A study on the knowledge and perception of artificial intelligence

Abstract

This study investigated the knowledge and perception of artificial intelligence among library and information science professionals in Zambia by surveying 245 randomly selected participants. The results show that the library and information science professionals had a favourable and encouraging outlook with regard to artificial intelligence but were also concerned about artificial intelligence replacing librarians’ roles and the barriers to adopting artificial intelligence technologies in Zambian libraries. The article suggests that libraries should consider the study’s findings before implementing artificial intelligence, particularly concerning technology and facilities, librarians’ proficiency in artificial intelligence, and leadership positions in artificial intelligence initiatives. The research can be used as a resource by library boards and associations to develop policies for implementing artificial intelligence in academic libraries, and fills a research vacuum in developing nations like Zambia regarding the knowledge of university and college libraries, and their willingness to use artificial intelligence.

Keywords

Artificial Intelligence (AI)digital technologies intelligent library development librarian skills technology adoption Zambia

Introduction

Artificial intelligence (AI) aims to create machines which can perform tasks that normally require human intelligence, such as problem-solving, decision-making and natural language processing. AI systems are designed to learn from data and adapt to new situations, allowing them to improve their performance over time. However, it is important to note that AI is still in its early stages of development, and many challenges need to be addressed before it can be fully integrated into libraries and information services. These challenges include privacy, security and ethical considerations. Additionally, as AI technologies continue to evolve, it will be important for libraries and information services to keep pace with the latest developments and adapt their services accordingly (Bubinger and Dinneen, 2021; Huang and Rust, 2018; Lund et al., 2020).

ExLibris (2019) argues that machines possess greater intelligence capacity due to their efficient recognition and assimilation of patterns on a significantly larger scale than humans. This capacity for intelligence allows machines to learn and improves their ability to perform tasks without being explicitly programmed. Many of our routine computing tasks are already influenced by AI. AI characteristics are present in most modern computers and smartphones, and we have undoubtedly used them without realizing they were intelligent devices:

Natural language processing, robotics, self-driving or autonomous vehicles, speech recognition, machine learning, deep learning, and self-driving automobiles are some examples of artificial intelligence in computers. The strength and benefit of artificial intelligence come from the fact that machines can recognize patterns quickly and efficiently on a scale that humans cannot. (Madakam et al., 2022:)

Libraries have traditionally been viewed as institutions that promote access to information and knowledge. However, the use of automation and digital technologies in libraries has been slower than in other industries. This has led to the criticism that libraries need to catch up with the times and take advantage of the opportunities presented by digital technologies. However, it is essential to note that libraries have unique challenges in digitization, such as limited budgets, concerns about preserving and digitizing physical collections, and the need to ensure access for patrons who may not have digital literacy skills (Astle and Muir, 2002; Awamleh and Hamad, 2022; Matusiak et al., 2017). Additionally, librarianship has a different approach to knowledge, focused on preservation and access rather than profit, which may explain the slow progress in digitalization. It is important to note that libraries are working to overcome these challenges and finding new ways to provide access to information and knowledge through digital technologies (Alenezi, 2023; Feliciano-Cestero et al., 2023; Lischer-Katz, 2022; Meng et al., 2023).

AI is having a significant impact on libraries and information services. It automates repetitive tasks, such as cataloguing and data entry, and improves search capabilities, providing patrons with more accurate and relevant results. AI-powered chatbots are also being used to assist patrons with their research and answer their questions. Additionally, machine learning algorithms analyse large data sets and make personalized recommendations to patrons. However, the use of AI in libraries also raises some concerns, such as the need for privacy, security and the ethical use of data (Asemi et al., 2020; Panda and Chakravarty, 2022; Smith, 2022). AI is a rapidly evolving field, changing how we interact with technology. It involves the development of intelligent computers that can perceive, think and behave like humans (Goralski and Tan, 2020; Hassani et al., 2020; Popenici and Kerr, 2017).

With the growing use of AI in libraries, there is also an increasing need for data and AI literacy (Laupichler et al., 2022; Mani et al., 2021). The responsibilities of library and information science (LIS) employees in assisting users will need to shift as their context changes due to AI. For instance, newcomers to scientific research will affect scholarly communication and the methods used to support it. For this, library personnel will need a solid understanding of AI technologies and the ability to use them in their work. Many libraries and information services already use AI in their operations (Alam, 2022; Hussain, 2023). In particular, machine learning technologies are being used for activities like automatic resource categorization and classification; collection recognition and weeding; automated cataloguing and data entry; personalized suggestions based on users’ search and lending histories and other data (Cordell, 2020; Gul and Bano, 2019; Pekala, 2017; Yang, 2022); and the application of voice assistants, virtual assistants and chatbots to educational institutes’ library services (Mckie and Narayan, 2019).

Moreover, with the increasing use of AI in libraries, they will need to ensure that these technologies are used ethically and responsibly. LIS professionals will have to work to ensure that AI is used to improve access to information rather than restrict it. Additionally, they must work to ensure that AI-powered systems are inclusive and equitable, and do not perpetuate biases or discrimination.

Libraries utilize Artificial Intelligence (AI) to leverage big data and perform data analysis in their operational and service-oriented domains. However, the full implementation of AI in libraries is difficult without LIS professionals having the relevant knowledge, skills and wisdom. There is a lack of research in the LIS field in Zambia on using AI in libraries. Such research would be beneficial in understanding the perception of library professionals towards AI and how it can be adopted in libraries. This can assist library administrators and tech-savvy professionals in promoting the adoption of AI technology in libraries.

The objectives of this study are to:

Assess the knowledge of LIS professionals about AI;

Identify the perception of AI among LIS professionals;

Determine the skills that LIS professionals require in the AI era.

The research questions for this study are:

What knowledge do LIS professionals have of AI?

What is the perception of AI among LIS professionals?

What skills are required by LIS professionals in the AI era?

Literature review

AI in libraries is not a new area of study; several studies have been conducted on AI. Empirical research, conceptual papers and literature review articles were collected from Google Scholar in 2023 using ‘artificial intelligence AND library’ as keywords. And to obtain articles related to the knowledge and perception of AI among LIS professionals, manual screening of relevant documents was conducted.

Many conceptual papers on AI in libraries have been published, including on the application of AI for efficient library service delivery in academic libraries in Nigeria (Yusuf et al., 2022). Yusuf et al. (2022) report that implementing AI technology in academic libraries has raised the bar for the effectiveness and efficiency of library service delivery, enabling libraries to enhance and offer dynamic services for library users. It is user-friendly, especially in searching for information, and is also used to direct and assist library activities. The study also points out that, despite AI’s advantages, several difficulties still prevent the seamless implementation of the technology in many academic libraries in Africa, including unstable power supplies, increasing skills gaps, job loss and inadequate infrastructure. Massis (2018) found that while AI may be seen as a threat to traditional institutions like libraries, it also has the potential to enhance library services greatly. The author suggests that while the implementation and development of AI in libraries is still in its early stages, AI can significantly improve a variety of library services if fully accepted and integrated into them.

According to Tait and Pierson (2022), there are excellent prospects for LIS education to position the field as a driving force at the nexus of human information behaviour, information ethics, and ethical AI and robot development and usage. They suggest that by including more education on AI and robots in LIS programmes, LIS professionals will be better equipped to understand the implications of these technologies and how to use them responsibly and ethically.

Cox et al. (2018) interviewed 33 library directors, library commentators, specialists and publishers to gather their perspectives on the future of AI in libraries. They identify several areas where AI could be useful, such as in supporting machine-readable collections, information-finding tools, research creation, scholarly communication, and teaching and learning. McKie et al. (2022) found that the perceived personalities and humanness of voice assistants play a significant role in how users interact with the technology and retrieve information; Yao et al. (2015) discovered that Xaiotu, an AI-based smart talking robot, could be readily tailored to cater to the specific requirements of diverse libraries, thus enabling the provision of virtual reference services in libraries; Kaushal and Yadav (2022) found that integrating chatbot technology with an existing library information system could give a range of services promoting scholarly communication and research; and Modiba (2021) found that records were not effectively managed due to the lack of a reliable records management system, and therefore suggests implementing AI technology such as automated digitization, automated classification, and the quick retrieval and disposal of records, which can be used to manage records services effectively.

Further, a study by Massis (2018) suggests that while AI may be seen as a threat to traditional institutions like libraries, it also has the potential to enhance library services greatly. Mogali (2014) identified various areas of AI, including pattern recognition, expert systems, robots and natural language processing. The author notes that the use of expert systems in library tasks such as cataloguing, categorization and reference services has shown significant promise and has the potential to increase library productivity greatly.

Grbin et al. (2022) highlight the importance of librarians’ participation in developing and researching automation solutions. They argue that, as information professionals, librarians should be supported and encouraged to collaborate with researchers and contribute to machine learning initiatives, and that librarians bring a unique set of skills and knowledge to the table, such as expertise in information organization, data management and user-centred design, which can greatly benefit the development and implementation of automation solutions. Harisanty et al. (2022) discovered that exploring AI from multiple perspectives, including those of leaders, practitioners, and scientists, provided a comprehensive understanding of the level of awareness among library stakeholders and the necessary knowledge to undertake AI initiatives. Their study highlights the benefits, practicality, and requisite knowledge and skills related to AI, as well as the obstacles and available AI resources in Indonesian libraries.

According to Ajani et al. (2022), librarians’ opinions on whether university libraries can incorporate AI technology into their operations and services are divided. The authors argue that integrating AI into library operations and services can enhance libraries by lowering the human error rates associated with repetitive jobs. However, their study also brings to light librarians’ worries about losing their jobs. Wood and Evans (2018) found that most of their respondents believed that AI will significantly impact libraries over the next three decades, with resource discovery and referencing being the most likely areas. Honghai (2020) reports that AI does not take the position of reference librarians but helps them deliver services that meet consumers’ technical expectations. According to Honghai, AI can efficiently analyse vast amounts of data from internal and external repositories to cater to the specific needs of consumers. The author also discusses the employment of an AI-powered ‘knowledge assimilation agent’ to produce knowledge through machine learning from library materials and user–system interactions. This can support researchers who work with a large amount of data and help a library stay relevant within its organization. However, LIS professionals have some concerns about AI, including worries about job losses in libraries, a lack of breakthroughs in AI that are pertinent to libraries, and privacy and data security issues, and believe that libraries should work to ensure that AI is used to benefit society rather than restrict access to information (Cox et al., 2018). Garcia-Febo (2019) emphasizes that libraries should proactively address these concerns by developing policies and procedures which ensure that AI is used ethically and responsibly. She also calls for libraries to invest in developing AI technologies that are aligned with their missions and goals, and support their role as stewards of knowledge and information.

Research method and plan

A descriptive approach was employed for this study. The three independent variables, namely knowledge, perception, and skills, were examined, while the dependent variable was the number of AI implementations. The objective was to assess the statistical relationship between the knowledge, perception, and skills of LIS professionals (the independent variables) and AI (the dependent variable).

Zambia was the focus of this study because this kind of inquiry has not yet been conducted in the country. The target population was LIS professionals who are members of the Library and Information Association of Zambia. Forty-five statements were distributed to the 469 selected participants via Google Forms to collect primary data. However, only 245 participants responded to the structured questionnaire. It used a 5-point Likert scale, with (1) strongly disagree being the lowest score and (5) strongly agree the highest. Literature such as published articles, books and websites was reviewed to gather secondary data.

Thematic analysis was employed to analyze the data, resulting in the identification of three themes: (1) awareness of AI, (2) perception of AI, and (3) AI skills. The researchers utilized SPSS for data analysis and to address the research questions.

Results

The following are the findings from the primary data obtained through the administration of the questionnaire, which have been analysed following the themes established at the start of the study. The findings are presented in graphs and tables.

Table 1 provides an overview of the theme of ‘awareness of AI’ among the LIS professionals. The majority of the respondents were aware of AI in libraries, as indicated by the various responses in Table 1. This conclusion is derived from the fact that, on average, 44.1% of the respondents agreed that AI is essential for the effectiveness and efficiency of library service delivery, enabling libraries to enhance and offer dynamic services for their users.

Table 1.

Awareness of AI among LIS professionals.

Statements	Strongly agree (%)	Agree (%)	Neutral (%)	Disagree (%)	Strongly disagree (%)	M	SD
AI is used in reference services in libraries	48 (19.6)	108 (44.1)	24 (9.8)	40 (16.3)	25 (10.2)	3.46	1.11
AI predicts readers’ book search trends	24 (9.8)	130 (53.1)	64 (26.1)	27 (11.0)	0 (0.0)	3.61	0.89
AI is employed in chatbots to enhance the experiences of readers	45 (18.4)	95 (38.8)	81 (33.0)	14 (5.7)	10 (4.1)	3.61	0.98
AI is used to detect misinformation	72 (29.4)	115 (46.9)	38 (15.5)	13 (5.3)	7 (2.9)	3.94	0.97
AI is used to find articles	41 (16.8)	148 (60.4)	38 (15.5)	14 (5.7)	4 (1.6)	3.84	0.90
AI is used in optical character recognition and the preservation of documents	84 (34.3)	75 (30.6)	42 (17.1)	26 (10.6)	18 (7.4)	3.73	1.11
AI is used in indexing	75 (30.6)	102 (41.6)	40 (16.3)	22 (9.0)	6 (2.5)	3.88	1.00
AI is used in weeding library materials	40 (16.3)	121 (49.4)	60 (24.5)	24 (9.8)	0 (0.0)	3.72	0.92
AI is used in library auditing	65 (26.5)	86 (35.1)	38 (15.5)	25 (10.2)	31 (12.7)	3.52	1.14
AI is used in the acquisition of library materials	84 (34.3)	112 (45.7)	33 (13.5)	12 (4.9)	4 (1.6)	4.06	0.94
AI is used in library decision support systems	33 (13.5)	99 (40.4)	83 (33.9)	20 (8.1)	10 (4.1)	3.51	0.97
AI is used in the circulation of library materials	72 (29.4)	133 (54.3)	14 (5.7)	24 (9.8)	2 (0.8)	4.01	0.94
AI is used in library security and surveillance	85 (34.6)	110 (44.9)	36 (14.7)	7 (2.9)	7 (2.9)	4.05	0.96
AI is used in bibliographies and anthologies	95 (38.8)	95 (38.8)	43 (17.5)	10 (4.1)	2 (0.8)	4.10	0.93
AI is used to find citations	70 (28.6)	95 (38.8)	43 (17.5)	22 (9.0)	15 (6.1)	3.74	1.06
AI is used in research data management	111 (45.3)	108 (44.1)	8 (3.3)	15 (6.1)	3 (1.2)	4.26	0.93
AI is used in digital asset management	94 (38.4)	92 (37.6)	25 (10.2)	20 (8.1)	14 (5.7)	3.94	1.07
AI is used in content summarization	90 (36.7)	115 (47.0)	21 (8.6)	12 (4.9)	7 (2.8)	4.09	0.96
AI is used in language translation	40 (16.3)	158 (64.5)	42 (17.2)	5 (2.0)	0 (0.0)	3.95	0.80
AI is used in the writing of systematic literature reviews	74 (30.2)	113 (46.1)	12 (4.9)	36 (14.7)	10 (4.1)	3.83	1.06
AI is used in search engines	85 (34.7)	160 (65.3)	0 (0.0)	0 (0.0)	0 (0.0)	4.34	0.68
AI is used in library databases	61 (24.9)	96 (39.2)	38 (15.5)	18 (7.3)	32 (13.1)	3.55	1.13

Table 2 provides an overview of the ‘perception of AI’ among the LIS professionals. The majority of the respondents indicated that AI could be used to overcome LIS professionals’ performance disparities and could make things easier, with an average of 35.5% of the respondents in agreement. However, most of the respondents indicated that AI made LIS professionals lazy and threatened their employment, with an average of 38.2% in agreement. The respondents also indicated barriers to the adoption of AI in libraries, such as the lack of LIS professionals’ skills in AI, budgetary constraints, high energy requirements, and a scarcity of vendors specializing in AI, with an average of 49.8% in strong agreement.

Table 2.

Perception of AI among LIS professionals.

Statements	Strongly agree (%)	Agree (%)	Neutral (%)	Disagree (%)	Strongly disagree (%)	M	SD
AI robots can fill librarian shortages	61 (24.9)	47 (19.2)	33 (13.4)	72 (29.4)	32 (13.1)	3.13	1.18
Librarian roles can be performed more effectively by AI robots	20 (8.2)	75 (30.6)	64 (26.1)	58 (23.7)	28 (11.4)	3.00	1.07
AI robots can work alongside librarians in the future	47 (19.2)	95 (38.8)	60 (24.5)	22 (9.0)	21 (8.5)	3.51	1.07
AI can bridge librarian performance gaps	33 (13.5)	117 (47.7)	41 (16.7)	44 (18.0)	10 (4.1)	3.48	1.02
AI makes library staff lazy	100 (40.8)	112 (45.7)	24 (9.8)	6 (2.5)	3 (1.2)	4.22	0.90
Budgeting is an issue in adopting AI in libraries	113 (46.1)	45 (18.4)	87 (33.5)	0 (0.0)	0 (0.0)	4.10	0.94
The lack of LIS professionals’ skills and knowledge is the reason for not adopting AI in libraries	42 (17.1)	74 (30.2)	70 (28.6)	34 (13.9)	25 (10.2)	3.30	1.09
AI is a threat to librarians’ employment	75 (30.6)	69 (28.1)	31 (12.7)	26 (10.6)	44 (18.0)	3.42	1.20
The scarcity of vendors specializing in AI is the reason for not adopting AI in libraries	115 (46.7)	60 (24.5)	56 (22.9)	5 (2.0)	9 (3.7)	4.08	1.02
The high energy demand for AI technology is the reason for not adopting AI in libraries	182 (74.3)	37 (15.1)	24 (9.4)	1 (0.4)	1 (0.4)	4.65	0.84

Table 3 provides an overview of the competencies required by library professionals in the AI era. The majority of the respondents (an average of 65%) were in strong agreement that electronic communication, hardware and software, Internet applications, computing and networking, cyber security and network management, data quality control, data curation, database management systems, designing AI mechanisms, data analysis and algorithms, data handling, and data mining are the necessary competencies required by LIS professionals for them to be proficient in AI – hence the need to integrate education on AI in LIS programmes.

Table 3.

AI skills required by librarians in the AI era.

Statement	Strongly agree (%)	Agree (%)	Neutral (%)	Disagree (%)	Strongly disagree (%)	M	SD
Electronic communication	205 (83.7)	24 (9.8)	12 (4.9)	4 (1.6)	0 (0.0)	4.75	0.78
Hardware and software	212 (86.5)	21 (8.6)	11 (4.5)	1 (0.4)	0 (0.0)	4.81	0.71
Internet applications	159 (64.9)	58 (23.7)	24 (9.8)	1 (0.4)	3 (1.2)	4.50	0.88
Programming skills	156 (63.7)	54 (22.0)	35 (14.3)	0 (0.0)	0 (0.0)	4.49	0.85
Computing and networking	192 (78.4)	17 (6.9)	36 (14.7)	0 (0.0)	0 (0.0)	4.63	0.84
Cyber security and network management	195 (79.7)	45 (18.3)	0 (0.0)	5 (2.0)	0 (0.0)	4.75	0.74
Data quality control	200 (81.6)	37 (15.1)	8 (3.3)	0 (0.0)	0 (0.0)	4.78	0.69
Data curation	180 (73.5)	64 (26.1)	1 (0.4)	0 (0.0)	0 (0.0)	4.73	0.67
Database management systems	171 (69.8)	28 (11.4)	46 (18.8)	0 (0.0)	0 (0.0)	4.51	0.88
Designing AI mechanisms	121 (49.4)	30 (12.3)	52 (21.2)	28 (11.4)	14 (5.7)	3.88	1.13
Data analysis and algorithms	79 (32.2)	85 (34.8)	49 (20.0)	32 (13.0)	0 (0.0)	3.86	1.00
Data handling	115 (46.9)	80 (32.7)	30 (12.2)	12 (4.9)	8 (3.3)	4.15	1.01
Data mining	108 (44.1)	94 (38.4)	19 (7.8)	18 (7.3)	6 (2.4)	4.14	1.00

Discussion

The conclusions of the descriptive data analysis, which highlight the significance of the adoption of AI in libraries for LIS professionals, are covered in this section. Before going on to other issues, the initial focus was to ascertain what essential understanding library professionals had of AI. The respondents were also questioned on their opinions of AI technology, the skills needed and the barriers to AI adoption in libraries.

Table 1 provides an overview of the theme of ‘awareness of AI’ among the library professionals. According to Wkiquote, AI is ‘an area of research in computer science’. AI aims to make robots capable of thinking like people, including learning, logical thinking and self-correction. One may argue that basic AI expertise is something that librarians already possess. The respondents showed that they understood AI to refer to intelligent devices or robots. Prior research in Pakistan indicates that chief librarians were familiar with voice search, text data mining, big data, cloud computing and Google Assistant, but not robotic AI and chatbots (Ali et al., 2020). According to earlier studies in Canada, librarians characterized AI in terms of how it functioned, its place among other AI goods and technologies, and what it signified (Ajibade and Mutula, 2020; Hervieux and Wheatley, 2021). The respondents in this study showed that they recognized the definition of AI as a machine that imitates human behaviour and that AI’s purpose is to support humans in their jobs, particularly data processing.

From the results, it can be inferred that the respondents thought AI was advantageous for libraries, particularly in terms of its use for routine library tasks such as circulation services, acquisitions, weeding and the registration of new members, among others, which freed up the respondents to work more productively on library development. This is in line with various research projects on how AI technology may be used in catalogues and categorization to classify library resources (Chaoying, 2021). It is clear from the responses that the respondents indicated that several library data sets were not analysed because of a lack of time, resources and energy, and could not be used for service development and decision-making. This supports the need for librarians and library directors to use AI in their data processing.

AI can be useful for research support by providing expertise on study subjects and facilitating the quick and accurate retrieval of relevant information. This has been demonstrated in previous research studies investigating the use of AI in research services. AI can also analyse large data sets, identify patterns and trends, and make predictions, aiding the research process. Additionally, AI-powered tools such as natural language processing and machine learning can help researchers to extract insights from unstructured data sources, such as text and social media data, which can help to enhance the quality and depth of research findings (Fernandez, 2016; Iantovics et al., 2016). Previous research, which discovered that intelligent talking robots were a sensible choice for reference services, provides proof that the benefits of AI may also be realized in the field of information services (Yao et al., 2015).

Research has shown that AI can be used in libraries for a variety of purposes, including cataloguing, classification, indexing, referencing and acquisition processes (Mogali, 2014), search engines in digital libraries (Wu et al., 2015), information literacy (Honghai, 2020; Yueh et al., 2020), library marketing (Omehia and Mmejim, 2020), public relations (Guth and Vander Meer, 2017) and content creation (Hilt, 2017). This study found that adopting AI applications provides benefits, particularly for managing libraries, organizing human resources and career development, and managing physical infrastructure, including buildings, rooms and equipment. Systems for making decisions that are important to this management role can employ AI (Herron, 2017).

Table 2 presents an overview of the perception of AI among library professionals. This is evident from their unanimously positive responses to the items listed ‘AI can overcome librarians’ performance disparities’, the respondents believed that AI could make things easier. According to the respondents, AI has the potential to address performance disparities among librarians, as they believed it could simplify tasks. The findings from the survey indicate that librarians highly value the ease that AI brings. According to earlier studies, AI technology can increase efficiency and production in a variety of industries, including banking (Mor and Gupta, 2021), manufacturing (Long et al., 2020) and agriculture (Lakshmi and Corbett, 2020). Libraries can benefit from the increased adaptability, efficiency and creativity resulting from the application of AI (Chen and Shen, 2020; Yu et al., 2019).

Library users also benefit from AI applications in terms of convenience, such as obtaining rapid round-the-clock service and swiftly and correctly accessing dependable information sources. A library’s prompt response can enhance community library users’ experiences and help with content production (Nguyen, 2020; Peltonen and Wickström, 2014). The results of past research indicate that, even though a few.

Table 3 provides an overview of the competencies required by library professionals in the AI era. AI has the potential to be used in libraries, but this is not possible without the competence of librarians, which involves both technical and soft skills. The use of information technology in libraries, as well as its evolution, must be understood by librarians. Additionally, they must be proficient in AI, including having an understanding of AI, AI tools and technologies, data analytics, library management, user behaviour and system architecture. It can be challenging to explain AI to those who do not work in information technology, programming or computer science because it has its roots in these fields; yet with the right training, anybody with or without such a background can use AI in their work (Long and Magerko, 2020).

In addition to competence, soft skills are linked to the adoption of AI, with the idea that if librarians have these skills, the adoption of AI in libraries will be simpler. Soft skills include creativity and innovation, critical thinking, cooperation, communication and an adaptable attitude towards technological advancements. In the information and communications technology era, librarians’ soft skills include communication, leadership, interpersonal and presentation skills (Satishkumar and Machendranath, 2018). In the AI era, librarians must be flexible or able to adapt and open to new technology, rather than rejecting AI because they think it will cost them their job. There have not been many studies on librarians’ soft skills and competency in the age of AI. Still, some have discovered evidence of information and communication technology proficiency (Oyedokun et al., 2018), professional competence in digital libraries (Khan and Bhatti, 2017), and librarians’ professional abilities, such as communication, presentation, marketing and leadership skills (Kulkarni et al., 2017). The results of this study show that, among other things, it is not only essential but also a requirement that modern LIS professionals be information-technology-savvy, have a solid understanding of data analytics, be able to manage a library, understand user behaviour and system design, and be able to think creatively and be adaptable.

Implications

This study was designed to gather statistical information on LIS professionals’ knowledge, perception and skills. The inquiry intended to investigate the relationship between awareness, perception and AI skills in libraries. The goal of this research was to equip policymakers and LIS stakeholders at large with factual information on the study’s outcomes.

The findings show that the LIS professionals were aware of AI in libraries and indicated that AI is essential for the effectiveness and efficiency of library service delivery, enabling libraries to enhance and offer dynamic services for library users. The LIS professionals also indicated that AI could overcome their performance disparities and make things easier. However, there were concerns that AI made LIS professionals lazy and threatened their jobs.

The findings also show that the LIS professionals were aware of the barriers to adopting AI in libraries, such as their lack of AI skills, budgetary constraints, high energy requirements and a scarcity of vendors specializing in AI. Moreover, the LIS professionals were very aware of the necessary competencies required for them to be proficient in AI, such as knowledge of electronic communication, hardware and software, Internet applications, computing and networking, cyber security and network management, data quality control, data curation, database management systems, designing AI mechanisms, data analysis and algorithms, data handling, and data mining – hence the need to integrate education on AI in LIS programmes. The study’s findings will help policymakers and LIS professionals to improve library service delivery and thereby libraries’ effectiveness and efficiency, as well as add to the body of knowledge, as it will contribute to future research in this field of study.

Conclusion

In this study, the LIS professionals who responded to the survey were often early adopters of new information and communications technology, and were quite open to the idea of using AI in library operations. The study shows that LIS professionals were aware of the skills required to adopt AI technologies, hence their eagerness and preparedness to take the lead role, which is contrary to what Cox et al. (2018: 426) suggest when they say that ‘IT [information technology] services might be in a greater natural position to take on some of these [AI management] duties’. However, this study also shows that LIS professionals were concerned that AI could threaten their jobs, with the fear that most of their roles could be replaced by intelligent machines.

As it is frequently these people who assess if an innovation has value, the motivation for the acceptance of an innovation like AI falls entirely on library professionals, who are sensitive, informed and understand the requisite abilities to implement AI technology. There is strong evidence that LIS professionals perceive AI as playing a significant role in library services in the future based on the study’s favourable findings on its usage in various library-related contexts. However, despite this study setting a strong trajectory for future research in this field, it focused on Zambian LIS professionals. This sample is not representative enough to draw general conclusions from the findings. Hence, the study provides a good literal foundation for representative research with a wider sample and more robust research on AI and its applications in LIS.

Footnotes

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Funding

The authors received no financial support for the research, authorship and/or publication of this article.

ORCID iD

A Subaveerapandiyan

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