INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
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ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XIV, Issue X, October 2025

www.ijltemas.in Page 923

Applications, Awareness and Assessment of Artificial Intelligence in
Central Library of Banaras Hindu University to Enhancing Smart

Library towards Automated Library Systems: A study of Users'
Attitudes

Santosh Kumar Kannaujia, Dr. Madhu Patel

Department of Library & Information Science, Mahatma Gandhi Central University, Motihari, Bihar- 845401, India

DOI: https://doi.org/10.51583/IJLTEMAS.2025.1410000112

Abstract

Purpose: The purpose of this article is to explore the users' knowledge about artificial intelligence in an automated scenario of
central library of Banaras Hindu University.

According to the study, user awareness is still moderate even though AI is improving cataloguing, resource access, and user services
at the Central Library.

Scope: This study explores the users’ awareness of Central Library of Banaras Hindu University in intelligent environment as well
as the automation of this academic library utilizing AI.

Methodology: For this study, a total of 100 questionnaires were distributed, and 85 BHU users answered. The data was analysed
using Microsoft Excel to understand user perspectives and experiences, as well as to investigate the impact of AI on library
automation.

Findings: Of those surveyed, just 45.88% were aware of chatbots and other AI tools. 56.47% of them visited daily, despite this.
According to a survey, 64.71% of Central Library patrons are aware of automation. The report highlights how artificial intelligence
(AI) is transforming traditional library operations by enhancing services and user engagement through intelligent technology.
Results demonstrate that AI improves productivity and customization, satisfying the changing requirements of scholars, teachers,
and students.

Keywords: Smart Library, AI Technology, Artificial Intelligence, Automated Library Systems, Central Library, Digital Libraries.

I. Introduction of the Study

Libraries are quickly changing from static information repositories to dynamic, tech-driven smart libraries in the digital age. This
change is mostly due to artificial intelligence (AI), which has brought about intelligent automation, individualized user experiences,
and effective information retrieval technologies. Implementing AI technologies such as predictive analytics, automated cataloguing,
and virtual assistance can enhance libraries' operational effectiveness and meet the diverse needs of their patrons. Academic
Libraries are not exempt from the technology revolution that has swept through traditional institutions in the twenty-first century.
This introduction explores the significance of AI in reshaping library functions and sets the stage for analyzing its specific
applications and impacts within the Central Library of Banaras Hindu University (BHU). Using AI technologies, the library is set
to introduce innovative services and resources that will greatly enhance the library experience for all users. These forthcoming
developments are expected to transform users’ engagement with information and the community.

II. Review of related Literature

Moghe, Nagarkar, and Pradhan (2024) explored the critical evaluation of the KOHA Open-LMS (Library Management System)
implementation is provided in this study for each of the 13 libraries of higher education institutions in Pune, Maharashtra's Maharshi
Karve Stree Shikshan Sanstha (MKSSS). Manjunatha and Kumar (2024) studied postgraduate Library and Information Science
(LIS) students in South Indian universities are asked to consider their knowledge of and use of automation, digitization, and
reference management systems. Park and Doo (2024) reviewed the developments in artificial intelligence (AI) technology offered
chances to create more dynamic and varied blended learning as it transitioned into a new phase during the COVID-19 pandemic.
Wingström, Hautala and Lundman (2024) studied the creativity has been impacted by artificial intelligence (AI). The usual
definitions of creativity, which have historically included five components—actor, process, outcome, domain, and space—are called
into question by the developments of creative AI systems. Bozkurt and Sharma (2023) analysed the given the permanence of
generative AI, we must investigate the possible applications of these technologies in online and remote learning, considering both
the advantages and disadvantages. Echedom and Okounghae (2021) examined the characteristics of artificial intelligence (AI),
its application to library operations, instances of academic libraries in Sub-Saharan Africa that have implemented AI technologies,
the necessity of AI in libraries, and the difficulties in implementing AI in libraries were all covered in this study.

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Objectives of the Study

 To identify and analyse the key applications of Artificial Intelligence (AI) in modern library systems.

 To assess the awareness, adoption, and utilization of AI tools among library professionals and users.

 To find out the benefits and challenges associated with implementing AI in library environments.

 To study the impact of AI on the efficiency, personalization, and accessibility of library services.

Limitations of the study

The study is limited to UG, PG and Research Scholars of BHU to investigate the awareness about role and AI applications in
automated library environment.

Role of AI in Enhancing Smart Libraries in Automated Systems

AI is playing a vital role in transforming traditional libraries into “Smart Libraries” by enhancing efficiency, improving user
experience, and optimizing resource management. AI-powered tools automate tasks like cataloguing, classification, and metadata
generation, while also providing personalized recommendations and intelligent search systems. This shift allows librarians to focus
on more complex tasks and community engagement, ultimately making libraries more accessible and responsive to user needs.

Improved
User

Experience

Personalized
Recommendations

Accessibility
Features

Intelligent
Search
system

Collection
Development

and
Optimization

User-
Friendly

Interfaces

Optimized
Resource

Manageme
nt

Predictive
Analytics

Preservation
and Security

Preservation
of Digital

and Analog
Records

Content
Customizat

ion and
Adaptation

Enhanced
Security

1.Enhanced
Efficiency

and
Automation

2. Streamlined
Circulation and

Resource
Management

3. Smart
Shelving and

Inventory
Management

4. Virtual
Assistants

and
Chatbots

1. Automated
Cataloguing

and Metadata
Management

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The library is currently using AI applications to improve smart libraries.

Through a variety of applications, such as intelligent guiding, personalized suggestions, automated chores, and enhanced search
capabilities, artificial intelligence is being applied in libraries to improve smart library functions. A crucial element is Natural
Language Processing (NLP), which makes it possible for chatbots to assist users and analyse text data to gain insights. Algorithms
for machine learning assist with tasks like recommendation systems and library operations optimization. Libraries may improve the
whole library experience for patrons and employees by using these AI tools to create more effective, entertaining, and user-friendly
spaces.

A closer study at AI applications in libraries can be found here:

Key barriers of AI Adoption

There are some following crucial barriers to adopting AI technology: Adoption of AI is trammel by a variety of factors, including
organizational, ethical, and legal issues.

Technical Barriers:

Data Quality and Infrastructure Deficits: Large amounts of structured, high-quality data are necessary for AI systems to operate
efficiently; inconsistent or subpar data might result in unreliable outputs and reduce performance. In addition, many libraries lack
the solid IT infrastructure (such as a dependable power supply and powerful network access) required for smooth AI integration
and growth, as well as antiquated legacy systems.

Financial Barriers:

High Implementation and Maintenance Costs: One of the biggest obstacles, particularly for underfunded schools, is the
substantial upfront costs associated with hiring hardware, software, and AI expertise. Another significant, long-term financial
burden is the continuing expenses for upkeep, updates, and retraining AI models.

Organizational Barriers:

Lack of Skilled Personnel and Training: One major obstacle is the severe lack of personnel with specific AI knowledge and data
science abilities. Many employees find it difficult to use AI tools effectively due to a lack of professional development programs
and the frequent need for extensive training for current personnel.

Ethical and Legal Barriers:

Privacy, Security, and Bias Concerns: AI applications frequently call for gathering and analysing large amounts of user data
(such as borrowing history and others), which presents significant privacy and data protection concerns that run counter to the

1. Intelligent Guidance and Navigation

 Virtual Assistants/Chatbots
 Intelligent Sensing Spaces

2. Intelligent Navigation

 Better User Experience
 Personalized Suggestions
 Enhancements to Search Features

3. Summarizing the Content

 Automated Tasks and Operations

 Automated Cataloguing

 Intelligent Inventory Management

4. Data Analysis and Reporting

 Research and Learning Support

 Virtual Research Assistants

5. Citation Analysis

 AI Frameworks and Libraries

 Natural Language Processing

 Machine Learning

 Data Mining

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ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XIV, Issue X, October 2025

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library profession's dedication to patron privacy. Due to imbalanced training data, algorithmic biases in AI models have the potential
to reinforce social injustices and produce unfair or discriminating results in the provision of services.

Operational Barriers:

Interoperability and Customization Issues: It might be technically challenging and necessitate significant customisation to
integrate AI technologies with current, frequently proprietary library management systems (LMS). It is particularly challenging to
guarantee accountability and transparency in library operations due to the "black box" nature of some AI decision-making processes.

III. Research Methodology

This study examines the impact of Artificial Intelligence (AI) on the automation of libraries in the current scenario. I distributed
100 closed ended questionnaires to users to gather their experiences and perspectives on AI in an automated library environment,
and received only 85 responses. The data was collected from the users of the Banaras Hindu University. Received data was
processed and analysed using MS-Excel.

Data Analysis and Interpretation

Table 1: Gender Category of Respondents

Gender of the
Respondents

Number of
Respondents

Percentage of
Respondents

(%)

X F FX Arithmetic
Mean

(��̅)

Total 85
(100%)

1. Male 52 61.18% 52 1 52 42.5

2. Female 33 38.82% 33 1 33

Table 1 illustrates the gender distribution of the respondents, out of 100 total 52 (61.18%) males and 33 (38.82%) females
participating in the questionnaire.

Table 2: Category of the age of the respondents

Age of the
Respondents

Number of
Respondents

Percentage of
Respondents

(%)

X F FX Arithmetic
Mean

(��̅)

Total 85
(100%)

1. 18-25 yrs 82 96.47% 82 1 82 42.5

2. 26-30 yrs 3 3.53% 3 1 3

Number of
Respondents

Percentage of
Respondents

(%)
X F FX

Arithmetic
Mean

For Each
Variables 85

(100%)
2. Female 33 38.82% 33 1 33
1. Male 52 61.18% 52 1 52 42.5

61.18%

52
42.5

38 82

33 33

Gender Category of Respondents

1. Male 2. Female

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According to the graph, the largest percentage of responders is between the ages of 18 and 25 of the replies to the questionnaire, 82
(96.47%) users are between the ages of 18 and 25, and 3 (3.53%) are between the ages of 26 and 30.

Table 3: Category of Educational Qualification of the Respondents

Category of
Educational
Qualification of
the Respondents

Number of
Respondents

Percentage of
Respondents

(%)

X F FX Arithmetic
Mean

(��̅)

Total 85
(100%)

1. UG 50 58.82% 50 1 50 28.33

2. PG 23 27.06% 23 1 23

3. Research
Scholar

12 14.12% 12 1 12

Table 3 shows that there are 50(58.82%) users are under-graduate followed by 23(27.06%) users are post-graduate and 12(14.12%)
users are research scholars who responded the distributed questionnaire as per the received data.

Percentage of
Respondents (%)

X F FX Arithmetic Mean
For Each

Variables 85
(100%)

2. 26-30 yrs 3.53% 3 1 3
1. 18-25 yrs 96.47% 82 1 82 42.5

96.47%

42.5

3.53%

3 3

0.00%
1000.00%
2000.00%
3000.00%
4000.00%
5000.00%
6000.00%
7000.00%
8000.00%
9000.00%

Category of the age of the respondents

1. 18-25 yrs 2. 26-30 yrs

58.82%

28.33

27.06%

14.12%

Category of Educational Qualification of the Respondents

Category of Educational Qualification of the Respondents 1. UG 2. PG 3. Research Scholar

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Table 4: Status of daily visit the library

Status of daily
visit the library

Number of
Respondents

Percentage of
Respondents

(%)

X F FX Arithmetic
Mean

(��̅)

Total 85
(100%)

1. Yes 55 64.71% 55 1 55 21.25

2. No 9 10.59% 9 1 9

3. Sometimes 20 23.53% 20 1 20

4. Rarely 1 1.18% 1 1 1

Table 4 shows the information about library among respondents. Out of the participants, 55 (64.71%) indicated that they visit the
library regularly. In contrast, 9 (10.59%) reported that they do not visit the library, while 20 (23.53%) mentioned that they visit
sometimes. Additionally, 1 (1.18%) stated that they rarely visit the library based on the responses received.

Table 5: Frequency of visit the central library by the users

Frequency of visit the
central library by the
users

Number of
Respondents

Percentage of
Respondents

(%)

X F FX Arithmetic
Mean

(��̅)

Total 85
(100%)

1. Per day/Daily 48 56.47% 48 1 48 17

2. Twice in a week 3 3.53% 3 1 3

3. Thrice in a week 7 8.23% 7 1 7

4. Once in a week

3 3.53% 3 1 3

5. Whenever needed 24 28.23% 24 1 24

Number of
Respondents

Percentage of
Respondents

(%)
X F FX

Arithmetic
Mean

For Each
Variables 85

(100%)
4. Rarely 1 1.18% 1 1 1
3. Sometimes 20 23.53% 20 1 20
2. No 9 10.59% 9 1 9
1. Yes 55 64.71% 55 1 55 21.25

0
0

0 0 0 0 0 0 0

64.71%

21.25

10 59

9 9

23 3

201

1.18%

1 1

Status of daily visit the library

1. Yes 2. No 3. Sometimes 4. Rarely

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Table 5 examines the frequency with which users visit the central library. The largest group, comprising 48 users (56.47%), visits
the library daily. Following this, 3 users (3.53%) reported visiting the library only twice a week, while 7 users (8.23%) visit three
times a week. Additionally, 3 users (3.53%) visit the library just once a week, and 24 users (28.23%) visit the library as needed.

Table 6: Users’ awareness about library automation

Users’ awareness about
library automation

Number of
Respondents

Percentage of
Respondents

(%)

X F FX Arithmetic
Mean

(��̅)

Total 85
(100%)

1. Yes 53 62.35% 53 1 53 42.5

2. No 32 37.65% 32 1 32

Table 6 shows majority 53(62.35%) of users admit that they are aware about automation of library whereas 32(37.65%) users were
not aware about library automation in the central library as per the received responses.

Number of
Respondents

Percentage of
Respondents (%)

X F FX Arithmetic Mean
For Each

Variables 85
(100%)

1. Yes 53 62.35% 53 1 53 42.5
2. No 32 37.65% 32 1 32

62.35%

42.5

37.65%

Users’ awareness about library automation

1. Yes 2. No

56.47%

3
3.53%

3 3
7

8 2
7 7

28 23

24 24

NUMBER OF
RESPONDENTS

PERCENTAGE OF
RESPONDENTS (%)

X F FX ARITHMETIC MEAN FOR EACH
VARIABLES 85

(100%)

Frequency of visit the central library by the users

1. Per day/Daily 2. Twice in a week 3. Thrice in a week 4. Once in a week 5. Whenever needed

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Table 7: Status of automation in the library

Opinion of Users on
automated library

Number of
Respondents

Percentage of
Respondents

(%)

X F FX Arithmetic
Mean

(��̅)

Total 85
(100%)

1. Fully automated 27 31.76% 27 1 27 28.33

2. Semi-automated

39 45.88% 39 1 39

3. Partially automated 19 22.35% 19 1 19

Table 7 shows that the highest proportion of respondents, 39 individuals (45.88%), indicated that their library is semi-automated.
Additionally, 27 respondents (31.76%) reported that their library is fully automated, reflecting a positive trend toward the adoption
of complete digital systems in library services. Whereas, 19 respondents (22.35%) stated that their library is partially automated.

Table 8: Users Awareness about Artificial Intelligence

Users Awareness about
Applications of Artificial
Intelligence

Number of
Respondents

Percentage of
Respondents

(%)

X F FX Arithmetic
Mean

(��̅)

Total 85
(100%)

1. Yes 39 45.88% 39 1 39 28.33

2. No 21 24.70% 21 1 21

3. Not Sure 25 29.41% 25 1 25

27 31.76% 27 1 27

28.33
39 45.88% 39

1
39

19 22.35% 19
1

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Number of
Respondents

Percentage of
Respondents (%)

X F FX Arithmetic Mean For Each Variables
85 (100%)

Status of automation in the library

1. Fully automated 2. Semi-automated 3. Partially automated

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Table 8 indicates that 39 users (45.88%), representing a significant majority of the respondents, reported that they were aware of
AI applications. In contrast, 21 participants (24.70%) stated that they were unaware of such applications. Additionally, 25
respondents (29.41%) selected the "Not Sure" option, reflecting uncertainty or confusion regarding the use of AI applications.

IV. Findings of the Study

There were 52 (61.18%) male and 33 (38.82%) female respondents contributed for the study. There were 82(96.47%) majority of
users are lies between the age category of 18 to 25 years old. There were found maximum 82 (96.47%) users got between 18 to 25
yrs. who responded the questionnaire. These statements show that 50(58.82%) users were under-graduate there after 23(27.06%)
respondents were post-graduate and 12(14.12%) respondents were research scholars. There were maximum 55(64.71%)
respondents admit that they are visiting the library at regular basis and 20(23.53%) users visit the library sometimes. 48(56.47%)
users daily visit the library for their study purposes whereas 24 (28.23%) users visit the library when they needed. There were
upmost 53(62.35%) users aware that their library is automated. The maximum 39(45.88%) respondents were aware about artificial
intelligence (AI) applications in the library.

V. Conclusion

A revolutionary change in how libraries function, provide services, and engage with patrons is represented by the incorporation of
Artificial Intelligence (AI) into library systems. The ways that intelligent systems are redefining conventional library functions were
highlighted in this study, which examined the many roles and applications of AI in the context of smart libraries. This study
investigated and found almost 64.71% respondent visited library daily and 62.35% shows users’ awareness about library
automation. This study also reflected that 45.88% respondents aware of AI’s applications useful for users in libraries.

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