drug discovery through image analysis
and natural language processing. In finance, AI automates processes, detects fraud, and predicts
market trends. AI plays a vital role in developing autonomous vehicles and optimizing traffic
in transportation. In gaming, AI agents exhibit human-like behaviors, while in entertainment,
AI recommends personalized content on streaming platforms. In manufacturing, AI-driven
robotics enhance efficiency and predictive maintenance reduces downtime. AI also contributes
to environmental monitoring, analyzing real-time data for pollution detection and climate
8
modeling. AI's versatility continues to revolutionize industries, enhancing efficiency, accuracy,
and innovation.
2.5
Challenges and Limitations of Artificial Intelligence
Artificial Intelligence (AI) has made remarkable strides in recent years, but it still faces
several challenges and limitations that impede its widespread adoption and deployment. As AI
becomes more prevalent in various industries and applications, concerns revolve around its
potential impact on human activities (Brynjolfsson & McAfee, 2014). Ethical concerns arise
due to AI's potential impact on privacy, security, and bias (Floridi et al., 2018). Ensuring
transparency and accountability in AI decision-making is crucial (Diakopoulos, 2016).
Technical challenges involve improving AI's interpretability and explainability (Lipton, 2016).
Addressing data quality and availability issues is essential for effective AI models (Hutson,
2018). The fear of job displacement by AI automation poses economic challenges
(Brynjolfsson & McAfee, 2014). To harness AI's potential for societal benefit, collaboration
among stakeholders and robust regulatory frameworks is necessary (Lepri et al., 2018).
2.6
AI and corresponding technologies in businesses and organizations
As of today, the prevalence of AI and corresponding technologies in businesses and
organizations has significantly increased across various industries. AI adoption has accelerated
due to advancements in technology, increased data availability, and the potential to enhance
operational efficiency and customer experiences. Artificial Intelligence (AI) and its
corresponding technologies have significantly impacted businesses and organizations, driving
innovation, efficiency, and competitive advantage. AI's ability to process vast amounts of data
and extract valuable insights has transformed decision-making processes, enabling
organizations to make informed and data-driven choices (Varian, 2014). Machine Learning
algorithms have been employed in diverse applications, such as customer segmentation,
9
predictive analytics, and recommendation systems, enhancing personalized user experiences
(Provost & Fawcett, 2013).
Natural Language Processing (NLP) has revolutionized customer interactions through
chatbots and virtual assistants, providing efficient and personalized customer support
(Sutskever et al., 2014). Sentiment analysis powered by NLP enables organizations to gauge
customer feedback and sentiments, leading to improved products and services (Cambria et al.,
2016).
Computer Vision has found applications in industries like manufacturing and retail,
optimizing quality control and inventory management with automated visual inspection and
object recognition systems (LeCun et al., 2015). Moreover, AI-driven automation has
streamlined various business processes, reducing operational costs and minimizing errors.
Robotic Process Automation (RPA) performs repetitive tasks with speed and accuracy,
liberating human resources for higher-value activities (Davenport, 2018). AI and Big Data
integration have facilitated data-driven marketing strategies, allowing businesses to target
specific customer segments and optimize advertising campaigns (Sheth, 2019).
2.7
Overview of Customer Satisfaction
Customer satisfaction is a crucial aspect of business success and refers to the level of
contentment customers experience with a product, service, or overall interaction with a
company. It is a key indicator of how well a business meets or exceeds customer expectations
and is essential for building strong customer relationships, loyalty, and advocacy. Customer
satisfaction is not only a reflection of the quality of the product or service but also the entire
customer experience, including pre-purchase interactions, support, and after-sales service.
2.7.1 Importance of Customer Satisfaction
Customer satisfaction holds significant importance for businesses due to several
reasons. Satisfied customers are more likely to stay loyal to a brand, leading to increased
10
customer retention and reduced churn, essential for long-term business sustainability. Positive
customer experiences and high satisfaction levels contribute to a positive brand reputation,
resulting in word-of-mouth marketing and organic growth. In highly competitive markets,
customer satisfaction becomes a significant differentiator, giving companies a competitive
advantage. Satisfied customers also lead to repeat purchases, increasing customer lifetime
value and revenue. Additionally, high customer satisfaction correlates with reduced complaints
and negative feedback, while promptly addressing and resolving customer issues enhances
satisfaction levels. Finally, satisfied customers indicate excellent service, boosting employee
morale and motivation.
2.8
Relationship Between AI and Customer Satisfaction
The relationship between AI and customer satisfaction has become increasingly
significant in modern business contexts. AI-powered technologies have revolutionized the way
companies interact with their customers, leading to enhanced satisfaction and personalized
experiences. AI-driven chatbots and virtual assistants provide quick and efficient customer
support, addressing queries and resolving issues promptly, which contributes to higher
customer satisfaction (Sutskever et al., 2014). These AI systems can handle a large volume of
customer interactions simultaneously, ensuring minimal waiting times and improving overall
customer service.
AI-driven recommendation systems play a crucial role in enhancing customer
satisfaction. By analyzing customer behavior and preferences, these systems provide
personalized product or content recommendations, increasing customer engagement and
loyalty (Sheth, 2019). AI's ability to process vast amounts of data enables businesses to gain
valuable insights into customer preferences, enabling them to tailor their offerings to meet
specific customer needs effectively. AI plays a crucial role in influencing customer satisfaction
by streamlining customer interactions, providing personalized recommendations, and
11
improving overall customer service. However, ethical and bias-related concerns must be
carefully managed to harness AI's full potential for enhancing customer satisfaction in the long
term.
2.9
AI and Human Efforts in Today’s Businesses and Organizations
In today’s businesses and organizations, the integration of Artificial Intelligence (AI)
with human efforts drives innovation and efficiency. AI augments human capabilities,
improving decision-making, productivity, and customer satisfaction. AI's strength lies in data
analysis, where it can process large datasets in real time, extracting valuable insights that
humans may miss. This enables organizations to make data-driven decisions more efficiently
and accurately. (Varian, 2014). Additionally, AI algorithms in predictive analytics enable
businesses to anticipate customer preferences and market trends, assisting in strategic planning
and product development (Provost & Fawcett, 2013).
AI-driven automation streamlines repetitive tasks, freeing up human resources for
higher-value activities. Robotic Process Automation (RPA) performs mundane tasks with
precision, reducing errors and operational costs. This partnership between AI and humans
optimizes productivity, allowing employees to allocate their time and skills effectively. AI has
also improved customer interactions, enhancing satisfaction. AI-powered chatbots and virtual
assistants offer 24/7 support, promptly addressing queries and resolving issues. These systems
handle large volumes of interactions simultaneously, reducing waiting times and enhancing
overall customer service. (Davenport, 2018 and Sutskever et al., 2014). These systems can
handle a large volume of interactions simultaneously, reducing waiting times and enhancing
overall customer service.
AI and human collaboration in today's businesses and organizations have redefined the
way we operate and interact with customers. AI's ability to analyze data, automate tasks, and
enhance customer interactions has proven transformative. By harnessing the power of AI while
12
addressing ethical concerns, organizations can unlock the full potential of this partnership and
create a more efficient, innovative, and customer-centric future.
2.10
Factors Impeding Customer Acceptance of AI’s Services
Several factors impede customer acceptance of AI's services, limiting its full potential in
various industries. One key barrier is the lack of transparency and explainability in AI decisionmaking processes (Lipton, 2016). Customers may be hesitant to trust AI-driven
recommendations or outcomes when they are unable to understand how AI arrived at its
conclusions. Another concern is about data privacy and security which can hinder customer
acceptance of AI services (Li, 2018). Customers may worry about their personal information
being mishandled or used without their consent. Furthermore, potential biases in AI algorithms
can lead to unequal treatment of customers, leading to distrust and reluctance to engage with
AI services (Mittelstadt et al., 2016). Addressing these challenges through improved
transparency, data privacy measures, and bias mitigation strategies is essential to foster
customer acceptance and trust in AI's services.
2.11
The roles of AI-driven customer service interactions in shaping customer
satisfaction
AI-driven customer service interactions play a crucial role in shaping customer
satisfaction by providing efficient and personalized support to customers. AI-powered chatbots
and virtual assistants can handle a large volume of customer queries simultaneously, reducing
waiting times and improving response times (Sutskever et al., 2014). This quick and responsive
service enhances customer satisfaction by addressing their needs promptly.
AI-driven customer service interactions can provide personalized experiences. By
analyzing customer data and previous interactions, AI systems can offer tailored product
recommendations and assistance, making customers feel valued and understood (Sheth, 2019).
This personalized approach enhances customer engagement and loyalty. AI-driven interactions
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can operate 24/7, providing round-the-clock support to customers. This accessibility ensures
that customers can get help whenever they need it, increasing overall customer satisfaction
(Sutskever et al., 2014).
2.11
Customer Education and AI
Customer education plays a crucial role in the successful adoption and acceptance of
AI technologies. As businesses integrate AI-driven solutions into their products and services,
it is essential to educate customers about AI's capabilities, benefits, and limitations. Customer
education helps demystify AI, dispel misconceptions, and build trust, leading to higher
customer confidence in using AI-powered tools and services.
Educating customers about AI's potential benefits is vital. AI can improve product
recommendations, enhance customer support, and personalize user experiences. When
customers understand how AI can add value to their interactions with a brand, they are more
likely to embrace and appreciate its implementation (Provost & Fawcett, 2013). It is important
to be transparent about AI's limitations and potential risks. Customer education should
encompass discussions about data privacy, security, and the measures in place to protect
sensitive information. This transparency fosters customer trust, assuring them that their data is
being handled responsibly (Li, 2018).
Customer education on AI ethics and bias is essential to address concerns about fairness
and equal treatment. Customers need to understand how AI algorithms work, how decisions
are made, and how potential biases are identified and addressed (Mittelstadt et al., 2016).
Organizations can employ various educational channels to inform their customers about AI,
such as websites, blogs, webinars, and interactive tutorials. Engaging and user-friendly
materials can help customers grasp AI concepts and applications more effectively.
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2.12
Previous Studies on AI impact on customer satisfaction
Several sectors, businesses, and organizations deal with a diverse and wide range of
customers and each sector strives to provide every available resource to satisfy their customers.
In the quest for customer satisfaction, many industries, sectors, businesses, and organizations
have employed the use of AI to enhance customer satisfaction. These AI and its corresponding
techs have a direct and indirect impact on the level of satisfaction enjoyed by the customers.
Fong, Tan, & Chong, 2020 think that AI-powered customer service (i.e., the use of
artificial intelligence technologies, such as chatbots and virtual assistants, to handle customer
interactions and inquiries) has a direct impact on customer satisfaction. The researchers found
that AI-powered chatbots positively impact customer satisfaction by providing quick and
accurate responses. The researchers believed that AI-driven customer service has shown
tremendous potential in enhancing customer satisfaction. The study found that AI-powered
chatbots and virtual assistants provide quick and accurate responses to customer inquiries,
reducing response times and wait periods (Fong, Tan, & Chong, 2020). By handling routine
queries efficiently, AI allows human agents to focus on more complex issues, improving the
overall customer experience. These AI-driven solutions have demonstrated significant
potential to enhance customer satisfaction by providing efficient and effective support to
customers.
Chatbots and virtual assistants are programmed with vast amounts of information and
are capable of processing queries at lightning speed. This rapid response time is crucial in
today's fast-paced business environment, where customers expect timely answers to their
questions. Moreover, AI-powered customer service reduces the need for customers to wait in
long queues or on hold to speak with a human agent. This not only saves customers' time but
also contributes to their overall satisfaction. Furthermore, AI-driven customer service solutions
continuously learn and improve over time. As a result, the AI becomes more adept at
15
understanding customer needs and providing accurate responses with each interaction which
results in satisfying the customer (Fong, Tan, & Chong, 2020).
The researchers concluded that AI-powered customer service has shown tremendous
potential in enhancing customer satisfaction. By providing quick and accurate responses,
reducing response times, and enabling human agents to focus on more complex issues, AIdriven solutions improve the overall customer experience. Thus, AI can be a powerful tool in
delivering exceptional customer service and fostering long-term customer loyalty and ultimate
satisfaction.
From the work of Zhang, Wang, Liu, & Jia, on Personalization and Recommendation
Engines. The researchers opine that AI-based recommendation engines have been instrumental
in delivering personalized experiences to customers (Zhang, Wang, Liu, & Jia, 2020), thereby
fostering customer satisfaction. The researchers found that AI-powered recommendation
systems improve user satisfaction and engagement in e-commerce. By analyzing vast amounts
of customer data, AI algorithms offer tailored product or content suggestions, leading to higher
customer satisfaction and engagement. Personalization fosters a sense of relevance, making
customers feel understood and valued. Personalization and recommendation engines powered
by AI have emerged as essential tools for delivering personalized experiences to customers
(Zhang, Wang, Liu, & Jia, 2020). These systems utilize sophisticated algorithms to analyze
vast amounts of customer data, such as browsing history, purchase behavior, preferences, and
demographic information, to provide tailored product or content suggestions.
The impact of personalization goes beyond just recommending relevant products or
content. By tailoring the customer experience to individual preferences, AI-based
recommendation engines create a more enjoyable and seamless journey for customers. This, in
turn, can lead to increased customer engagement and loyalty. Customers are more likely to stay
engaged with a platform that consistently delivers relevant and valuable content or product
16
recommendations. The researchers concluded that AI-based recommendation engines have
revolutionized customer experiences by delivering personalized product or content
suggestions. The ability to analyze vast amounts of customer data and offer tailored
recommendations fosters a sense of relevance, making customers feel understood and valued.
This level of personalization not only enhances customer satisfaction and engagement but also
leads to increased customer retention, loyalty, and revenue generation.
AI Predictive Analytics and Forecasting also contribute to customer satisfaction. This
is deduced from the work of Moro, Cortez, & Rita, 2015. AI's predictive analytics capabilities
enable businesses to anticipate customer needs and preferences. By analyzing historical data,
AI can forecast trends and demand patterns, empowering companies to proactively address
customer expectations (Moro, Cortez, & Rita, 2015). Anticipating customer demands enhances
customer satisfaction and loyalty.
Predictive analytics and forecasting powered by AI have become invaluable tools for
businesses seeking to understand and anticipate customer behavior. By leveraging vast
amounts of historical data, AI algorithms can analyze patterns and trends to make accurate
predictions about future customer needs and preferences. Predictive analytics enhances
customer loyalty by enabling businesses to offer targeted promotions and personalized
recommendations. By understanding customer preferences, businesses can deliver relevant
offers that resonate with individual customers, increasing the likelihood of conversion and
repeat business. Personalized promotions create a sense of value and appreciation, further
strengthening the customer-business relationship.
The researchers concluded that AI's predictive analytics capabilities have
revolutionized the way businesses understand and address customer needs. By analyzing
historical data to forecast trends and demand patterns, businesses can proactively tailor their
offerings, optimize inventory management, and provide personalized experiences. Anticipating
17
customer demands enhances customer satisfaction and loyalty, contributing to the long-term
success of businesses in today's competitive market.
AI-powered solutions have significantly impacted the e-commerce sector. The study by
Senecal & Nantel, 2004 has shown that AI-driven personalization, recommendation engines,
and chatbots positively influence customer satisfaction and loyalty (Senecal & Nantel, 2004).
Personalized product recommendations and efficient customer support through AI enhance the
overall e-commerce experience. The integration of AI in e-commerce has brought about
transformative changes, revolutionizing the way businesses interact with customers and
enhancing the overall shopping experience. AI-powered solutions in the e-commerce sector
encompass a range of applications, including personalized product recommendations,
recommendation engines, and chatbots, all of which have a positive impact on customer
satisfaction and loyalty.
One of the most significant contributions of AI in e-commerce is personalized product
recommendations. AI algorithms analyze a customer's browsing and purchase history,
preferences, and behavior to provide tailored product suggestions. This level of personalization
creates a sense of relevance, as customers feel that the platform understands their unique needs
and desires. Studies have shown that personalized product recommendations can lead to higher
customer engagement, increased conversion rates, and enhanced customer satisfaction
(Senecal & Nantel, 2004). The authors concluded that the impact of AI in e-commerce has been
profound, as AI-driven personalization, recommendation engines, and chatbots have
significantly
influenced
customer
satisfaction
and
loyalty.
Personalized
product
recommendations create a sense of relevance and engagement, while AI-driven chatbots
provide swift and efficient customer support. These AI-powered solutions enhance the overall
e-commerce experience, driving business success and most especially fostering customer
loyalty and satisfaction.
18
In Obermeyer et al., work on the Bias and Fairness of Artificial Intelligence to prevent
negative impact on customers, the researchers opine that AI algorithms trained on biased data
can perpetuate discrimination and fairness issues. Addressing bias in AI models is essential to
prevent negative impacts on customer experiences (Obermeyer et al., 2019). Fair and unbiased
AI systems contributes to equitable customer interactions and satisfaction. Bias and fairness
are critical considerations in AI development, especially when AI algorithms are trained on
biased data. Biases present in training data can lead to discriminatory outcomes, perpetuating
inequalities and fairness issues in AI-driven customer experiences. Addressing bias in AI
models is essential to create fair and equitable customer interactions, ultimately leading to
higher levels of customer satisfaction.
The researchers concluded that by addressing bias and ensuring fairness in AI models,
businesses can create more inclusive and equitable customer interactions. Fair and unbiased AI
systems contributes to a positive customer experience, as customers feel valued and respected,
irrespective of their demographics or background. Ultimately, mitigating bias enhances
customer satisfaction and helps businesses build strong and lasting relationships with their
customers.
Liao et al., 2019 discovered that educating customers about AI and its role in healthcare
increases acceptance and satisfaction. The researchers opine that Customer education and
understanding of AI play a critical role in shaping their acceptance of AI-driven solutions and
the satisfaction customers will derive from it. Educating customers about AI's benefits and
limitations can increase their trust and willingness to embrace AI technologies (Liao et al.,
2019). Transparent communication about how AI improves customer experiences enhances
customer acceptance. Customer acceptance of AI-driven solutions is influenced by their level
of education and understanding of AI technology. Educating customers about AI's benefits and
limitations is crucial for fostering trust and increasing their willingness to embrace AI
19
technologies in their interactions with businesses. Liao et al., 2019 conclude that by educating
customers about AI's benefits, limitations, and data usage practices, businesses can shape
customer acceptance of AI-driven solutions positively. Transparent communication and
providing a seamless experience that combines AI capabilities with human touchpoints can
lead to higher levels of customer trust and satisfaction with AI technologies.
AI-powered personalized recommendations and targeted marketing have been shown
to improve customer retention rates. Satisfied customers are more likely to remain loyal to a
brand that caters to their preferences (Füller, Hutter, Hautz, & Matzler, 2014). Retaining
customers through personalized experiences is crucial for long-term business success. One of
the impacts of AI on customer satisfaction is customer retention. If businesses are able to retain
their customers in a particular business, then it is an indication that those customers are satisfied
with the services the business renders.
Fuller et al., 2014 and Moro, Cortez & Rita, 2015 conclude that AI's impact on customer
retention is substantial. Personalized recommendations, targeted marketing, anticipation of
customer needs, enhanced customer experiences, and churn prevention contribute to improved
customer satisfaction and loyalty. By leveraging AI to provide tailored experiences and address
individual preferences, businesses can enhance customer retention, leading to long-term
success and sustainable growth.
Xu, Akula, Srinivasan, & Manikonda, 2021 work on AI and Customer Feedback
Analysis reveals that AI technologies, such as sentiment analysis, have been effective in
analyzing customer feedback and sentiments. These insights help businesses identify areas for
improvement and enhance overall customer satisfaction (Xu, Akula, Srinivasan, & Manikonda,
2021). Actionable feedback analysis leads to more customer-centric service improvements. AIdriven customer feedback analysis has become a valuable tool for businesses to gain deep
insights into customer sentiments and opinions. With the ability to process vast amounts of
20
unstructured data, AI technologies, such as sentiment analysis, provide valuable feedback
analysis that helps organizations understand customer perceptions and preferences more
effectively.
The researchers conclude that AI-powered customer feedback analysis is a powerful
tool that enables businesses to gain actionable insights into customer sentiments and
preferences. By using sentiment analysis and other AI-driven techniques, organizations can
identify areas for improvement, tailor their offerings to meet customer needs, and provide
personalized and proactive customer support. Implementing data-driven improvements based
on customer feedback leads to more customer-centric service and enhances overall customer
satisfaction.
According to Friggeri, Adamic, Eckles, & Cheng, 2014, Customer Engagement on
Social Media influences customer satisfaction. The better the engagement relationship, the
greater the satisfaction derived by the customer. AI-driven content personalization has
contributed to increased customer engagement on social media platforms. By tailoring content
to individual interests, businesses can foster deeper connections with their audience (Friggeri,
Adamic, Eckles, & Cheng, 2014). Engaging content on social media enhances brand loyalty
and customer satisfaction. AI has revolutionized customer engagement on social media by
enabling businesses to personalize content and interactions for their audience. Through
advanced algorithms and data analytics, AI can analyze user behavior, preferences, and
interests, allowing companies to deliver highly relevant and engaging content on social media
platforms.
Customer Experience Management has been affirmed to have a great impact on
customer satisfaction. Nunan & Di Domenico, 2020, opine that AI-driven customer experience
management has been found to enhance customer engagement and satisfaction. Providing
personalized and proactive customer service through AI results in positive customer
21
experiences (Nunan & Di Domenico, 2020). A customer-centric approach to AI adoption
improves customer satisfaction. AI-driven customer experience management has emerged as a
powerful strategy for businesses to enhance customer engagement and satisfaction. By
leveraging AI technologies, companies can provide personalized and proactive customer
service, leading to positive and memorable customer experiences.
The researchers conclude that AI-driven customer experience management has become
a game-changer for businesses looking to enhance customer engagement and satisfaction.
Personalized interactions, proactive support, seamless omnichannel experiences, and efficient
issue resolution are some of the key benefits of AI adoption. By leveraging AI technologies for
predictive analytics, feedback analysis, and continuous improvement, businesses can create
memorable and customer-centric experiences for their customers, leading to increased loyalty,
and long-term success, and milestone customer satisfaction.
In Healthcare Services, AI has a significant impact on customer satisfaction. Wang, Yu,
Wei, & Zhang, 2020 reveals that AI-powered healthcare services, such as chatbots and
telemedicine, have positively impacted patient satisfaction. Patients appreciate the accessibility
and convenience of AI-driven healthcare interactions (Wang, Yu, Wei, & Zhang, 2020). AIenabled healthcare services enhance patient experiences and outcomes. AI has made significant
strides in transforming healthcare services, offering innovative solutions that positively impact
patient satisfaction and outcomes. Two key areas where AI has demonstrated considerable
potential are chatbots and telemedicine.
AI-powered chatbots can triage patient symptoms and provide preliminary assessments,
helping patients determine whether they require immediate medical attention or if self-care
measures are sufficient. This reduces unnecessary emergency room visits and enhances patient
confidence in managing their health concerns. Also, AI plays a significant role in facilitating
telemedicine and remote consultations. AI-driven algorithms can aid in diagnosing medical
22
images, such as X-rays and MRIs, providing faster and more accurate assessments. This
accelerates the diagnostic process, expediting treatment plans and reducing patient anxiety.
23
CHAPTER THREE
3.0
Research Method
This chapter presents and describes the totality of the research methodology employed
for the study. It provided a procedural outline for conducting this research work by
systematically investigating relevant variables of interest. The chapter focuses on the research
design, population, sampling size, sampling technique, the instrument for data collection,
validity and reliability of the instrument, the data collection procedure, and the data analysis
method.
3.1
Research Design
A descriptive survey research design is employed for this study. Descriptive research
aims to accurately and systematically describe a population, situation, or phenomenon
(McCombes, 2023). The method was chosen because of the nature of the research, which
involves collecting respondents’ views and avoiding manipulating variables.
A descriptive research method is suitable for this study because it allows the researcher
to record what was collected so that information obtained from a representative population
sample is adequately analyzed. This helps to minimize errors and enhance reasonable
interpretation of the results.
3.2
Population of the Study
This study focuses on a group of technologically adept individuals, primarily
comprising those born and raised in the 21st century. The participants within this population
fall between the ages of eighteen (18) and sixty-five (65) and come from diverse organizations
and businesses.
3.3
Samples and Sampling Techniques
The study sample comprised eighty (80) individuals across diverse sectors, businesses,
and organizations, including Information Technology, Healthcare and Life Sciences, Finance
24
and Banking, Retail and E-commerce, Manufacturing and Industry, Education, Government,
and Public Sector. The sample was chosen to specifically target individuals who have access
to and utilize Artificial Intelligence (AI) and its services, focusing on those involved in AIoriented businesses and organizations. The characteristics of the sample are represented in
Table One (1).
3.4
Instrument for Data Collection
The instrument for data collection in this study is a structured questionnaire vetted and
approved by the supervisor. The items of the questionnaires were divided into parts A and B.
Part A comprised demographic data of the respondents. Part B represents the five research
questions of the study. Section A – E respectively contains questions on the level of prevalence
of AI and corresponding technologies in today’s businesses and organizations; the advantage
of AI and human efforts in today’s businesses and organizations; factors impeding customer
acceptance of AI’s services; roles of AI-driven customer service interactions, including
response time and issue resolution, in shaping customer satisfaction and the role of customer
education and understanding of AI play in shaping their satisfaction and acceptance of AIdriven solutions.
3.5
Validity and Reliability of the Instrument
Validity is the degree to which a tool or an instrument measure what it is expected to
measure (Sukumar, 2023). To assess the validity and reliability of the questionnaire, a pilot test
was conducted and the responses were analyzed for reliability. The questionnaire as an
instrument for data collection was also submitted to the project Supervisor to confirm the
contents and face validity of the instrument. The tool was also examined for coverage, clarity
of wording, length, and format.
25
Table 1: Characteristics of the Sample
Parameter
Group
Age Group
18-24 years
25-34 years
35-44 years
45-54 years
Gender
Male
Female
Educational
Secondary
Level
Bachelor’s degree
Master's degree
Prefer not to say
Employment Employed
Status
Unemployed
Student
Self-employed
Industry
Information Technology
Healthcare and Life Sciences
Finance and Banking
Retail and E-commerce
Manufacturing and Industry
Education
Other
Missing Factor
Types of AI
Natural Language Processing (NLP)
application
Machine Learning and Predictive Analytics
Robotics and Automation
Computer Vision
Virtual Assistants and Chatbots
Recommendation Systems
Data Analytics and Insights
Other
None
The sector
Information Technology and Software
that AI has
Healthcare and Life Sciences
the most
Finance and Banking
significant
Retail and E-commerce
adoption
Manufacturing and Industry
Customer Service and Support
Source: Field Survey, 2023
Frequency
11
30
8
1
30
20
22
60
16
2
60
40
(%)
27
21
2
28
5
15
2
15
9
5
5
6
3
6
1
7
14
11
7
27
5
18
1
3
22
4
4
7
5
8
54
42
4
56
10
30
4
30
18
10
10
12
6
12
2
7.6
15
11.8
7.6
29
5.4
19.4
1
3.2
44
8
8
14
10
16
Reliability (r) refers to the stability of the measuring instrument used and its consistency
over time. It is the consistency at which the research instrument or tool measures what it is
intended to measure when applied on several occasions (Sürücü & Maslakçı, 2020). The
26
instrument’s reliability presented to the respondents was confirmed through Cronbach’s Alpha
with r = 0.874 for the questionnaire.
3.6
Procedure of Data Collection
Data was collected and used for this project work. To ensure accuracy and speed, the
data collection was conducted online with the help of Qualtrics survey form. During data
collection, the questionnaires were properly checked to determine whether they would be
acceptable; this included checking the instrument for completeness and accuracy. Data were
edited to facilitate good data analysis; this included examining the collected data to detect
errors and omissions and correct these, when possible, even before collection from respondents.
3.7
Method of Data Analysis
This project used simple percentages to bring out reliable inferences for decision-
making. The data was encoded and analyzed utilizing the Statistical Package for Social Science
(SPSS) version 21.0.
27
CHAPTER FOUR
4.0
DATA ANALYSIS AND DISCUSSION OF FINDINGS
This study investigates AI’s impact on customer satisfaction. This chapter covers data
presentation, data analysis, and discussion of findings. Valid inferences are deduced and
presented based on simple percentages from the data gathered.
4.1
Data Analysis
Research Question 1: What is the level of prevalence of AI and corresponding technologies in
today’s businesses and organizations?
Table 2 shows respondents’ responses to the prevalence of AI and corresponding technologies
in today’s businesses and organizations.
Table 2 shows the percentage of the respondents’ responses on the prevalence of AI
and corresponding technologies in today’s businesses and organizations in order of importance
based on the respondents’ responses. The responses from the table revealed that AI and its
corresponding technologies have a high degree of prevalence in today’s businesses and
organizations. However, the statement, “Artificial Intelligence (AI) and related technologies in
business settings are widespread and generally in use” was the first in rank with the highest
cumulative frequency of 90 percent. The Statements “I frequently encounter the use of AI or
AI-related technologies in the businesses or organizations I interact with” and “Does AI
adoption Significantly improve the overall productivity of businesses and organizations?”
came second in rank with 84 percent cumulative frequency. The statements “I frequently use
AI-powered products or services provided by businesses personally” and “Businesses
communicate the benefits of AI technologies to their customers excellently” came fourth and
fifth in rank with 78 and 74 percent cumulative frequencies respectively.
28
Table 2:
8
9
Simple Percentage responses on the Prevalence of AI and corresponding
technologies in today’s businesses and organizations.
SA
A
Cum
D
SD Cum MF Rank
Parameters
Freq Freq
A
Freq Freq
D
Freq
(%) (%) Freq (%) (%) Freq
%
(%)
(%)
Artificial Intelligence
25
20
45
4
4 (8) 1
1st
(AI) and related
(50) (40) (90) (8)
(2)
technologies in
business settings are
widespread and
generally in use
I frequently encounter
the use of AI or AIrelated technologies in
the businesses or
organizations I interact
with
22
(44)
20
(40)
42
(84)
4
(8)
1
(2)
5
(10)
3
(6)
2nd
10 Does AI adoption
19
Significantly improve
(38)
the overall productivity
of businesses and
organizations?
23
(46)
42
(84)
7
(14)
-
7
(14)
1
(2)
2nd
11 I frequently use AIpowered products or
services provided by
businesses personally
14
(28)
25
(50)
39
(78)
7
(14)
4
(8)
11
(22)
-
4th
12 Businesses
communicate the
benefits of AI
technologies to their
customers excellently
Source: Field Survey, 2023
11
(22)
26
(52)
37
(74)
8
(16)
5
(10)
13
(26)
-
5th
Table 3 shows the descriptive statistics for research question 1. The prevalence of AI
and its corresponding technologies in today’s businesses and organizations. The table reveals
mean factor of 18.2 and 22.8 for Strongly Agree and Agree with the standard deviation of 5.72
and 2.77 respectively. The table reveals 205 sum total for the level of agreement, which affirms
the prevalence of AI and its corresponding technologies in today’s businesses and
organizations.
29
Table 3:
Descriptive Statistics table for research question 1
SA
A
D
SD
MF
Mean
18.2
22.8
6
2
1
Standard Error
2.557342 1.240967 0.83666 1.048809 0.547723
Median
19
23
7
1
1
Mode
#N/A
20
4
0
1
Standard Deviation 5.718391 2.774887 1.870829 2.345208 1.224745
Sample Variance
32.7
7.7
3.5
5.5
1.5
Kurtosis
-1.75097 -2.70366 -2.89796
-2.6281
2
Skewness
-0.17274 -0.00936
-0.3818 0.581456 1.360828
Range
14
6
4
5
3
Minimum
11
20
4
0
0
Maximum
25
26
8
5
3
Sum
91
114
30
10
5
Count
5
5
5
5
5
Source: Field Survey, 2023
Likewise, the responses to research question one is also presented in Figure 1 to reveal
the level of agreement to each parameter as presented in Table 2.
Figure 1:
Bar chart showing the frequency distribution for each parameter on the
prevalence of AI and its corresponding technologies in today’s businesses and
organizations.
I frequently use AI-powered products
or services provided by businesses
personally
I frequently encounter the use of AI or
AI-related technologies in the businesses
or organizations I interact with
30
30
20
20
10
10
0
0
SA
A
D
SD
SA
MF
Figure 1.1
A
D
SD
MF
Figure 1.2
Does Ai adoption Significantly improve
the overall productivity of businesses
and organizations
Businesses communicate the benefits
of AI technologies to their customers
excellently
30
30
20
20
10
10
0
0
SA
Figure 1.3
A
D
SD
SA
MF
Figure 1.4
30
A
D
SD
MF
Artificial Intelligence (AI) and related
technologies in business settings are wide
spread and generally in use
30
20
10
0
SA
A
D
SD
MF
Figure 1.5
Therefore, it is evident from the above responses that this research work can conclude
that AI and its corresponding technology have found significant adoption and prevalence in
today’s businesses and organizations.
Research Question 2: What is the advantage of AI and human efforts in today’s businesses
and organizations?
Table 4 shows the percentage of the respondents’ responses on the Advantages of AI
and human efforts in today’s businesses and organizations in order of importance based on the
respondents’ responses. The responses from the table revealed that AI and human effort work
in partnership to benefit today’s businesses and organizations. The cumulative agreement
percentage ranges from 68 to 92 percent. However, the statement, “Integration of AI and human
efforts in businesses will evolve in the nearest future and AI will take over most tasks, reducing
human involvement” was the first in rank with the highest cumulative frequency of 92 percent.
The Statements “Businesses and organizations integrate AI with human efforts to achieve
optimal results?” and “Businesses leverage the unique strengths of human efforts in
conjunction with AI technologies rather than relying over AI technologies alone” came second
in rank with 90 percent cumulative frequency. The statements “Employees in businesses and
organizations generally perceive AI as a tool to complement their effort” and “Human efforts
31
excel over AI in businesses and organizations” came fourth and fifth in rank with 78 and 68
percent cumulative frequencies respectively.
Table 4:
Simple Percentage Responses on the Advantage
today’s businesses and organizations
SA
A Cum D
SD
Parameters
Freq Freq
A
Freq Freq
(%) (%) Freq (%) (%)
(%)
13 Integration of AI and
28
18
46
3
human efforts in
(56) (36) (92) (6)
businesses will evolve
shortly and AI will
take over most tasks,
reducing human
involvement
14 Businesses and
23
22
45
4
organizations integrate (46) (44) (90) (8)
AI with human efforts
to achieve optimal
results.
15 Businesses leverage
26
19
45
3
1
the unique strengths of (52) (38) (90) (6)
(2)
human efforts in
conjunction with AI
technologies rather
than relying over AI
technologies alone.
16 Employees in
19
20
39
7
3
businesses and
(38) (40) (78) (14) (6)
organizations
generally perceive AI
as a tool to
complement their
effort
17 Human efforts excel
11
23
34
15
over AI in businesses
(22) (46) (68) (30)
and organizations
Source: Field Survey, 2023
of Ai and human efforts in
Cum MF Rank
D
Freq
Freq %
(%)
3 (6) 1
1st
(2)
4 (8) 1
(2)
2nd
4 (8) 1
(2)
2nd
10
(20)
1
(2)
4th
15
(30)
1
(2)
5th
Table 5 shows the descriptive statistics for research question 2. The advantages of AI
and human efforts in today’s businesses and organizations. The table reveals mean factor of
21.4 and 20.4 for Strongly Agree and Agree with the standard deviation of 3.01 and 0.93
respectively. The table reveals 209 sum total for the agreement level,
32
Table 5:
Descriptive Statistics table for research question 2
SA
A
D
SD
MF
Mean
21.4
20.4
6.4
0.8
1
Standard Error
3.009983389 0.927362 2.271563 0.583095
0
Median
23
20
4
0
1
Mode
#N/A
#N/A
3
0
1
Standard Deviation
6.730527468 2.073644 5.07937 1.30384
0
Sample Variance
45.3
4.3
25.8
1.7
0
Kurtosis
0.578775785 -1.96322 2.836668 2.66436 #DIV/0!
Skewness
-1.024622108 0.235514 1.729141 1.714392 #DIV/0!
Range
17
5
12
3
0
Minimum
11
18
3
0
1
Maximum
28
23
15
3
1
Sum
107
102
32
4
5
Count
5
5
5
5
5
Source: Field Survey, 2023
which affirms that there are advantages of AI and human effort in today’s businesses and
organizations.
Likewise, the responses to research question two (2) is also presented in Figure 2 to
reveal the level of agreement to each parameter as presented in Table 4.
Figure 2:
Bar chart showing the frequency distribution for each parameter on the
Advantage of AI and human efforts in today’s businesses and organizations.
Figure 2.1
Figure 2.2
Businesses leverage the unique
strengths of human efforts in
conjunction with AI technologies
rather than relying over AI…
Integration of AI and human efforts in
businesses will evolve in the nearest
future and AI will take over most tasks,
reducing human involvement
40
40
20
20
0
0
SA
A
D
SD
SA
MF
33
A
D
SD
MF
Businesses and organizations integrate AI
with human efforts to achieve optimal
results
Employees in businesses and
organizations generally perceive AI
as a tool to complement their effort
30
30
20
20
10
10
0
0
SA
A
D
SD
MF
SA
Figure 2.3
A
D
SD
MF
Figure 2.4
Human efforts excel over AI in businesses
and organizations
25
20
15
10
5
0
SA
A
D
SD
MF
Figure 2.5
Therefore, it is evident from the above responses that this research work can conclude
that AI and human effort in today’s businesses and organizations are more advantageous
compared to human effort or AI only.
Research question 3: What are the factors impeding customer acceptance of Ai’s services?
Table 6 shows the respondents’ responses on factors impeding customer acceptance of Ai’s
services.
Table 6 shows the percentage of the respondents’ responses on the factors impeding
customer acceptance of Ai’s services in today’s businesses and organizations in order of
importance based on the respondents’ responses. The responses from the table revealed that
there are factors that impede customers' acceptance of AI services in
34
Table 6:
Factors Impeding Customer Acceptance of AI’s Services
SA
A
Cum
Freq Freq Freq
%
%
%
18 AI's understanding of 18
22
40
your language and (36) (44) (80)
intent
during
interactions
19 Inadequate
18
20
38
transparency trust in
(36) (40) (76)
AI systems and AIpowered services or
products
20 Poor communication
19
19
38
of AI usage in
(38) (38) (76)
business
services/products to
their customers
21 AI errors impact trust 15
22
37
and confidence in
(30) (44) (74)
using AI-powered
services or products
22 AI-powered services
7
20
27
often provide
(14) (40) (54)
incorrect or irrelevant
information
Source: Field Survey, 2023
Parameters
D
SD Cum MF Rank
Freq Freq Freq Freq
%
%
%
%
8
8
2
1st
(16)
(16) (4)
11
(22)
-
11
(22)
1
(2)
2nd
11
(22)
-
11
(22)
1
(2)
2nd
11
(22)
-
11
(22)
2
(4)
4th
19
(38)
3
(6)
22
(44)
1
(2)
5th
today’s businesses and organizations. The cumulative agreement percentage ranges from 54 to
80 percent. However, the statement, “Inadequate transparency trust in AI systems and AIpowered services or products” was the first in rank with the highest cumulative frequency of
80 percent. The Statements “Poor communication of AI usage in business services/products to
their customers” and “AI-powered services often provide incorrect or irrelevant information”
came second in rank with 76 percent cumulative frequency. The statements “AI errors impact
trust and confidence in using AI-powered services or products” and “AI's understanding of
your language and intent during interactions” came fourth and fifth in rank with 74 and 54
percent cumulative frequencies respectively.
Table 7 shows the descriptive statistics for research question three (3). Factors that
35
Table 7: Descriptive Statistics table for research question 3
SA
A
D
SD
MF
Mean
15.4
20.6
12
0.6
1.4
Standard Error
2.204540769
0.6 1.843909
0.6 0.244949
Median
18
20
11
0
1
Mode
18
20
11
0
1
Standard Deviation 4.929503018 1.341641 4.123106 1.341641 0.547723
Sample Variance
24.3
1.8
17
1.8
0.3
Kurtosis
3.088451964 -2.40741 3.50519
5 -3.33333
Skewness
-1.77732255 0.165635 1.640682 2.236068 0.608581
Range
12
3
11
3
1
Minimum
7
19
8
0
1
Maximum
19
22
19
3
2
Sum
77
103
60
3
7
Count
5
5
5
5
5
Source: Field Survey, 2023
Impedes Customer Acceptance of AI’s Services in today’s businesses and organizations. The
table reveals mean factor of 15.4 and 20.6 for Strongly Agree and Agree with the standard
deviation of 2.21 and 0.6 respectively. The table reveals 180 sum total for the level of
agreement, which affirms that there are several factors that impedes customers’ acceptance of
AI and its corresponding technologies in today’s businesses and organizations.
Also, Figure 3 presents the respondents’ responses to each parameter in bar chart to
reveal the respondent’s agreement to the factors that impedes customers’ acceptance of AI
services and its corresponding technologies in today’s businesses and organizations.
Therefore, it is evident from the above responses that this research work can conclude
that there are factors that impede customer acceptance of AI’s services in today’s businesses
and organizations.
36
Figure 3:
Bar chart showing the frequency distribution for each parameter on the Factors
Impeding Customer Acceptance of AI’s Services
Inadequate transparency trust in AI
systems and AI-powered services or
products
Poor communication of AI usage in
business services/products to their
customers
30
20
15
20
10
10
5
0
0
SA
A
D
SD
MF
SA
Figure 3.1
A
D
SD
MF
Figure 3.2
AI-powered services often provide
incorrect or irrelevant information
AI errors impact trust and confidence in
using AI-powered services or products
30
30
20
20
10
10
0
0
SA
A
D
SD
MF
SA
Figure 3.3
A
Figure 3.4
AI's understanding of your language and
intent during interactions
25
20
15
10
5
0
SA
A
D
SD
Figure 3.5
37
MF
D
SD
MF
Research Question 4: What are the roles of AI-driven customer service interactions, including
response time and issue resolution, in shaping customer satisfaction?
Table 8:
Roles of AI-driven customer service interactions, including response time and issue
resolution, in shaping customer satisfaction
SA
A Cum D
SD Cum MF Rank
Parameters
Freq Freq Freq Freq Freq Freq Freq
%
%
%
%
%
%
%
23 AI systems respond faster
26
18
44
6
6
1st
to inquiries compared to
(52) (36) (88) (12)
(12)
human effort.
24 Issues were effectively
11
24
35
7
3
10
5
2nd
resolved by an AI-driven
(22) (48) (70) (14) (6)
(20) (10)
customer support system
25 AI-driven customer service 19
16
35
11
3
14
1
2nd
interactions have improved (38) (32) (70) (22) (6)
(28) (2)
the overall efficiency of
issue resolution
26 AI-driven interactions
10
19
29
14
3
17
4
4th
adequately understand and (20) (38) (58) (28) (6)
(34) (8)
respond to language and
intent
27 Issue resolution
6
19
25
14
8
22
3
5th
capabilities of AI-driven
(12) (38) (50) (28) (16) (44) (6)
systems are better
compared to human agents
Source: Filed Survey, 2023
Table 8 shows the percentage of the respondents’ responses on the roles of AI-driven
customer service interactions, including response time and issue resolution, in shaping
customer satisfaction in order of importance based on the respondents’ responses. The
responses from the table revealed that AI-driven customer service helps today’s businesses and
organizations in shaping customer satisfaction. The cumulative agreement percentage ranges
from 50 to 88 percent. However, the statement, “AI systems respond faster in inquiries
compared to human effort” was the first in rank with the highest cumulative frequency of 88
percent. The Statements “Issues were effectively resolved by an AI-driven customer support
system” and “AI-driven customer service interactions have improved the overall efficiency of
issue resolution” came second in rank with 70 percent cumulative frequency. The statements
38
“AI-driven interactions adequately understand and respond to language and intent” and “Issue
resolution capabilities of AI-driven systems is better compared to human agents” came fourth
and fifth in rank with 58 and 50 percent cumulative frequencies respectively.
Table 9:
Descriptive Statistics table for research question 4
SA
A
D
SD
MF
Mean
14.4
19.2
10.4
3.4
2.6
Standard Error
3.586084215 1.319091 1.691153 1.28841 0.927362
Median
11
19
11
3
3
Mode
#N/A
19
14
3
#N/A
Standard Deviation
8.018728079 2.949576 3.781534 2.880972 2.073644
Sample Variance
64.3
8.7
14.3
8.3
4.3
Kurtosis
-0.731480787 2.532699 -2.83779 2.550443 -1.96322
Skewness
0.760467018 1.235323 -0.23855 1.007859 -0.23551
Range
20
8
8
8
5
Minimum
6
16
6
0
0
Maximum
26
24
14
8
5
Sum
72
96
52
17
13
Count
5
5
5
5
5
Source: Field Survey, 2023
Table 9 shows the descriptive statistics for research question four (4). Roles of AIdriven customer service interactions, including response time and issue resolution, in shaping
customer satisfaction. The table reveals mean factor of 14.4 and 19.2 for Strongly Agree and
Agree with the standard deviation of 3.59 and 1.32 respectively. The table reveals 168 sum
total for the level of agreement, which affirms that AI-driven customer service interactions play
several roles in shaping customers satisfaction and the roles include quick response time,
effective issue resolution among others.
Similarly, Figure 4 presents the respondents’ responses to each parameter in bar chart
to reveal the respondents’ level of agreement to the roles of AI-driven customer
39
Figure 4:
Bar chart showing the frequency distribution for each parameter on the roles of
AI-driven customer service interactions, including response time and issue
resolution, in shaping customer satisfaction.
AI-driven customer service
interactions have improved the overall
efficiency of issue resolution
AI systems responds faster in inquiries
compared to human effort
30
20
20
10
10
0
0
SA
A
D
SD
SA
MF
Figure 4.1
A
D
SD
MF
Figure 4.2
Issues were effectively resolved by an
AI-driven customer support system
AI-driven interactions adequately
understand and respond to language
and intent
30
20
20
10
10
0
0
SA
A
D
SD
SA
MF
Figure 4.3
A
Figure 4.4
Issue resolution capabilities of AI-driven
systems is better compared to human
agents
20
15
10
5
0
SA
A
D
Figure 4.5
40
SD
MF
D
SD
MF
service interactions in shaping customer satisfaction in today’s businesses and organizations.
Therefore, it is evident from the above responses that this research work can conclude
that AI-driven customer service interactions, including response time and issue resolution, help
in shaping customer satisfaction in today’s businesses and organizations.
Research Question 5: What is the role of customer education and understanding of AI play in
shaping their satisfaction and acceptance of AI-driven solutions?
Table 10 shows the percentage of the respondents’ responses on the Role of
customer education and understanding of AI play in shaping their satisfaction and acceptance
of AI-driven solutions in order of importance based on the respondents’ responses. The
responses from the table revealed that customer education and understanding about AI play
significant roles in shaping customer satisfaction and acceptance of AI-driven solutions. The
cumulative agreement percentage ranges from 72 to 90 percent. However, the statements,
“Businesses and organizations must educate their customers about the AI-driven solutions they
offer” and “Customer education about AI can dispel common misconceptions and fears about
AI” were the first in rank with the highest cumulative frequency of 90 percent. The Statement
“Lack of understanding about AI hinders customer acceptance of AI-driven solutions” came
third in rank with 88 percent cumulative frequency. The Statement “It is very likely for
customers to trust and use AI-driven solutions after receiving proper education about how they
work” came fourth in rank with a cumulative frequency of 84 percent. The statements
“Education will increase the rate of effectiveness of AI-driven businesses” and “Businesses
generally prioritize customer education and understanding of AI-driven solutions” came fifth
and sixth in rank with 82 and 72 percent cumulative frequencies respectively.
41
Table 10: Role of customer education and understanding of AI play in shaping their
satisfaction and acceptance of AI-driven solutions
SA
A
Cum
D
SD Cum MF Rank
Parameters
Freq Freq Freq Freq Freq Freq Freq
%
%
%
%
%
%
%
28 Businesses and
30
15
45
3
1
4 (8) 1 (2) 1st
organizations must
(60) (30) (90) (6)
(2)
educate their
customers about the
AI-driven solutions
they offer
29 Customer education
22
23
45
3
2
5
1st
about AI can dispel
(44) (46) (90) (6)
(4)
(10)
common
misconceptions and
fears about AI
30 Lack of
26
18
44
1
3
4 (8) 2 (4) 3rd
understanding about
(52) (36) (88) (2)
(6)
AI hinders customer
acceptance of AIdriven solutions
31 It is very likely for
21
21
42
4
3
7
1 (2) 4th
customers to trust and (42) (42) (84) (8)
(6)
(14)
use AI-driven
solutions after
receiving proper
education about how
they work
32 Education will
22
19
41
4
3
7
2 (4) 5th
increase the rate of
(44) (38) (82) (8)
(6)
(14)
effectiveness of AIdriven businesses
33 Businesses generally 16
20
36
12
1
13
1 (2) 6th
prioritize customer
(32) (40) (72) (24) (2)
(26)
education and
understanding of AIdriven solutions
Source: Filed Survey, 2023
Table 11 shows the descriptive statistics for research question five (5). Role of customer
education and understanding of AI play in shaping their satisfaction and acceptance of AIdriven solutions. The table reveals mean factor of 22.83 and 19.33 for Strongly Agree and
Agree with the standard deviation of 4.75 and 2.73 respectively. The table reveals 253 sum
total for the level of agreement, which affirms that customer education and understanding of
42
AI play major roles in shaping customer satisfaction and acceptance of AI-driven solutions in
today’s business and organization.
Table 11:
Descriptive Statistics table for research question 5
SA
A
D
SD
Mean
22.83333333 19.33333
4.5 2.166667
Standard Error
1.939358428 1.115547 1.565248 0.401386
Median
22
19.5
3.5
2.5
Mode
22
#N/A
3
3
Standard Deviation 4.750438576 2.73252 3.834058 0.983192
Sample Variance
22.56666667 7.466667
14.7 0.966667
Kurtosis
0.528157721 0.585937 4.51895 -2.39001
Skewness
0.205531828 -0.43458 1.980105 -0.45594
Range
14
8
11
2
Minimum
16
15
1
1
Maximum
30
23
12
3
Sum
137
116
27
13
Count
6
6
6
6
Source: Field Survey, 2023
MF
1.166667
0.307318
1
1
0.752773
0.566667
-0.10381
-0.31257
2
0
2
7
6
Figure 5 pictorially reveals the respondents’ responses to each parameter which also
reveals the respondent’s agreement that customer education and understanding of AI play
significant roles in shaping customer satisfaction and acceptance of AI-driven solutions in
today’s business and organization.
Figure 5:
Bar chart showing the frequency distribution for each parameter on the role of
customer education and understanding of AI play in shaping their satisfaction
and acceptance of AI-driven solutions.
It is essential that businesses and
organizations educate their customers
about the AI-driven solutions they offer
Customer education about AI can
dispel common misconceptions and
fears about AI
40
30
30
20
20
10
10
0
0
SA
A
D
SD
SA
MF
Figure 5.1
A
D
SD
Figure 5.2
43
MF
It is very likely for customers to trust and
use AI-driven solutions after receiving
proper education about how they work
Lack of understanding about AI
hinders customer acceptance of AIdriven solutions
40
40
20
20
0
0
SA
A
D
SD
MF
SA
Figure 5.2
A
D
SD
MF
Figure 5.3
Education will increase the rate of
effectiveness of AI-driven businesses
Businesses generally prioritize
customer education and
understanding of AI-driven solutions
30
50
20
10
0
0
SA
A
D
SD
MF
SA
Figure 5.5
A
D
SD
MF
Figure 5.6
Therefore, it is evident from the above responses that this research work can conclude
that customer education and understanding of AI play a significant role in shaping customers’
satisfaction and acceptance of AI-driven solutions in today’s businesses and organizations.
4.2
Discussion of Findings
Research question 1 verified the level of prevalence of AI and corresponding
technologies in today’s businesses and organizations. Ninety percent of respondents agreed
that Artificial Intelligence (AI) and related technologies in business settings are widespread
and generally in use. This response agrees with the opinion of Varian 2014 when he stated that
44
AI adoption has accelerated due to advancements in technology, increased data availability,
and the potential to enhance operational efficiency and customer experiences. AI and its
corresponding technologies are now being widely adopted and used in various businesses.
Provost & Fawcett gave an example of Machine Learning algorithms which have been
employed in diverse applications, such as customer segmentation, predictive analytics, and
recommendation systems, enhancing personalized user experiences.
Another view of the respondents that revealed the level of prevalence of AI and its
corresponding technologies is that most respondents claimed that they frequently encounter the
use of AI or AI-related technologies in the businesses or organizations they interact with and
agreed that AI adoption significantly improves the overall productivity of businesses and
organizations. The respondents identified that they have encountered at least one of the
following AI applications Natural Language Processing (NLP), Machine Learning and
Predictive Analytics, Robotics and Automation, Computer Vision, Virtual Assistants and
Chatbots, Recommendation Systems, and Data Analytics and Insights as they interact with
businesses and organizations. Although, Virtual Assistants and Chatbots were identified by the
respondents to be the most frequently encountered AI application. This response gains support
from Liao et al., 2021 who concluded that AI-enabled chatbots and virtual assistants can
respond to queries quickly, guaranteeing clients get assistance immediately and cutting down
on wait times and thereby improving the overall productivity of the businesses and
organizations.
In the same vein, this research work confirmed that AI and its corresponding
technologies prevail in today’s businesses and organizations. The responses revealed that the
respondents frequently use AI-powered products or services provided by businesses and
organizations which is evident in the characteristics of the respondents as the respondents
affirm to have used one or more AI-powered products. The respondents also claim that
45
businesses communicate the benefits of AI technologies to their customers excellently which
can also contribute to the prevalence of AI and its corresponding technologies. The respondents
gain support from Provost & Fawcett, 2013 conclusion. The researchers conclude that
Customer education plays a crucial role in the successful adoption and acceptance of AI
technologies. As businesses integrate AI-driven solutions into their products and services, it is
essential to educate customers about AI's capabilities, benefits, and limitations.
Therefore, this research work concluded that AI and its corresponding technologies has
found their way into today’s business and organizations. These technologies are being used
widely to shape and reshape the business sector and apply them to various business endeavours
ranging from Information Technology and Software, Healthcare and Life Sciences, Finance
and Banking, Retail and E-commerce, Manufacturing and Industry, Customer Service and
Support, among many others, although some people are yet to still embrace the opportunity AI
brings.
Research question 2 explores the advantages of AI and human efforts in today’s
businesses and organizations. The percentage cumulative frequency from Table 3 and bar
frequency from Figure 2 revealed that there are vast advantages of AI and human effort in
today’s businesses and organizations. The statement “Integration of AI and human efforts in
businesses will evolve in the nearest future and AI will take over most tasks, reducing human
involvement” was first in rank with ninety-two percent cumulative frequency under agree. This
response gains support from the opinions of Varian 2014. Varian claims that in today’s
businesses and organizations, the integration of Artificial Intelligence (AI) with human efforts
drives innovation and efficiency as AI augments human capabilities, improving decisionmaking, productivity, and customer satisfaction. Likewise, the statements “Businesses and
organizations integrate AI with human efforts to achieve optimal results and “Businesses
leverage the unique strengths of human efforts in conjunction with AI technologies rather than
46
relying over AI technologies alone” were the second in rank. These statements imply that
businesses and organizations combine both AI and its technologies with human efforts to
achieve an optimal result. The respondents' statement gains support from Davenport, 2018 and
Sutskever et al., 2014 as they claim that AI-driven automation streamlines repetitive tasks,
freeing up human resources for higher-value activities.
Also, the respondents claim that “Employees in businesses and organizations generally
perceive AI as a tool to complement their effort also complement the claim that AI and human
effort can be maximized in businesses and organizations to enhance business productivity.
Albeit, the respondents affirm that despite the numerous benefits that AI can provide, Human
efforts excel over AI in businesses and organizations but affirm that the partnership between
AI and humans optimizes productivity, allowing employees (humans) to allocate their time and
skills effectively and this affirmation gains support from Davenport, 2018 and Sutskever et al.,
2014.
Research question 3 attended Factors Impeding Customer Acceptance of AI’s Services.
The statement with the highest frequency from the responses is that AI's understanding of your
language and intent during interactions. This means that respondents fear that AI might not be
able to understand their language and intention due to the fact that AI lacks the emotion and
lack human feeling. Thus, it impedes customer acceptance of AI services. Other factors impede
customer acceptance of AI services, limiting its full potential in various industries the responses
came second highest are “Inadequate transparency trust in AI systems and AI-powered services
or products” and “Poor communication of AI usage in business services/products to their
customers.” These statements gain support from Lipton, 2016. Lipton claims that one key
barrier to impeding Customer acceptance of AI’s services is the lack of transparency and
explainability in AI decision-making processes. The statements “AI errors impact trust and
confidence in using AI-powered services or products” and “AI-powered services often provide
47
incorrect or irrelevant information” were 4th and 5th in rank respectively but the respondents
still claim that the statements are part of the factors that impede customer acceptance of AI’s
services.
Thus, this research work educed that there are factors that impede customer acceptance
of Ai’s services in today’s businesses and organizations. These factors range from lack of trust,
transparency, poor communication, and generating incorrect and relevant information.
Research question 4 explores the roles of AI-driven customer service interactions,
including response time and issue resolution, in shaping customer satisfaction. The respondents
affirm that Ai-driven customer service plays important role in customer satisfaction. The
statement with the highest frequency is, “AI systems respond faster in inquiries compared to
human effort.’ The second in rank are the statements “Issues were effectively resolved by an
AI-driven customer support system” and “AI-driven customer service interactions have
improved the overall efficiency of issue resolution.” This affirmation implies that AI-driven
customer service responds faster in inquiry compared to the traditional human effort. It further
means that despite the faster response, issues were effectively resolved and there are
improvements in overall issue resolution when compared to the traditional human effort of
resolving issues. Another response that also reveals the roles of AI-driven customer services is
that the Issue resolution capabilities of AI-driven systems are better compared to human agents.
These claims from the respondents gained support from several authors. Sutskever et al., 2014
concluded that AI-powered chatbots and virtual assistants can handle a large volume of
customer queries simultaneously, reducing waiting times and improving response times. The
researchers revealed that AI-driven interactions can operate 24/7, providing round-the-clock
support to customers. This accessibility ensures that customers can get help whenever they
need it, increasing overall customer satisfaction.
48
Significantly, the respondents agree with the statement “AI-driven interactions
adequately understand and respond to language and intent” as the role of AI-driven customer
service. This response from the respondents dispels the misconception that Ai cannot
understand language and intent. Seth 2019, claims that AI-driven customer service interactions
can provide personalized experiences. By analyzing customer data and previous interactions,
AI systems can offer tailored product recommendations and assistance, making customers feel
valued and understood.
Thus, this work deduced that there are numerous roles of AI-driven customer service
interactions, including response time and issue resolution, in shaping customer satisfaction.
The roles include fast response, effective issue resolution, and improve overall efficiency and
productivity, among many others.
Research question 5 explores the role of customer education and understanding of AI
play in shaping their satisfaction and acceptance of AI-driven solutions. Two statements,
“Businesses and organizations must educate their customers about the AI-driven solutions they
offer” and “Customer education about AI can dispel common misconceptions and fears about
AI” came first in rank with the highest cumulative frequency of ninety under Agree. This
implies that the respondents agreed that education plays a major role in customers' acceptance
of AI-driven services. As businesses integrate AI-driven solutions into their products and
services, it is essential to educate customers about AI's capabilities, benefits, and limitations.
Customer education helps demystify AI, dispel misconceptions, and build trust, leading to
higher customer confidence in using AI-powered tools and services. When customers
understand how AI can add value to their interactions with a brand, they are more likely to
embrace and appreciate its implementation (Provost & Fawcett, 2013).
The respondents also agreed with the statements “Lack of understanding about AI
hinders customer acceptance of AI-driven solutions,” “It is very likely for customers to trust
49
and use AI-driven solutions after receiving proper education about how they work,” “Education
will increase the rate of effectiveness of AI-driven businesses,” and “Education will increase
the rate of effectiveness of AI-driven businesses.” This implies that the respondents claimed
that education is important in ensuring customers' acceptance of AI services. Li, 2018 work
supports the claims of the respondents. Li concluded that it is important to be transparent about
AI's limitations and potential risks. Customer education should encompass discussions about
data privacy, security, and the measures in place to protect sensitive information. This
transparency fosters customer trust, assuring them that their data is being handled responsibly.
Likewise, the responses gain support from the work of Mittelstadt et al., 2016 where the
researchers opined that customer education on AI ethics and bias is essential to address
concerns about fairness and equal treatment. Customers need to understand how AI algorithms
work, how decisions are made, and how potential biases are identified and addressed.
Thus, this work deduced that education plays a significant role in fostering
understanding and shaping customer satisfaction and acceptance of AI-driven solutions.
Organizations can employ various educational channels to inform their customers about AI,
such as websites, blogs, webinars, and interactive tutorials. Engaging and user-friendly
materials can help customers grasp AI concepts and applications more effectively.
50
CHAPTER FIVE
5.1
Conclusion
In this comprehensive study, the study investigated various facets of the prevalence and
impact of AI and related technologies in today's businesses and organizations. The research
sought to answer five critical questions, shedding light on the role of AI in shaping modern
enterprises and its implications for customer satisfaction and acceptance.
The study findings indicate that AI adoption has become widespread across industries,
with businesses and organizations of all sizes recognizing the value of AI-driven solutions.
From automating routine tasks to enhancing decision-making processes, AI technologies are
being integrated into various aspects of operations, reflecting the growing recognition of AI's
potential to drive efficiency and innovation. Therefore, it is imperative for businesses to
continue investing in AI to stay competitive in today's rapidly evolving landscape.
The research highlights the symbiotic relationship between AI and human efforts in
modern enterprises. While AI can automate repetitive tasks and provide data-driven insights,
human creativity, empathy, and critical thinking remain indispensable. It is recommended that
organizations adopt a collaborative approach, where AI augments human capabilities rather
than replacing them, to maximize the advantages of both AI and human contributions.
The study identifies several factors that hinder/impedes customer acceptance of AI
services, including concerns about privacy, security, and the fear of job displacement. To
overcome these barriers, businesses should prioritize transparent communication about data
handling, invest in robust security measures, and emphasize the role of AI in enhancing job
roles rather than replacing them. Additionally, educating customers about AI's benefits and
limitations is essential for dispelling misconceptions and fostering trust.
51
The research underscores the pivotal role of AI-driven customer service interactions in
shaping customer satisfaction. Faster response times and efficient issue resolution were found
to significantly influence customer perception. To improve customer satisfaction,
organizations should invest in AI-powered chatbots and automated support systems that can
provide quick and accurate responses. It is also crucial to ensure that human agents are available
for complex queries, combining AI's speed with human expertise.
Finally, the study emphasizes the importance of customer education and understanding
in shaping satisfaction and acceptance of AI-driven solutions. Customers who are wellinformed about AI's capabilities and limitations are more likely to trust and embrace AI-based
services. Therefore, organizations should develop educational materials and campaigns to
enhance customer awareness and provide clear information about how AI benefits them.
5.2
Recommendations
Based on our research, the following recommendations are offered:
Businesses and organizations should continue to invest in AI technologies to improve
operational efficiency, data-driven decision-making, and innovation. Ensure that AI initiatives
align with the business goals and customer needs.
There should be fostering of a collaborative work environment that will enable the
compliments of AI and human skills. Business and organizations should train employees to
work effectively alongside AI systems and emphasize the value of their unique abilities.
Business and organizations should proactively address customer concerns regarding AI,
privacy, and job displacement through transparent communication, robust security measures,
and emphasizing the augmentation of human roles.
52
Business and organizations should prioritize AI-driven customer service solutions to
provide quicker responses and efficient issue resolution. Combine AI with human agents to
deliver a seamless and personalized customer experience.
Business and organizations should develop educational materials and campaigns to
enhance customer awareness and understanding of AI's benefits and limitations. Empower
customers to make informed choices when interacting with AI-driven solutions.
53
APPENDICES
Questionnaire
PART ONE - Demographic Information
1. What is your age group?
a) 18-24 year
b) 25-34 years
e) 55-64 years
f) 65+ years
2. What is your gender?
a) Male
b) Female
c) 35-44 years
c) Non-binary
d) 45-54 years
d) Prefer not to say
3. What is your highest level of education completed?
a) Secondary School Leaving certificate or equivalent
b) Bachelor's degree
c) Master's degree d) Doctorate or professional degree e) Prefer not to say
4. What is your current employment status?
a) Employed full-time
b) Employed part-time
c) Unemployed and actively
seeking employment
d) Unemployed and not seeking employment
e) Student
f) Retired g) Self-employed
h) Prefer not to say
5. Which industry do you work in, or with which industry are you most closely associated?
a) Information Technology b) Healthcare and Life Sciences
c) Finance and Banking
d) Retail and E-commerce e) Manufacturing and Industry
f) Education g) Government and Public Sector
h) Other (please specify) ____________
i) Not applicable
6. What types of AI applications have you come across in businesses and organizations?
(Select all that apply)
a) Natural Language Processing (NLP) b) Machine Learning and Predictive Analytics
c) Robotics and Automation d) Computer Vision e) Virtual Assistants and Chatbots
f) Recommendation Systems g) Data Analytics and Insights
h) Other (please specify) ______________ i) None
7. In which sectors have you observed the most significant adoption of AI and related
technologies? (Select all that apply)
a) Healthcare and Life Sciences b) Finance and Banking c) Retail and E-commerce
d) Manufacturing and Industry e) Information Technology and Software
f) Customer Service and Support g) Other (please specify) ____________
PART TWO
SECTION A - What is the level of prevalence of AI and corresponding technologies in today’s
businesses and organizations?
SA A D SD
Parameters
8 Artificial Intelligence (AI) and related technologies in business settings
are widespread and generally in use
9 I frequently encounter the use of AI or AI-related technologies in the
businesses or organizations I interact with
54
10 Does AI adoption Significantly improve the overall productivity of
businesses and organizations?
11 I frequently use AI-powered products or services provided by
businesses personally
12 Businesses communicate the benefits of AI technologies to their
customers excellently
SECTION B - What is the advantage of AI and human efforts in today’s businesses and
organizations?
SA A D SD
Parameters
13 Integration of AI and human efforts in businesses will evolve shortly
and AI will take over most tasks, reducing human involvement
14 Businesses and organizations integrate AI with human efforts to
achieve optimal results.
15 Businesses leverage the unique strengths of human efforts in
conjunction with AI technologies rather than relying over AI
technologies alone.
16 Employees in businesses and organizations generally perceive AI as a
tool to complement their effort
Human efforts excel over AI in businesses and organizations
SECTION C - What are the factors impeding customer acceptance of Ai’s services?
18
19
20
21
22
Parameters
AI's understanding of your language and intent during interactions
Inadequate transparency trust in AI systems and AI-powered services
or products
Poor communication of AI usage in business services/products to their
customers
AI errors impact trust and confidence in using AI-powered services or
products
AI-powered services often provide incorrect or irrelevant information
SA A D SD
SECTION D - What are the roles of AI-driven customer service interactions, including
response time and issue resolution, in shaping customer satisfaction?
SA A D SD
Parameters
23 AI systems respond faster to inquiries compared to human effort.
24 Issues were effectively resolved by an AI-driven customer support
system
25 AI-driven customer service interactions have improved the overall
efficiency of issue resolution
26 AI-driven interactions adequately understand and respond to
language and intent
27 Issue resolution capabilities of AI-driven systems are better
compared to human agents
55
SECTION E - What is the role of customer education and understanding of AI play in shaping
their satisfaction and acceptance of AI-driven solutions?
Parameters
SA A D SD
28 Businesses and organizations must educate their customers about
the AI-driven solutions they offer
29 Customer education about AI can dispel common misconceptions
and fears about AI
30 Lack of understanding about AI hinders customer acceptance of
AI-driven solutions
31 It is very likely for customers to trust and use AI-driven solutions
after receiving proper education about how they work
32 Education will increase the rate of effectiveness of AI-driven
businesses
33 Businesses generally prioritize customer education and
understanding of AI-driven solutions
56
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