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Artificial Intelligence in Social Media and its role in Digital Marketing

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Artificial Intelligence in Social Media and its role in Digital Marketing

Introduction

Artificial intelligence is transforming social media and digital marketing by helping brands understand their clients better and create more personalized experiences that increase sales and loyalty. However, the over-reliance on technology exposes users to the risk of data breaches and cyber-attacks (Tabrizchi & Kuchaki, 2020). Marketing is an essential part of business operations as it is instrumental in performance and business outcomes. Artificial intelligence is essentially the future of marketing. As such, it is integral that there is a better understanding of how it factors into social media and the influence it has in digital marketing. The problem is that the reliance on the utilization of artificial intelligence has been immense in recent times, notwithstanding the drawbacks associated with the technology. The key issue involved data privacy. The use of AI entails dealing with large amounts of customer data that need to be in safe hands, but privacy has affected the use of this technology in social media marketing. In 2022, approximately $4.4 million was the total cost associated with the breach of privacy with respect to the utilization of AI (Tabrizchi & Kuchaki, 2020). The issue was experienced in the US. The significance of the research is in the fact that this technology will undoubtedly continue playing a central role in social media marketing. The problem of data privacy needs to be addressed as minimizing the risks related to privacy when using AI in social media, and digital marketing is privy to better organizational outcomes.

Background

Root Cause of Problem

Humanity is in an age where technological developments come in leaps and bounds. The analytical process traditionally applied in the marketing process has been replaced with a digitalized process featuring social media use. Artificial intelligence has made a huge impact across different aspects of the lives of human beings apart from marketing. This goes to show just how significant this technology has been in transforming how individuals and entities function. These developments have resulted in marked differences from the past as technology has significantly improved the marketing process, especially in light of the importance of social media. The popularity has grown drastically as more than 80% of the major organizations across the US use AI in social media marketing. While previously, the marketing process involved the marketing personnel doing all the necessary tasks to promote a business, AI has helped make the process predicated on machine learning.

Figure 1:Global artificial intelligence market size and forecast (Tabrizchi & Kuchaki, 2020).

The chart represents the increase in the adoption of AI across the globe with respect to AI market size. This graph depicts the growth in reliance on artificial intelligence over time. The measure is in compound annual growth rate (CAGR). The graph indicates that from around 2016, the use of AI has grown drastically, resulting in tremendous market size growth. The forecast also shows that the use of AI will steadily continue to rise in the next few years (Tabrizchi & Kuchaki, 2020).

Figure 2: Data Breaches and Identity Theft Reports (Tabrizchi & Kuchaki, 2020)

The use of AI has grown more popular year after year. Over the same period, the issue of data privacy has become more pronounced as the number of data breaches has also risen, as can be observed from the figure above. The figure shows that the increase in the usage of AI is correlated to the increase in data breaches. The measures that are represented include the total number of breaches and reports of identity theft over the course of the last two decades (Tabrizchi & Kuchaki, 2020). The research is vital because it should expand the knowledge on the utilization of AI in social media marketing. The knowledge can help address the shortcomings, such as data privacy issues that arise with the utilization of AI.

Literature Review

Introduction to Literature Review

Social media marketing has rapidly become an integral part of organizations' marketing process (Fashami et al., 2022). Social media has proven to be a powerful tool for marketing businesses. Still, there is a need for a better understanding of the functionalities of this media in regard to marketing. This reviews examines the role and impact that social media marketing plays in organizations. Data for this review was obtained by researching various topics, including capabilities of social media marketing, social media responsibility, and marketing.

The literature review consists of articles covering the usability of social media marketing. The key factors entailed the usage of AI in various digital engagements. Some of this engagement but not limited to social media marketing, consumer engagement using digital content marketing, and integration of social responsibility in digital marketing. The research databases where the articles were gathered include Scopus, EBSCO Host, and ProQuest. The featured keywords and search terms were social media marketing, digital marketing, content marketing, and social media advertising. The choice of featured articles entailed the consideration of scholarly works and peer-reviewed journals.

Review of Literature

Capabilities of social media marketing

Capatina et al. (2020) used a multi-method approach to study the possibilities and expectations associated with machine learning and social media marketing. Capatina et al. (2020) sought to investigate the perceptions of AI technology in social media marketing. The authors used focus groups and surveys to collect research data. The focus groups took place in 2018 and featured 30 experts on AI technologies and social media marketing. The surveys were also conducted in 2018, whereby the participants responded to online questionnaires through personalized invitational e-mails that were directly sent to owners of digital agencies and social media marketers. There were 180 responses to the e-mails (Capatina et al., 2020). The participants were from Italy, France, and Romania. The variables associated with the profile of participants included country, age, current position, experience in years, and frequency of using AI software in social media marketing. Capatina et al. (2020) applied the Fuzzy-sets Qualitative Comparative Analysis methodology to explore the future capabilities of AI-based software. The software capabilities were distributed into audience analysis, image analysis, and sentiment analysis. Image analysis capabilities of the software were regarded as the most influential among potential users from Romania. Sentiment analysis, on the other hand thought to be most influential by the French (Capatina et al., 2020). The potential Italian users regarded the audience analysis capabilities to be the most influential. In each case, there was a different combination of capabilities found under the choices of audience analysis, image analysis, and sentiment analysis.

Fashami et al. (2022) conducted a study to come up with a digital content marketing framework for consumer engagement with brands on social media. Like Capatina et al. (2020), their focus was also on expounding on the capabilities and understanding of social media marketing. Fashami et al. (2022) used the Bibliometrix package of R and VOSviewer software to identify and map out the science performance and the scientific network. They applied the systematic bibliometric review to identify and analyze thematic trends in digital content marketing and brand engagement. The methodology involved the conduction of performance analysis first before the mapping of science takes place. The performance analysis entailed an examination of the role that authors have played, countries, institutes, and their contribution to a particular field of science. The mapping process is about gaining more perspective on the intellectual structure and the developments that have taken place at every period. The research classified the five clusters that are essential in developing a conceptual digital content marketing framework. The ADO-TCM framework helped determine the five components. The five clusters were content characteristics, social media characteristics, online community characteristics, consumer characteristics, and source characteristics. The performance analysis showed that the United States, China, and the United Kingdom were atop the list. Fashami et al. (2022) also found out that culture and artificial intelligence play key roles in influencing the digital content marketing process.

Social responsibility and social media marketing

Rahmani et al. (2023) conducted their study to explore the integration of social sustainability in the digital marketing process. The basis of the study was small businesses in Iran. They used a descriptive survey and qualitative approach to determine the components and dimensions that factor in the integration of social responsibility in digital marketing. The researchers used semi-structured interviews to collect data from 11 participants. The data from the interview was coded using open coding, selective coding, and axial coding (Rahmani et al., 2023). The qualitative analysis started with data collection, followed by open coding, axial coding, and selective coding. Across these stages, MAXQDA software was used to perform the qualitative analysis. Open coding determined that there are eight main categories and 37 subcategories (Rahmani et al., 2023). The categories associated with integrating social responsibility included digital marketing, environmental function, social performance, commercialization strategies, business competitiveness, service delivery, and development quality, and economic performance (Rahmani et al., 2023). The findings from the interviews were used to develop the model for the integration of social responsibility in digital marketing. The model was made up of various aspects, such as contextual conditions, intervening conditions, and consequences or outcomes (Rahmani et al., 2023). Each of these aspects had major categories which were regarded as being most essential. The takeaway from the study regarding social responsibility is that small businesses in Iran should use target marketing, establish measures to cut down on the use of energy and raw materials, and align their practices with entities with good environmental performance indexes. In addition, Rahmani et al. (2023) indicated that companies should train their workers on green behavior and environmentally friendly use of materials.

Analysis of Literature

Social media marketing has become quite integral in marketing, as indicated across all three articles. As Fashami et al. (2022) state, digital content marketing is important, but the body of literature is scattered. This is reflected in the focus areas of the articles. All articles suitably addressed their subject areas and helped improve the understanding of social media marketing. While the general subject revolves around the applicability of social media marketing, Fashami et al. (2022), Rahmani et al. (2023) and Capatina et al. (2020) approach the topic from different standpoints. The study by Capatina et al. (2020) is more future-oriented as they investigated the future usage of software and the perceptions of users. In contrast, Fashami et al. (2022) were more focused on maximizing the current potential of social media marketing by using a marketing framework to enhance consumer engagement. Rahmani et al. (2023) on the other hand introduced the element of social responsibility in digital marketing.

The methodologies used in the research papers also varied. Capatina et al. (2020) use focus groups and online surveys, while Fashami et al. (2022) use a systematic bibliometric review to conduct their study. Rahmani et al. (2023) also applied a different method as they used semi-structured interviews in the data collection process. Capatina et al. (2020) presented key capabilities of individuals in Italy, France, and Romania with respect to their perception of the future capabilities of AI-based software. The results from Fashami et al. (2022) are indicative of a different aspect as they pinpoint the most important considerations when building a content marketing framework. The results by Fashami et al. (2022) and Capatina et al. (2020) were established on individuals' perceptions of the essential features of social media marketing. They also focused on the contribution of AI to social media marketing. Rahmani et al. (2023) brought forth a different perspective by putting together two subjects in social media marketing and social responsibility together.

Discussion

The last few years have seen a rise in concerns associated with the privacy of social media users. The concern has revolved around the increase in data breaches, as numerous incidents have been reported. To make matters worse, the cases are generally on the rise, and the impact of privacy breaches has been immense. Given that artificial intelligence application in social media marketing depends on data collected from social media usage, privacy breaches pose a challenge to the efficacy of this technology. Privacy issues have affected the trust of social media users and resulted in perceptions of losing control of their personal data. The majority of social media users are concerned about businesses accessing their data.

There are several risks and threats associated with social media, which shows that this is a major problem. One of them is data mining. As individuals use social media, they leave a data trail behind, which is reflective of personal details. The data that companies collect on user behavior is usually stored and leveraged for better marketing, but at a time, third parties gain access to the information (Tabrizchi & Kuchaki, 2020). Malware sharing is a common problem that affects data on social media. The malware is capable of gaining access to data and subsequently compromising individual or organizational accounts. The malware can be used for extortion (Tabrizchi & Kuchaki, 2020). The impact of data breaches on artificial intelligence is also evident in regard to bot attacks. Social media bots are automatic accounts that create posts and follow new accounts at the mention of specific terms (Liu et al., 2021). Bots and botnets are used to send spam, launch DDoS attacks, and steal data. The attacks enable hackers to access the networks and devices of individuals and organizations. The attackers can steal the identities of individuals, sell data to other parties or take hostage of data for a price (Liu et al., 2021). All these forms of attacks result in the loss of private data and the number of costs millions of dollars on top of the exposure of confidential details.

Figure 3: Average Total Cost of a Data breach (Violion 2022).

The figure shows the average costs of privacy breaches in the US alone. From the look of it, the costs have fluctuated over the last five years but have remained fairly high. It indicates that 2022 has seen the highest figure yet in regard to the average costs of the data breach (Violion 2022). The figures are in millions of dollars.

The population affected by the problem in this study entails organizations that use AI in social media marketing and individuals whose data is accessed without authorization. The issue is affects entities in any corner of the world as long as they are connected to the social media accounts of other users. The main findings from the study show that AI is continually becoming a major tool for utilization in social media marketing. More companies are using technology to improve their marketing process. However, the continued use of AI in social media results in more exposure to the data breach risks. From the previous image, data breaches are trending upward; thus, organizations are likely to suffer from more unauthorized access to social media users' data.

Recommendations

According to Violion (2022), the American Data Privacy and Protection Act has been applied to improve data privacy. Under the policy, different strategies for securing data were advanced and have been utilized to promote compliance with the goal of reducing the problem of data breaches. The Act established national standards and safeguards when it comes to personal information that is collected by companies (Violion, 2022). The guidelines provided under the policy should be applied to enhance data protection. They include encryption and backing up of data, regular monitoring and analysis of data access and protection, and the use of standard operating procedures. The rules also cover the aspect of limiting the amount of data as volume increases the risk of data breaches.

Conclusion

Artificial intelligence will continue to play a key role in social media marketing in the near future as the rate of adoption is already quite high. The prevalence of data breaches is also quite high, and this negates AI in social media marketing. It is likely that the privacy of data will still be affected by breaches, whether intentional or unintentional. The financial impact of the breaches has been quite significant up to the moment. If the trajectory continues, as indicated in figure 1 which shows the global artificial intelligence market size and forecast, businesses will stand to suffer substantial losses. It is imperative that there are more stringent measures that will help prevent unauthorized persons from accessing private information. Future research should focus on enhancing the effectiveness of current practices in protecting private data and developing other strategies for the security of private information.

References

Capatina, A., Kachour, M., Lichy, J., Micu, A., Micu, A. E., & Codignola, F. (2020). Matching the future capabilities of an artificial intelligence-based software for social media marketing with potential users’ expectations.  Technological Forecasting and Social Change,  151, 119794. https://doi.org/10.1016/j.techfore.2019.119794

Fashami, R., Z., Haghighinasab, M., Seyyedamiri, N., & Ahadi, P. (2022). Designing a Digital Content Marketing Framework to Engage Consumers with Brands on Social Media: A Bibliometric Review. Journal of Business Management, 14(4), 573-601. https://jibm.ut.ac.ir/article_90590.html?lang=en

Liu, B., Ding, M., Shaham, S., Rahayu, W., Farokhi, F., & Lin, Z. (2021). When mahine learning meets privacy: A survey and outlook. ACM Computing Surveys (CSUR), 54(2), 1-36. https://doi.org1145/3436755

Rahmani, N., Vahabzadeh Munshi, S., & Mehrani, H. (2023). Integration of Sustainability in Small Business Digital Marketing: A Qualitative Study. International Journal of Digital Content Management, 4(6), 287-309. https://journals.atu.ac.ir/article_14943_57e1132bed944a4b13d0a9d794238cff.pdf

Tabrizchi, H., & Kuchaki Rafsanjani, M. (2020). A survey on security challenges in cloud computing: issues, threats, and solutions. The journal of supercomputing, 76(12), 9493-9532. https://doi.org/10.1007/s11227-020-03213-1

Violino, B. (2022) Data Privacy Rules are sweeping across the globe, and getting stricter, CNBC. https://www.cnbc.com/2022/12/22/data-privacy-rules-are-sweeping-across-the-globe-and-getting-stricter.html.