




































AMERICAN INTERNATIONAL JOURNAL OF BUSINESS AND MANAGEMENT STUDIES 6(1) (2024), 1-7 

 
1 

 

        Business and Management Studies 
                                                              AIJEFR VOL 6 NO 1 (2024) P-ISSN 2641-4937  E-ISSN 2641-4953 

                                                                                                                        Available online at www.acseusa.org      

                                                                                                                                     Journal homepage: https://www.acseusa.org/journal/index.php/aijbms 

                                                                                                                                             Published by American Center of Science and Education, USA 

ARTIFICIAL INTELLIGENCE AND THE FUTURE OF 

COMMUNICATION IN BUSINESS ADMINISTRATION: A 

COMPREHENSIVE REVIEW                                                             
                     

  Mir Mohtasam Hossain Sizan (a)1    Bizary Prava Mondal (b)    Md Rafiqul Islam  (c)    Md Rashed Buiya  (d)  
  
  (a)  Masters of Science in Business Analytics, University of North Texas, USA; E-mail: mhsizan855@gmail.com 
  (b) Masters of Science in Information Systems & Technology, University of North Texas, USA; E-mail: bizaryprava.99@gmail.com 
  (c) Department of Business Administration, International American University, Los Angeles, California, USA; E-mail: me.hanifislam@gmail.com 
  (d) Computer Science Department, California State University, Dominguez Hills, USA; E-mail: md.rashedbuiya124@gmail.com 

 

 
A R T I C L E I N F O 
 

 

Article History: 

 

Received: 6th July 2024 

Reviewed & Revised: 6th July 

to 8th September 2024 

Accepted: 10th September 2024 
Published: 17th September 2024 

 

Keywords: 

 

Artificial Intelligence, Communication 

Transformation, Quantitative Analysis,  

Workforce Education, Communication  

Business European Communication Professionals  

 

JEL Classification Codes:  

 

M10, M15 

 

Peer-Review Model:  

 

External peer review was done through  

double-blind method.  

 
A B S T R A C T 

 
As steam engines were introduced and the Industrial Age began, Mesopotamian manufacturing 

processes underwent significant changes. The mechatronics business is now experiencing a 

technological boom, thanks to recent breakthroughs in the internet, cellphones, electronics, 

nanotechnology, healthcare, digital applications, and other related technologies. Robotics and artificial 

intelligence were prominent topics during the last World Economic Forum, with major economists such 

as Stiglitz and Roubini making significant contributions to the discussion. The objective of the study is 
to determine the impact of artificial intelligence on communication sources related to business. The 

purpose of the research is also to find the answers of the following questions: How well do professionals 

know and use artificial intelligence? What influence does artificial intelligence have on communication 

management, say experts? What challenges do professionals face with artificial intelligence 

communication? What threats do the artificial intelligence use they see? The study has used the data set 

of a quantitative cross-national survey of 2375 European communication professionals. The study has 

applied the One-way ANOVA analysis with post-hoc Scheffé, Kendall rank correlation, Pearson 

product-moment correlation, and Pearson's chi-square tests. The results show that communication 
managers have driven artificial intelligence implementation and educate themselves and their 

workforce. There is a significant positive relationship between the use of artificial intelligence and 

business communication sources. The results the artificial intelligence has make a lot of improvement in 

communications systems and shows how the experts evaluate the technology. Research indicates that 

individuals employed in the field of communication have a limited understanding of artificial 

intelligence, although they possess a higher level of anticipation regarding its influence on their 

profession compared to its impact on their personal life. 
 

 

© 2024 by the authors. Licensee ACSE, USA. This article is an open-access article distributed under 

the terms and conditions of the Creative Commons Attribution (CC BY) license 
(http://creativecommons.org/licenses/by/4.0/).                           

 

INTRODUCTION 

Artificial intelligence is becoming increasingly integrated into all areas of our lives, spanning from everyday activities to 

industries such as manufacturing, service, and retail. Language-based assistants like Siri and Alexa, as well as algorithms 

used in news sites and e-commerce platforms, are just a few examples of the advancements in artificial intelligence. An 

increase in patents related to artificial intelligence, a rise in job opportunities in the field, and a boost in positive media 

attention surrounding AI concerns (Dwivedi et al., 2021). There has been a noticeable increase in academic conferences, 

course enrollments, and research focused on artificial intelligence and its effects in various fields. AI has the potential to 

greatly influence the field of communication management (Salas-Pilco & Yang, 2022). Several uses of artificial intelligence 

have been highlighted by experts and trade publications. These include analytics, targeting, content generation, chatbots, 

assessment procedures, strategy formulation, and crisis management (Enholm et al., 2022). Although AI technologies have 

the potential to improve professional operations, there are those who believe that humans cannot be replicated or substituted 

by technology (Benbya et al., 2020). It is valuable to take into account the viewpoints of professionals in the field of 

communication. How knowledgeable are they in the field of artificial intelligence? Is the level of adoption of this technology 

satisfactory? How do they perceive the challenges and dangers that AI poses to the field? The aim of study is to evaluate the 

                                                      
1Corresponding author: ORCID ID: 0009-0003-1444-6791  
© 2024 by the authors. Hosting by ACSE. Peer review under responsibility of ACSE, USA.  

https://doi.org/10.46545/aijbms.v6i1.316  

 
To cite this article: Sizan, M. M. H., Mondal, B. P., Islam, M. R., & Buiya, M. R. (2024). ARTIFICIAL INTELLIGENCE AND THE FUTURE OF 

COMMUNICATION IN BUSINESS ADMINISTRATION: A COMPREHENSIVE REVIEW. American International Journal of Business and 

Management Studies, 6(1), 1–7. https://doi.org/10.46545/aijbms.v6i1.316 
 

http://creativecommons.org/licenses/by/4.0/)
http://creativecommons.org/licenses/by/4.0/)
https://www.openaccess.nl/en
https://doi.org/10.46545/aijbms.v6i1.316
https://orcid.org/0009-0003-1444-6791
https://orcid.org/0009-0004-1675-0786
https://orcid.org/0009-0000-3730-4460
https://orcid.org/0009-0004-9747-0785


  Sizan et al., American International Journal of Business and Management Studies 6(1) (2024), 1-7

  

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existing literature on AI in communication management and present the findings of a quantitative survey conducted among 

2375 practitioners in European countries. The study attempts to address these concerns and communication professionals' 

perspectives by answering these research questions: How much do professionals know about AI and how much do they use 

it daily? How do experts estimate AI's influence on communication management? What are professionals' AI communication 

management challenges? What threats do they see? The study provides the theoretical foundation and ongoing research in 

two steps: First, to define artificial intelligence in corporate information and computer science literature. The study will then 

present communication management and examine AI research in this field. Using these approaches will reveal research gaps 

that the empirical investigation addresses. 

 

LITERATURE REVIEW 

The term "artificial intelligence" was coined by John McCarthy, an American computer scientist, in the 1950s, specifically 

in a proposal for the 1956 Dartmouth Conference. This symposium is considered the inception of artificial intelligence as a 

formal discipline, aimed at studying the development of computers capable of performing tasks that need human-like ability 

(Bhutani & Sanaria, 2023). McCarthy's proposal emphasized the development of computational frameworks that might 

imitate aspects of human learning and understanding. This distinguished the area from current studies in artificial 

intelligence and laid the groundwork for future research in computer-based intelligence (Anderson, 2024). Computer 

scientists David Poole and Alan Mackworth at the University of British Columbia describe AI as “computational agents that 

act intelligently. They define intelligence as competent action responding to circumstances and goals, adapting to changing 

environments and goals, learning from experience, and making good decisions (Mackworth & Zhang, 2001).  

 

Cluster of Technologies 

The artificial intelligence as a “cluster of technologies” that includes “natural language processing” and “machine learning 

(Goldfarb et al., 2023). The analytics and machine learning as AI components, while AI encompasses data perception. 

Machine learning is often viewed as a meta-concept that includes knowledge representation (Brown, 2021). AI may be 

defined as flexible decision-making processes and behaviors of software-driven agents, by considering several definitional 

methods. They adapt to shifting objectives and unpredictable environments, learn from experience, seek logic, and persevere 

despite perceptual and computational limits (Subramaniam, 2020). Natural language processing, data retrieval, knowledge 

representation, semantic reasoning, and machine learning underpin AI. Knowledge representation is a subset of machine 

learning, while software-driven agents may respond depending on their environment or prior experiences. However, 

integrating both abstract and physical AI features makes this definition theoretically broad and easy to grasp for non-IT 

professionals. Guiding all organizational messages is a crucial aspect of communication management (Yu, 2023). This 

material primarily focuses on the potential impact of artificial intelligence on communication management and professional 

responsibilities.  

 

Transformation of AI Technology 

The transformative impact of AI assistants on how corporations engage with their customers. AI-based marketing has the 

potential to enhance communications, enhance targeting, and utilize bots for consumer communication (Haleem et al., 2022). 

A significant portion of communication skills, 32%, can be accomplished without the need for technological assistance. 

Additionally, 27% of these skills do require some level of tech support. This suggests that despite advancements in 

technology, human involvement is still crucial in this area. The technology will have a minimal impact on the job market 

for communications professionals, accounting for only 1.5% of job losses. As indicated by human practitioners set 

themselves apart from robots by leveraging their creativity, critical thinking skills, and the trust they build with stakeholders 

(Van Laar et al., 2017). Few businesses have integrated AI into their communication departments, despite the potential. Only 

3% of Swiss corporations utilize AI for communications, according to a study conducted by Chief Communication Officers 

(Zerfass et al., 2020; Pande et al., 2024). 

 

Technological Administration 

Further investigation is necessary as communication professionals appear to encounter significant challenges when 

integrating AI. The adoption of technical advances by administrations is contingent upon their inherent qualities and 

resources, such as communication procedures and structures, as well as their external environment, which includes 

legislative restrictions and technology infrastructure (Melville et al., 2004). AI in communications may encounter challenges 

at the meso-, department-, and agency levels in addition to the macro-level social barriers. It is uncertain if practitioners are 

as sanguine about AI as industry journals and practitioner literature are, or if they are more afraid that AI will replace them 

in many activities and lead to lower pay, more unemployment, and a loss of professional identity. Administrations and their 

members may be in risk when new technology is introduced (Ernst et al., 2019). These five criteria—which account for a 

substantial 54% of the total—carry the most weight, and they include the concepts of leadership and service (Javed, 2024). 

One risk associated with managing IT projects personally is "lack of ability, training, motivation and experience of staff, AI 

may diminish human abilities, responsibilities, control, and self-determination. Understanding AI influences how it is 

viewed and what it means for the communications industry. The paucity of scientific literature and experience sometimes 

leads to variable and imprecise knowledge levels among practitioners (Lebovitz et al., 2021).  

 

Unified Theory of Adoption and Usage of Technology (UTAUT) 

It is necessary to look into this baseline and any variations related to the organizational histories of practitioners and their 

usage of AI devices. Theoretically, organizational technology adoption is influenced by disparities in experience, age, and 



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gender. These variables are used as moderators by the Unified Theory of adoption and usage of Technology (UTAUT) and 

its sequel, UTAUT2, to explain how various factors influence the adoption and usage of new information systems (Touray 

et al., 2013). The opinions on AI will differ between men and women, between younger and older professionals, and between 

those who have used AI devices and those who haven't. It is also assumed by the TOE paradigm that the way different types 

of administrations perceive AI in communication management may differ (Fristedt et al., 2021).  

 

MATERIALS AND METHODS 

The study questions were incorporated in a quantitative, cross-national online survey of European communication 

professionals. Most of the 2375 practitioners have more than 10 years of communications experience and hold key positions. 

 

Data Collection Process 

The AI survey has 6 questions. All of our research instrument questions came from the literature review. The Total poll's 

demographic questions were analyzed. To engage participants, the research employed a 5-point Likert scale from 1 to 5 to 

assess how AI affected their job, division, agency, and work style (micro, meso, or macro). A definitional question assessed 

AI knowledge: We provided participants eight AI traits—four right and four wrong—and had them choose their preferences 

based on the information. Proper definition eliminated knowledge difference bias. The perceived hurdles of reaching human 

(practice competencies and motivation), organizational (top-level management, leaders, and clients' support), and societal 

(users' and external stakeholders' tolerance) AI in communications standards. Each level had cognitive or motivational 

challenges after structural ones. On a 5-point Likert scale, 1 was "not likely" and 5 was "very likely. “Not likely" and "very 

likely" were Likert scale extremes. Independent factors include responder gender, age, and country of origin, firm type, and 

management level.  

 

Survey  

The online survey ran for five weeks between January and March 2024. The academics, students, and practitioners from 

various locations were excluded from the population, 2375 responses out of 2670 were used for data analysis. Females made 

up 55.16% of 1,523 participants and males 43.2% of 1,156. The average age was 75.7% of the population (N = 2,570) had 

an academic degree, with 63.2% having a master's or postgraduate degree (N = 1575) and 6.2% a PhD. 67.6% (N = 1,617) 

had more than 10 years of communications experience, and 67.6% (N = 1,620) were unit or team leaders or agency CEOs. 

The communication departments of seven out of ten professionals were employed by joint stock corporations (17.7%, N = 

541), private corporations (25.1%, N = 618), governmental administrations (16.6%, N = 447), or non-profit administrations 

(10.6%, N = 270). The remaining professionals (27.5%) were employed by communication consultancies, PR firms, or 

independent Total communication (36.2%, N = 1,027), strategy and coordination (31.7%, N = 652), media relations/press 

spokesperson (30.7%, N = 630), online/social media 26.2%, N = 705), and marketing/brand/consumer communication 

24.7%, N = 665 were the most frequently mentioned communication management subdisciplines. Southern Europe (31.4%, 

N = 645) and Western Europe (27.0%, N = 761) represented the bulk of responders, followed by Northern and Eastern 

Europe. 

 

Data Evaluation 

Data analysis was done with SPSS. Depending on the variable, one-way ANOVA with post-hoc Scheffé, Kendall rank 

correlation, Pearson product-moment correlation, and Pearson's chi-square test identified significant differences and 

(inter-)dependencies. 

RESULTS AND DISCUSSIONS 

Professionals in communication generally exhibit a fairly narrow grasp of artificial intelligence. They anticipate a bigger 

influence on the profession Total than on how their company or they operate. Key risks and obstacles include unclear duties 

and varying degrees of proficiency across businesses, as well as a lack of individual capabilities.  

 

AI Communication Specialist 

The 16.7% of the participants were classified as adopters of AI, indicating that they make use of both intelligent equipment 

in their homes and offices and intelligent assistants on their smartphones. Table 1 represents the considered "AI experts," 

15.4% of the professionals polled accurately identified seven or all eight of the stated features of AI as either true. The 

majority only had a rather hazy idea of what artificial intelligence is, and 7.1% of respondents, or "AI greenhorns," avoided 

the definitional issue entirely by saying they had no idea. Compared to female experts (16.7%), there are more male experts 

(16.3%). Adoption and skill in AI are unrelated; interestingly, we discovered that those who do not yet utilize the technology 

in their daily life have higher levels of AI expertise (15.7% versus 13.7%). 

 

Table 1. Represents the AI communication specialists’ details 

 
Agents operated by software make decisions and take actions. 66.76% 

Acquiring knowledge through experience  56.60% 

Human-assisted computer activities 54.73% 

Adjusting to shifting objectives and erratic circumstances 35.70% 

Comprehending normal language (Meaningful moods)  41.60% 

The whole range of human abilities 15.50% 

(Going through emotions) 10.70% 

The process of learning by doing 6.60% 



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As a percentage, the frequency is determined by the selection process. When people talk about "Artificial 

Intelligence," they often use different definitions. Pick out all the definitions that you believe fit the bill. When we talk about 

AI, it is referring about 15.4% of the total sample and 16.6% of the definition-selecting population are experts in artificial 

intelligence. Most of the people (36.5%) have gotten 5 out of 6 things right. Among those working in the field of 

communication, 41% anticipate that AI will impact PR and communications in general (M = 2.70, SD = 2.37, N = 2,566). 

The influence on the profession will be substantial, according to every second responder (50.6%). Distinct differences exist 

between the micro and meso levels of impact perception, which is an intriguing observation: Even fewer professionals 

(33.7%) think that artificial intelligence would drastically alter their own work processes (M = 2.73, SD = 1.20), and only 

29.2% expect that AI will cause major changes to the way their agency's or department's communication department operates 

(M = 3.05, SD = 2.01). There were noticeable variations among the different kinds of corporations and the respondents' 

varying degrees of hierarchy. Working professionals in joint stock firms report a higher degree of organizational and personal 

effect compared to practitioners in other types of administrations. Specifically, 40.3% of them estimate a high or very high 

level of influence at the meso level, and 29.1% at the micro level. When comparing communication leaders to their 

colleagues in lower-ranking positions, the same holds true.  

 

Projects of AI Organization 

According to Table 2, the projected effects of AI on macro, meso, and micro levels are ranked from highest to lowest by 

organizational hierarchy. 

 

Table 2. The effect that communication experts anticipate AI will have on the field. 

 
Artificial intelligence will have impact on Head of communication 

department / Agency CEO 

Unit leader / 

Team leader 

Team member / 

Consultant 

Total 

The profession of public relations and communications as 

a whole * 

2.76 2.73 2.73 2.63 

-2.34 -2.36 -2.36 -2.36 

The way our department / agency works ** 5.11 3.02 2.74 3.03 

-2.36 -2.37 -1.35 -2.01 

The way I personally work * 2.63 2.71 2.65 2.72 

-1.18 -2.36 -2.36 -2.01 

Note. P-value < 0.01. 
 

More than half of the respondents considered organizational infrastructure and communication practitioners' 

competencies (M = 3.56, SD = 1.04, N = 2,566) to be major barriers to implementing AI in communication management 

(M = 3.54, SD = 2.35). The subsequent tier is distinguished by support from leaders, consumers, and senior management 

(M = 3.25, SD = 2.36), approval from users and external stakeholders (M = 2.73, SD = 1.02), and encouragement to apply 

AI from communication practitioners (M = 3.27, SD = 2.36). It is uncommon (M = 2.63, SD = 2.36) to identify social 

infrastructure.  

 

AI Administration Problems 

Table 3 illustrates two areas where they score significantly higher: organizational infrastructure (F = (4; 2561) = 4.736; p < 

0.01) and assistance from leaders, clients, and senior management (F = (4; 2,561) = 3.666; p < 0.01). However, it's important 

to note that compared to individuals who have not used AI frequently, those who have used AI have reported fewer issues. 

 

Table 3. The challenges different administrations expect adopting AI in communications 

 
  Cooperative 

stock 

Secluded Legislative Non-profit Consultancy Total 

Corporations  Corporations Administrations  Administrations  & Agencies  

Competencies of communication 

practitioners to use AI 

3.61 3.5 3.61 3.6 3.57 3.56 

-1.03 -1.04 -1 -0.76 -1.06 -1.04 

Motivation of communication 

practitioners to use AI 

3.27 4.29 2.73 2.73 2.76 3.27 

-2.33 -2.33 -1.07 -1.06 -2.35 -2.36 

Organisational infrastructure (e. g. 

IT, budgets, responsibilities) ** 

2.76 3.5 3.66 3.76 2.63 3.54 

-1.35 -2.34 -2.3 -1.06 -2.37 -2.35 

Support by top management, 

leaders, and clients ** 

5.13 3.35 2.71 2.73 3.27 3.25 

-2.35 -2.31 -2.33 -1.06 -2.36 -2.36 

Societal infrastructure (e. g. high-

speed internet, legal rules) 

3.04 2.73 3.03 3.04 2.63 2.63 

-1.2 -2.37 -2.35 -2.35 -1.18 -2.36 

Acceptance by users and external 

stakeholders  

2.76 2.76 2.76 2.63 2.7 2.73 

-1.03 -1.02 -1.02 -0.76 -1.04 -1.02 

Note: The Scheffé post-hoc test showed significant results (p < 0.01). 

 

Major barriers to incorporating AI into communications include organizations with uneven staff expertise (M = 

2.74, SD = 2.33, N = 2,566) and jobs that are not clearly defined (M = 3.61, SD = 1.35). Disillusionment with identity (M 

= 1.99, SD = 1.25), a reduction in one's essential abilities (M = 1.97, SD = 1.20), and a drop in pay (M = 2.44, SD = 2.36) 

are additional risks. Table 4 represents the professionals view these obstacles as possible hazards. With an index score of 

2.60 as opposed to 2.67 and 2.75 for team leaders and members, respectively, top communicators had a more positive view. 



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Meanwhile, 46.7% of nonprofit professionals anticipate issues with unclear responsibilities and 61.5% of nonprofit 

professionals foresee challenges with different staff capability.  

 

AI Communication Risk 

Changes in work responsibilities might account for the second piece of information. Planning and review with AI assistance 

increases CEO time. In this era of data-driven communication, stakeholder participation and news story authoring and 

interpretation may become outdated. 

 

Table 4. Represents the AI-facilitated intergenerational communication risks. 

 
  27 or 30 - 29 40 - 47 50 - 57 60 or Total 

younger older 

Statement pros are suffering job losses ** 2.65 2.16 2.33 2.43 2.33 2.41 

-1.33 -2.36 -2.35 -1.2 -1.35 -1.2 

Communiqué GPs 2.62 1.97 2.43 2.46 2.32 2.44 

wages will decrease -1.3 -2.34 -2.35 -2.33 -1.24 -2.36 

Organisations will encounter challenges 2.63 2.76 3.51 2.73 2.71 2.74 

miscellaneous operate proficiency -1.07 -2.35 -2.33 -2.31 -1.18 -2.33 

Businesses will face challenges  5.15 3.06 5.15 5.16 4.29 3.61 

whose roles are not clearly defined -1.24 -1.18 -1.23 -2.01 -1.31 -1.35 

In the field of communications 2.63 2.17 1.97 1.96 2.17 1.97 

Determination drops fundamental competencies ** -1.26 -2.34 -2.01 -1.2 -1.3 -1.2 

The infrastructures occupation 2.61 2.32 2.36 2.33 1.97 1.99 

will lose its distinctiveness -1.29 -1.23 -1.18 -1.35 -1.31 -1.25 

Note: ** Highly significant at p < 0.01 using Pearson correlation. 

 

The respondents were categorized based on the indices of all questions that assess the impact and all things that 

assess the risks. Approximately 67.7% of practitioners expect to have some degree of impact, however they score low or 

neutral on the risk scale (with a risk index value of less than 3, reflecting a predominantly optimistic outlook within the 

profession. However, a small fraction of just 14.7% of those who oppose AI predict that the technology would have a 

substantial adverse impact and present several risks with both indices being more than 3. 

 

DISCUSSIONS 

There is a still significant untapped potential for artificial intelligence in the field of communication management. Based on 

our findings, experts in the industry believe that AI has the capacity to transform their work, and like the third-person effect 

of media influence (Perloff, 2009). A cognitive bias when we inquired about the anticipated impact in depth from 

professionals: they anticipate that AI would revolutionize their field, but not their specific organization. Although 

professionals may have stayed informed about the latest developments in their sector, they have not yet utilized artificial 

intelligence in their professional or personal endeavors. Currently, AI does not have significant attention in the field of 

communication management. The study pioneering quantitative research examined the impact of artificial intelligence on 

public relations and marketing research (Berente et al., 2021). The responsibility of communication executives is to integrate 

artificial intelligence into their department, and communicators themselves should acquire knowledge on the issue. Although 

there is extensive discussion about AI in trade periodicals, the bulk of public relations specialists still lack knowledge about 

this subject. The limited comprehension of big data, a technology linked to artificial intelligence, among communication 

professionals (Smith, 2020). Moreover, the effectiveness of 'learning by doing' approaches should be evaluated as the use 

of AI-based gadgets in daily activities does not lead to proficiency. The practitioners should acquire new technologies in a 

methodical manner. The primary obstacle to integrating AI into communication management is the proficiency level of 

individual specialists, which presents a substantial threat to enterprises (Alshahrani et al., 2024).  

 

CONCLUSIONS 

Despite AI's inability to replicate every skill of a human communicator, practitioners of AI can nonetheless achieve mastery. 

Despite challenges at the human and organizational levels, meeting societal needs appears to be occurring. High-speed 

internet, adherence to AI rules, and the endorsement of external stakeholders are of little concern to anybody in the 

communication business. While there may be some disagreement among practitioners, it is necessary to fully adopt and 

accept artificial intelligence at this point in time. There is a significant proportion of individuals do not harbor significant 

fears or concerns regarding artificial intelligence. Experts in the field of communication, who anticipate the most beneficial 

influence of AI on employment may need to educate and involve colleagues with varying levels of AI expertise and 

apprehension. A significant proportion of the research sample consists of individuals in their twenties and those who 

anticipate significant repercussions and several hazards. Paradoxically, the individuals who were labelled as "digital were 

the ones who expressed the highest level of concern regarding artificial intelligence. The biggest expected Organisational 

threats were concerns around worker competence and uncertainty surrounding positions and tasks. Effective team staffing 

and organization of AI work are essential tasks for communication executives. The support of top-level management and 

the presence of a designated project champion are essential for an organization to adopt technology. Multiple factors should 

be considered while assessing the outcomes of our inquiry. Due to the lack of information about the Total number of 

communication professionals in Europe and the low response rate from Eastern Europe, our sample cannot be used to 

accurately represent the communication profession from a statistical standpoint. Our technique exclusively assessed the 



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perspectives of communication experts. Although we included our AI definition in the poll, it is possible that other variables 

influenced participants' perception of risks and challenges, despite our efforts to prevent this. We refrained from inquiring 

about the extent of AI use in communication departments or agencies due to our expectation that a significant number of 

respondents would lack knowledge on the subject. The intricate technology adoption models offered in the literature analysis 

were too intricate for us to examine. The study primary goal was to provide individuals with an early advantage in AI for 

communication management. To advance both theoretically and practically, future study should expand the viewpoint on 

potential challenges and hazards, incorporate other elements, and establish connections with empirical evidence. 

 

 
Author Contributions: Conceptualization, M.M.H.S., B.P.M., M.R.I. and M.R.B.; Methodology, M.M.H.S.; Software, M.M.H.S.; Validation, M.M.H.S.; 

Formal Analysis, M.M.H.S., B.P.M., M.R.I. and M.R.B.; Investigation, M.M.H.S.; Resources, M.M.H.S.; Data Curation, M.M.H.S.; Writing – Original 

Draft Preparation, M.M.H.S., B.P.M., M.R.I. and M.R.B.; Writing – Review & Editing, M.M.H.S., B.P.M., M.R.I. and M.R.B.; Visualization, M.M.H.S., 

B.P.M., M.R.I. and M.R.B.; Supervision, M.R.B.; Project Administration, M.R.I.; Funding Acquisition, M.M.H.S., B.P.M., M.R.I. and M.R.B. Authors 

have read and agreed to the published version of the manuscript. 

Institutional Review Board Statement: Ethical review and approval were waived for this study, due to the fact that the research does not deal with 

vulnerable groups or sensitive issues. 

Funding: The authors received no direct funding for this research. 

Acknowledgement: Not applicable.  

Informed Consent Statement: Informed consent was obtained from all subjects involved in the study. 

Data Availability Statement: The data presented in this study are available on request from the corresponding author. The data are not publicly available 

due to restrictions. 

Conflicts of Interest: The authors declare no conflict of interest.                                                                                                                                                                                                                                   

 

REFERENCES 

Anderson, M. M. (2024). AI as Philosophical Ideology: A Critical look back at John McCarthy’s Program. Philosophy & 

Technology, 37(2), 44. https://doi.org/10.1007/s13347-024-00731-1 

Alshahrani, R., Yenugula, M., Algethami, H., Alharbi, F., Goswami, S. S., Naveed, Q. N., ... & Zahmatkesh, S. (2024). 

Establishing the fuzzy integrated hybrid MCDM framework to identify the key barriers to implementing artificial 

intelligence-enabled sustainable cloud system in an IT industry. Expert systems with applications, 236, 118732. 

Benbya, H., Davenport, T. H., & Pachidi, S. (2020). Artificial intelligence in organizations: Current state and future 

opportunities. MIS Quarterly Executive, 19(4). https://dx.doi.org/10.2139/ssrn.3741983 

Bhutani, A., & Sanaria, A. (2023). The Past, Present and Future of Artificial Intelligence. 

Brown, K. (2021). The Nature of Information, Semantics, and Effectiveness for Artificial Intelligence and Cognition.  

Berente, N., Gu, B., Recker, J., & Santhanam, R. (2021). Special Issue Editor’s Comments: Managing Artificial 

Intelligence. Management Information Systems Quarterly, 45(3), 1433-1450. 

Dwivedi, Y. K., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., ... & Williams, M. D. (2021). Artificial 

Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, 

practice and policy. International journal of information management, 57, 101994. 
https://doi.org/10.1016/j.ijinfomgt.2019.08.002 

Enholm, I. M., Papagiannidis, E., Mikalef, P., & Krogstie, J. (2022). Artificial intelligence and business value: A literature 

review. Information Systems Frontiers, 24(5), 1709-1734. https://doi.org/10.1007/s10796-021-10186-w 

Ernst, E., Merola, R., & Samaan, D. (2019). Economics of Artificial Intelligence: Implications for the Future of Work. IZA 

Journal of Labor Policy, 9(1), 1-35. https://doi.org/10.2478/izajolp-2019-0004 

Fristedt, S., Svärdh, S., Löfqvist, C., Schmidt, S. M., & Iwarsson, S. (2021). “Am I representative (of my age)? No, I’m 

not”—Attitudes to technologies and technology development differ but unite individuals across rather than within 

generations. Plos one, 16(4), e0250425. 

Goldfarb, A., Taska, B., & Teodoridis, F. (2023). Could machine learning be a general purpose technology? A comparison 

of emerging technologies using data from online job postings. Research Policy, 52(1), 104653. 
https://doi.org/10.1016/j.respol.2022.104653 

Haleem, A., Javaid, M., Qadri, M. A., Singh, R. P., & Suman, R. (2022). Artificial intelligence (AI) applications for 

marketing: A literature-based study. International Journal of Intelligent Networks, 3, 119-132. 
https://doi.org/10.1016/j.ijin.2022.08.005 

Javed, M. A. (2024). A Critical Analysis of the HVAC Business Model to Determine Its Success Criteria. The American 

Journal of Management and Economics Innovations, 6(05), 78-86. 
https://doi.org/10.37547/tajmei/Volume06Issue05-09 

Lebovitz, S., Levina, N., & Lifshitz-Assa, H. (2021). Is AI ground truth really true? The dangers of training and evaluating 

AI tools based on experts’ know-what. MIS Quarterly, 45(3b), 1501-1525. 
https://doi.org/10.25300/MISQ/2021/16564 

Mackworth, A. K., & Zhang, Y. (2001). Constraint-Based Agents: A Formal Model for Agent Design. UBC Computer 

Science Technical Report TR-2001-09. 

Melville, N., Kraemer, K., & Gurbaxani, V. (2004). Information technology and organizational performance: An integrative 

model of IT business value. MIS quarterly, 28(2), 283-322. https://doi.org/10.2307/25148636 

Perloff, R. M. (2009). Mass media, social perception, and the third-person effect. In Media effects (pp. 268-284). Routledge. 



  Sizan et al., American International Journal of Business and Management Studies 6(1) (2024), 1-7

  

7 
 

Pande, S., Moon, J. S., & Haque, M. F. (2024). EDUCATION IN THE ERA OF ARTIFICIAL INTELLIGENCE: AN 

EVIDENCE FROM DHAKA INTERNATIONAL UNIVERSITY (DIU). Bangladesh Journal of 

Multidisciplinary Scientific Research, 9(1), 7-14. https://doi.org/10.46281/bjmsr.v9i1.2186 

Salas-Pilco, S. Z., & Yang, Y. (2022). Artificial intelligence applications in Latin American higher education: a systematic 

review. International Journal of Educational Technology in Higher Education, 19(1), 21. 
https://doi.org/10.1186/s41239-022-00326-w 

Subramaniam, R. (2020). Are IT Entrepreneurs More Likely Than Non-IT Ones to Reattempt Entrepreneurship After a 

Failure? (Doctoral dissertation, University of Leicester). 

Smith, R. D. (2020). Strategic planning for public relations. Routledge. 

Touray, A., Salminen, A., & Mursu, A. (2013). The impact of moderating factors on behavioral intention towards internet: 

A transnational perspective. International Journal of Computer and Information Technology, 2(6). 

Van Laar, E., Van Deursen, A. J., Van Dijk, J. A., & De Haan, J. (2017). The relation between 21st-century skills and digital 

skills: A systematic literature review. Computers in human behavior, 72, 577-588. 
https://doi.org/10.1016/j.chb.2017.03.010 

Yu, W. (2023). IT management in a non-IT company (Based on SPEAK ONLINE case) (Doctoral dissertation, Private 

Higher Educational Establishment-Institute “Ukrainian-American Concordia University"). 

Zerfass, A., Hagelstein, J., & Tench, R. (2020). Artificial intelligence in communication management: a cross-national 

study on adoption and knowledge, impact, challenges and risks. Journal of Communication Management, 24(4), 

377-389. https://doi.org/10.1108/JCOM-10-2019-0137 

 
 

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