"Exploring the Role of Artificial Intelligence in Improving Passenger Satisfaction in the Airline Industry: An Analysis of Customer Feedback and AI-Driven Solutions."

Abstract

This topic could explore the ways in which AI technologies are being used by airlines to improve the overall passenger experience, as well as the challenges and limitations that arise when using AI in this context. The analysis could draw on customer feedback data, as well as case studies and examples of AI-driven solutions that have been implemented by airlines to improve passenger satisfaction. Potential areas of focus could include personalized in-flight services, AI-powered customer service chatbots, and predictive maintenance to minimize flight delays and cancellations. The topic could also consider ethical considerations and potential privacy concerns associated with the use of passenger data in AI-driven solutions. explore how AI technologies can be leveraged to improve the passenger experience in the airline industry, including areas such as booking, check-in, in-flight services, and post-flight feedback. The discussion would cover the benefits of using AI, such as personalization and efficiency, as well as the challenges, such as data privacy and security concerns. The topic could also delve into case studies of airlines that have successfully implemented AI-based solutions to enhance passenger satisfaction, and provide recommendations for airlines that are considering adopting AI technologies to improve their services.

Full text

International Journal of Advance and Applied Research
www.ijaar.co.in
ISSN – 2347-7075
Impact Factor – 7.328
Peer Reviewed
Bi-Monthly
Vol.10 No.4
Mar – Apr 2023
174
“Exploring the Role of Artificial Intelligence in Improving
Passenger Satisfaction in the Airline Industry: An Analysis of
Customer Feedback and AI-Driven Solutions."
Dr.Sumitha.K 1 , Mr.Santhosh.K.V2
1Associate Professor & HOD, East Point College of Higher Education,
Bangalore, Karnataka, India.
2Assistance Professor, East Point College of Higher Education,
Bangalore, Karnataka, India.
Corresponding Author - Dr.Sumitha.K
Email : mesquitairena28@gmail.com
DOI-10.5281/zenodo.7827975
Abstract:
This topic could explore the ways in which AI technologies are being used by airlines to improve
the overall passenger experience, as well as the challenges and limitations that arise when using
AI in this context. The analysis could draw on customer feedback data, as well as case studies and
examples of AI-driven solutions that have been implemented by airlines to improve passenger
satisfaction. Potential areas of focus could include personalized in-flight services, AI-powered
customer service chatbots, and predictive maintenance to minimize flight delays and cancellations.
The topic could also consider ethical considerations and potential privacy concerns associated with
the use of passenger data in AI-driven solutions. explore how AI technologies can be leveraged to
improve the passenger experience in the airline industry, including areas such as booking, check-
in, in-flight services, and post-flight feedback. The discussion would cover the benefits of using AI,
such as personalization and efficiency, as well as the challenges, such as data privacy and security
concerns. The topic could also delve into case studies of airlines that have successfully
implemented AI-based solutions to enhance passenger satisfaction, and provide recommendations
for airlines that are considering adopting AI technologies to improve their services.
Keywords: Artificial Intelligence, Airlines, Passenger Satisfaction, Efficiency, Customer
Feedback
Introduction:
In recent times the technology has gained
traction in segments such as intelligent
maintenance, engineering and prognostics
tools, supply chains and customer services. The
sector is now eager to find more applications for
AI, with some European countries –
particularly Ireland, Finland, Cyprus,
Luxembourg, Sweden and the Netherlands –
leading the way. The revenue of commercial
airlines worldwide is predicted to recover in
2023, according to the trade organization
International Air Transport Association (IATA).
Airlines‟ financial losses are expected to
contract to $12 billion in 2022 compared with
$52 billion in 2021. Although recovery was
already present in the recent years it had been
slow due to ongoing border restrictions. And it
seems Artificial intelligence for aviation and
airlines is the one crucial element that actually
helps to improve the situation.
With increasing vaccinations and better
pandemic management this year, IATA expects
the aviation industry to recover in all regions,
with North America actually turning in profits
for the first time since the pandemic. An
important metric in the industry, the revenue
passenger kilometers (RPK, or the number of
kilometers paid by customers), is estimated to
have improved 18% in 2021 and is forecast to
improve 51% this year. This corresponds to
about 61% of pre-pandemic RPK.
As the aviation sector bounces back,
competition is bound to intensify as airlines
take advantage of customers eager to travel
after nearly two years of lockdowns. Firms that
innovate and incorporate new technologies will
be the clear winners.In particular, the use of
artificial intelligence (AI) is fast becoming a
game-changer in the industry.

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Source:https://www.ltimindtree.com/industries/travel-transport-and-hospitality
AI In Aviation
AI in aviation is disrupting the way
companies approach their data, operations,
and revenue stream. The world‟s leading
airlines are already using artificial
intelligence in aviation to improve
operational efficiency, avoid costly mistakes,
and increase customer satisfaction. There are
many different areas where machine learning
can empower the aviation industry. These
areas can be broken down into four main
categories:
 Customer service & retention
 Artificial intelligence in fleet &
operations management
 Air traffic control & air traffic
management
 Autonomous machines & processes
1)Customer Service And Retention
Aside from predictive maintenance and
increased efficiencies, enhanced customer
experience and customer satisfaction are
areas where AI in aviation is breaking new
ground. Artificial intelligence can be applied
to optimize pricing strategies, increase
customer satisfaction and engagement, and
improve the overall flight experience. Here‟s
a list of potential AI use cases for the travel
industry:
 Recommendation engines for tailored
offers – behavior-tracking techniques,
metadata, and purchase history can
create highly personalized offers,
increasing customer retention and
lifetime value.
 Sentiment analysis on social media –
when paired with intelligent algorithms,
social media feedback can evaluate
customer reactions close to real-time,
giving valuable insights for improving
customer experience.
 Chatbot software and customer service
automation – Kayak, a popular travel
booking service, allows you to plan your
next trip directly from your Facebook
Messenger app. Their type of chatbot is
humanlike, understands simple
questions, and responds in a casual,
conversational style.
 Conversational IVR – that allows to fully
automate calls or semi-automate the
process in contact centers by improving
the agents‟ efficiency.
According to research firm Gartner„s
“Emerging Technologies and Trends Impact
Radar for 2021” report, advanced virtual
assistants (AVA) are the next big step from
today‟s chatbots. AVAs will be powered by
NLP solution, resulting in conversational and
intuitive sessions, and semantic and deep
learning techniques such as deep neural
networks (DNNs).
Facial recognition and biometrics pave the
way to seamless airport security processes. A
similar approach can be applied to track how
people move across the airport, getting a
better sense of the flow of travelers.
2)Artificial intelligence in fleet &
operations management
Aviation companies and flight operators can
significantly lower operating costs and
overhead by optimizing their fleets and
operations with AI-powered systems.
Potential areas for applying AI in aviation
industry include:
 Dynamic pricing – to maximize revenue,
airlines are optimizing their base
published fare that has already been

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Dr.Sumitha.K , Mr.Santhosh.K.V
calculated according to passenger
journey, flight path, and broad
segmentation. Fares are further adjusted
after evaluating details about the
customers and current market conditions.
Airline companies use many different
variables to determine flight ticket prices:
whether the travel is during the holidays,
the number of free seats on the plane, etc.
According to John McBride, director of
product management for PROS, a
software provider that works with
airlines including Lufthansa, Emirates,
and Southwest, some operators have
already introduced dynamic pricing on
some ticket searches.
 Pricing optimization – also known as
airline revenue management, this is
similar to dynamic pricing. Machine
learning algorithms look for ways to
maximize sales revenue in the longer
term to ensure all flights are optimally
booked. These include historical data
such as past bookings, flight distance,
willingness to pay, etc.
 Flight delay prediction – as flight delays
are dependent on a huge number of
factors, including weather conditions and
what‟s happening in other airports,
predictive analytics and technology can
be applied to analyze massive real-time
data to predict flight delays, update
departure time, and re-book customers‟
flights on time.
 Airline companies are using many
different variables to determine the
flight ticket prices.
 Flight route optimization – is done
through machine learning-enabled
systems that can find optimal flight
routes, save money through lower
operational costs, and result in higher
customer retention. For this use case,
various route characteristics, such as
flight efficiency, air navigation charges,
fuel consumption, and expected
congestion level, can be analyzed.
 Avoiding travel disruption – Amadeus,
one of the leading global distribution
systems (GDS), has introduced a
Schedule Recovery system to help airlines
mitigate the risks of travel disruption
and flight delays.
 Crew scheduling – the labor costs of the
crew members and flight attendants of
major U.S. aircraft have grown (often
exceeding $1.3 billion a year) and are the
second-largest item (next to fuel cost) of
the total operating cost of major airlines.
Big data analysis can find the best way to
schedule an airline‟s crew to maximize
their time and increase employee
retention.
 Fraud detection – by analyzing specific
customers‟ flight and purchase patterns
and coupling them with historical data,
algorithms are able to identify passengers
with suspicious credit card transactions
and eliminate fraudulent cases, saving
airline and travel companies millions of
dollars every year.
Machine learning can also benefit the air
freight industry. For example, predictive
models help forecast whether a product will
be shipped on time and find the most optimal
routes. In addition, intelligent systems can
help identify problematic incidents and
increase operational efficiency.
3)Air Traffic Control And Air Traffic
Management (ATM)
The increasing benefits of AI in aviation
extend to critical tasks such as air traffic
management. Machine learning is not meant
to replace human air traffic controllers.
Instead, it aims to automate repetitive,
predictive tasks to free up human employees
to focus on more complex and important
tasks.
In August 2021, the UK government
approved a £3-million budget in partnership
with The Alan Turing Institute (UK‟s data
science research organization) and NATS
(National Air Traffic Services) to implement
live trials of the first-ever AI system in
airspace control called Project Bluebird.
AI In Aviation
Assembling an interdisciplinary team of data
scientists, engineers, and mathematicians,
Project Bluebird aims to study how AI
systems can work side-by-side with humans
to create an ATM that is intuitive,
sustainable, and risk-free.
In this project, machine learning algorithms
and data science are used to recommend
collaborative actions with air traffic control
teams, including tackling climate change
policies such as achieving net-zero carbon
emissions by 2050 through better routing and
lower fuel consumption.
4) Autonomous Machines And Processes
While completely self-flying planes still lie in
the distant future, there are already studies

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from both Airbus and Boeing to drive
autonomous aircraft forward. In December
2020, Boeing completed its test flights of five
uncrewed aircraft using AI algorithms, which
reached speeds of 270 kilometers per hour.
The company is confident that this successful
test run will propel autonomous technology
to the forefront in the coming years.
Meanwhile, there‟s an opportunity to
automate other types of airport processes,
such as ground handling, loading, fueling,
cleaning, and aircraft safety checks.
Airbus, one of the leading aerospace
companies, uses AI to analyze data coming
from various factories, predicting when
variations in the manufacturing processes
occur. This allows them to tackle the
problems earlier, when it‟s easier and less
costly, or even prevent them altogether.
Predictive maintenance will also help the
airline industry and aircraft manufacturers
save money in the long term as there would
be fewer parts replacements and overhauls.
The opportunities to implement Artificial
Intelligence (AI) at airports have
increased following the arrival of COVID
19 pandemic.
The use of AI at airports has been in the
pipeline for years. However the pandemic
fast tracked the importance of more tech-
smart innovation to face the challenges
ahead.
Artificial Intelligence (AI) is advertised to
be the answer to the challenges at
airports for better operational
performance, better access around the
terminal, and better safer travel
experience.
The Incheon airport in South Korea for
instance, as a way of controlling the
spread of the Covid-19 virus, introduced
robots to check the body temperature of
travellers (Incheon Airport presses ahead
with AI, biometrics and big data plans,
2021). The Incheon International Airport
has an airport robot assistant called
AIRSTAR. AIRSTAR communicates in
English, Mandarin, Japanese and Korean
and, produced by LG.
AIRSTAR moves at the speed of an
average pedestrian, finds its way around
surrounding obstacles and helps take
passengers where they need to go and
gives answers to their questions.
AIRSTAR can sense its moving speed and
adjusts accordingly when moving too fast
or too slow. AIRSTAR provides
passengers with information concerning
their flights, check-in, departure, arrival,
the airport, and other issues.
The robot measures the temperatures of
travellers without contact. In the case of
hyperthermia, the airline is automatically
contacted by the robot.
Other innovative technology of AI after
the pandemic are biometric airport
terminal such as face recognition in
Hartsfield-Jackson Atlanta, and Dubai
International Airport (for first and
business class passengers)
The use of chatbot for customer service
shouldn‟t be ignored as it helps
passengers get ready for flight. It helps
airlines and passengers form a good
relationship. Chatbots assist in
reservations booking, give the customer
booking advice, customer service helps
and booking management.
The keypoint and the importance of
Artificial Intelligence in airports is that
AI enables us to do things today that we
couldn‟t do five years ago. It has sped up
security at the landside of airports,
scanning people faster even though more
improvement is needed.
Research Methodology
Research Design: In the context of
research, primary data is collected for
specifically for the purpose of the research
project. This data is collected by the
researchers themselves, through method
personal interviews method to focus
groups(structured Interviews).
Researcher used Secondary data for the
purpose to support the primary data, which
improve the reliability and validity of
research findings. And to explore research
questions that cannot be addressed through
primary data collection methods.
The Objectives of the Study:
To identify the AI-driven solutions that can
be implemented to address the issues that
affect passenger satisfaction in the airline
industry.
To evaluate the effectiveness of AI-driven
solutions in enhancing passenger satisfaction
by conducting a survey or gathering feedback
from passengers.

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To provide recommendations for airlines on
how they can leverage AI to improve
passenger satisfaction and gain a competitive
advantage in the industry.
Target Population: Passengers who
travelled in past 6 months
Sample Size: 30
Tools used for data collection: Personal
Interviews Method
Review of Literature
 In this research article, Anirban Gupta
Et al., (2021), explains paper-based
processes have been replaced by digital
systems in aviation industry. It talks
about the usage and handling of artificial
intelligence in aviation industry and also
explains the growth that the industry has
achieved before and after implementing
this technology. As we all know that the
future generation will be machine
dominated, this article also provides
information about machine learning
along with AI. The specific objectives of
this research were use of AI and impact
of machine learning in aviation industry,
influence of AI-human collaboration and
future traits of aviation by AI.
 According to Yuchen Jiang Et al., (2022),
explains human-created machines can do
things like human and also how they
cultivate human-like intelligence. It also
describes how AI has entered into our
daily lives and the important roles played
by AI in different industries. Also
indicates how AI has become a part of our
life which we may or may not be aware of.
The study also discusses the challenges
that were faced on the path of revolution.
It is also believed that AI to be one of the
important tool which has changed socio-
economical lives to some extent.
 Through research Rusul L. Abduljabbar
Et al., (2019), describes the quick pace in
the development of AI which provides an
exceptional opportunity in different
industries including transport sector. The
study also describes the innovation
introduced by AI which imitates the way
the human brain works. This paper also
describes the challenges and limitations
of AI which are applied in transport
industry. The study also lightens that the
application of AI helps addressing the
concerns in more effective and efficient
manner.
 In this paper, A G Andrei Et al., (2021),
describes the changes that has happened
due to automatization and digitalization
in various industries which also includes
aviation industry. According to the study,
the use of this technology should simplify
and enhance the achievement of results.
This also explains how AI has gained
popularity over a period of time in all the
industries. This research also aims in
identifying the root cause of an accident
and also setting up new standards in
aviation industry with support of
artificial intelligence.
 In this study, Burcu Baydar Et al.,
(2019), explains the growing demand for
airline transportation in recent years and
its increased importance in both
passengers and cargo operations globally.
It also explains how airline industry has
been liable for connecting the global
economy and providing enormous jobs
and making modern quality of life
possible. The study also highlights how
airline industry is affected by various
factors including social, economic,
political and legal on both national and
international level.
 Nelvin Chummar Vincent Et al., (2021),
mainly emphases on application of
artificial intelligence in airports, space
and general aviation. The application of
AI in the airport mainly exhibits for
passenger identification, baggage
screening and answering customer
queries with the help of chatbots. The
application of AI in aviation sector
focuses on the control of aircraft for
stability, safety and maintenance and
fuel efficiency. The application of AI in
space differ and possibly make human
consideration redundant.
 Metin Emin Aslan Et al., (2022),
primarily focuses on improving flight
performance and minimizing
maintenance cost. At this juncture,
artificial intelligence came into picture
and it plays a very important role in
supporting maintenance repair overhaul
(MRO) companies. This research also
determines the most appropriate area
where AI can be implemented in aviation
maintenance repair activities and also in
identifying the most viable tool for
various decision making.

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 In this study, Reha Kilichan Et al.,
(2020), explains the application of
artificial intelligence and robotic
technologies in different fields and how it
is spreading rapidly and widely used
globally. The study also explains how
artificial intelligence becoming a part in
the tourism industry and the main focus
is to provide a better service to the
customers. Furthermore, in this study, AI
application and robotic technologies were
evaluated and development of these
technologies were revealed.
 In this paper, Maxim Krasnyuk Et al.,
(2021), talks about the development of
aviation industry that leads to an
increase in the number of flights which in
turn creates emission of more carbon
dioxide. At this juncture, the machine
learning came into picture and this helps
in reducing CO2 production by improving
the way the engines work or limiting the
running time of the engine. Also artificial
intelligence helps in solving different
issues. Furthermore artificial intelligence
and machine learning covers all areas of
aviation activities. It is also noted that
training and implementing AI is costly
but it plays a very important role in this
machine world.
 In this paper, Rafael Geisler (2018),
explains the recent adoption level and
potential impact of artificial intelligence
in travel and tourism industries. The
main focus of this paper lies on the
application of artificial intelligence in
chatbots and their usage along the
traveler journey. The main purpose of
this paper is to make people aware about
AI and how to use AI in their travel and
tourism business. The paper also
indicates the development of artificial
intelligence and its impact on travel and
tourism industry. AI is becoming a vital
part in everyone‟s day to day life and it
plays a very important role.
Findings:
AI to be activated, the organization must be
operating under digital systems. Therefore,
digital transformation is core process for AI
implementation, it enables the use of the
latest technologies to enhance existing
processes and improve existing services. It
creates the value by changing the way the
system delivers value to beneficiaries. Few
Airlines already have the IT infrastructure to
implement changes.AI framework is
perceived as a roadmap, reference point and
root of digital transformation projects. It
aims to improve business‟ digitization
processes by identifying the goals of
digitization and implement toward the goal.
After comparing the results of the analysis
implemented, the authors see that the study
hypotheses match their results. First, the
results of the correlational and regression
analyses prove that there is a positive
relationship between AI and customer
experience and that there is a direct
relationship between providing personalized
customer service and after-sale customer
support, and AI. And by using descriptive
analysis along with the analyses mentioned
earlier, authors show that providing
personalized customer service throughout the
customer‟s buying journey has a great impact
on the customer experience. Also, using AI in
call centers and other after-sales support
serviceswill decrease the customers‟ waiting
time, and hence enhance thecustomers‟
experience. Last but not least, the thematic
analysis of the interviews shows that not all
companies in Palestine are able to fully adopt
the technology of AI due to high costs and
lack of skills in the Palestinian society. In the
end, we now realize that AI is a fast-moving
train, and it is developing inside our homes
and working places. It will eventually take
over every device we use and will become an
inevitable part of our lives. All of us,
including the developers of such technology,
should make sure that we only allow it to
comfort humans, not replace them
Suggestion:
As an AI language model, some general
insights has been used in the airline industry
to improve passenger satisfaction. AI has
been used in a variety of ways to improve the
passenger experience in the airline industry,
including:
 Personalized recommendations:
airlines can use ai algorithms to analyse
passenger data, such as travel history
and preferences, to provide personalized
recommendations for flights,
accommodations, and activities.
 Chatbots and virtual assistants: ai-
powered chatbots and virtual assistants
can provide passengers with instant
access to information about flight
schedules, check-in procedures, and
baggage handling, reducing wait times

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and improving the overall customer
experience.
 Predictive maintenance: AI algorithms
can analyse data from aircraft sensors
and other sources to predict maintenance
issues before they occur, reducing the
likelihood of flight delays or
cancellations.
 Security screening: ai-based security
screening systems can analyze passenger
behavior and biometric data to identify
potential security risks, improving the
efficiency and accuracy of the screening
process.
 Smart Airports: AI can be used to
optimize airport operations, such as
predicting traffic patterns and optimizing
gate assignments, which can help reduce
wait times and improve the overall
passenger experience.
Overall, the use of ai in the airline industry
has the potential to improve passenger
satisfaction by providing personalized
recommendations, reducing wait times, and
improving the efficiency and accuracy of
airport operations. However, it is important
for airlines to ensure that these ai systems
are designed and implemented in a way that
protects passenger privacy and data security.
Conclusion:
In conclusion, analyzing customer
feedback is crucial for businesses to
understand their customers' needs and
improve their overall experience. With the
advancements in AI technology, businesses
can leverage AI-driven solutions to automate
the process of analyzing customer feedback,
making it faster and more efficient. These
solutions can help businesses identify
patterns, sentiment, and topics of customer
feedback, allowing them to take actionable
insights to improve their products and
services. Moreover, AI-driven solutions can
help businesses personalize their customer
experience by providing tailored
recommendations and support. Overall,
incorporating AI-driven solutions in customer
feedback analysis can enhance the customer
experience and increase customer loyalty,
leading to long-term business success.
Reference:
1. (PDF) The Influence of Artificial
Intelligence on the Productivity and
Customer Satisfaction in the Aviation
Industry. Available from:
https://www.researchgate.net/publication/
363070648_The_Influence_of_Artificial_I
ntelligence_on_the_Productivity_and_Cus
tomer_Satisfaction_in_the_Aviation_Indu
stry [accessed Mar 30 2023].
2. (PDF) The Role of Artificial Intelligence
on Enhancing Customer Experience.
Available from:
https://www.researchgate.net/publication/
334315006_The_Role_of_Artificial_Intelli
gence_on_Enhancing_Customer_Experie
nce [accessed Mar 30 2023].
How Artificial Intelligence Is Improving
Airline Industry (aeologic.com)-
suggestion
3. Artificial Intelligence in Airports –
iConnect Aviators Ltd
4. The Future of Artificial Intelligence in
Airports | Teague
5. AI in aviation and airlines: Use cases
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