Revolutionising Digital Marketing Education with Generative Artificial Intelligence Integration: An Asynchronous Approach ^†

Abstract

The discipline of marketing has seen a significant shift toward the use of AI over the past 10 years, with generative AI such as ChatGPT exponentially accelerating the impact of this technology due to its accessibility and relevance in helping meet organisational and practitioners’ objectives. The objective of this project was to innovatively incorporate generative pretrained transformers (GPTs) into digital marketing education as a means of asynchronously exposing learners to advances in this domain but also provide insights into managing AI use in this field more effectively. This pilot study focused on supporting tourism enterprises in less developed countries (LDCs), specifically Botswana, Uganda, and Zambia.

1. Introduction

1.1. Background and Rationale

It is understood in this new epoch of artificial intelligence (AI) that its application in marketing is aimed at increasing one’s understanding of consumers (sentiment analysis), improving customer relationships and market performance, and ultimately supporting the better management of brands [1].

Since 2022, however, the use of AI has seen its application broaden in many business disciplines, including digital marketing, to embrace the opportunities presented by large language models (LLMs) and generative pretrained transformers (GPTs). These forms of AI can provide task support and research insight while supporting content development opportunities that reduce organisational burden to employ data scientists or computer engineers in order to deliver value at what is coming to be known as the jagged frontier of generative AI [2].

This frontier is considered jagged as generative AI models such as ChatGPT can significantly improve performance on some tasks but may not yet have the same capability on others. As educators, it is critical that we are part of this evolving frontier and experiment in ways to assist students and research partners to understand how to best exploit the opportunities of AI. To effectively achieve this, it is critical to be mindful of the variety of challenges that AI also brings.

Challenges of originality, plagiarism, and academic credibility are very much on the mind of most academics, as using AI is still an open debate in terms of value, pedagogical impact, and appropriateness in the classroom [3].

1.2. Importance of Integrating Generative AI in Education

AI has emerged as a critical technology for gaining a competitive edge, with its application soaring significantly. Growth, as evidenced by a rise in AI mentions in Russell 3000 earning calls, highlights this escalation in application. It rose from less than 1% to 16.63% between 2015 and 2023 [4], which underscores its increasing impact on business. Generative AI (Gen AI), particularly the platform ChatGPT due to its market penetration, has the potential to revolutionise business domains due to its ease of use and accessibility, serving functions from sales and marketing to operations and finance [5,6]. This research focuses on Gen AI’s integration into marketing education, inspired by its ability to enhance opportunity seeking, decision making, performance, and education for entrepreneurs [7].

Digital marketing, in particular, benefits from more entrepreneurial orientations enabled by Gen AI, offering opportunities for proactive and risk-measured resource utilisation. Gen AI’s multi-modal capabilities support scalable content creation across various media, fostering new customer value through a more entrepreneurial marketing approach [8]. However, the practical application of Gen AI in marketing education and practice remains underexplored and presents ethical challenges [9,10].

This research aims to bridge the gap between marketing pedagogy and practice by enhancing marketing skills through practical Gen AI application [11]. This study’s strategic focus is on using Gen AI to upskill and enhance marketing capacity, exploring its potential in asynchronous education experiences.

1.3. Aim and Objectives

The overarching aim of this research was to explore and implement transformative marketing technologies, specifically Gen AI, in the context of international tourism, with a focus on fostering sustainable practices and competitive advantage, particularly in less developed countries (LDCs) in Africa. This was achieved through a series of strategic workshops and marketing strategy development focusing on improving the brand appeal of participant businesses to international travellers by employing Gen AI in digital marketing strategy creation. Ultimately, the aim was to support participant tourism organisations address sustainability challenges linked to the United Nation’s Sustainable Development Goals (SDGs) through their commercial practice and activities in such a way as to assist them in better communicating sustainability to meet changing customer expectations [12].

The objectives of this study were the following:

• To design and conduct a series of asynchronous workshops aimed at enhancing participants’ skills and knowledge related to the strategic use of Gen AI in marketing;
• To explore the capacity to enhance marketing competence through practical Gen AI application (developing value propositions, competitor analysis, and strategic insights, focusing on sustainable marketing practices);
• To provide insights for more effective pedagogy support and the integration of Gen AI in asynchronous education.

In the process of delivering the above objectives to the cohort of learners in Zambia, Uganda, and Botswana, the aim was to foster a collaborative environment where participants could exchange ideas and engage with peers and experts. The platforms Blackboard Collaborate and Nearpod were selected for the implementation of asynchronous learning. These platforms facilitate the integration of diverse content, activities, and external links, while also allowing a “self-paced” option. This approach was deemed most appropriate given the location of the learners, who were based in Africa, and that of the educators, based in Europe [13]. In addition, to further facilitate communication between educators and participants and among the participants themselves, a WhatsApp group was created. This was previously found to enhance collaboration between educator and learners through the creation of a community and the sense of “collective” prevalent in African society [14].

2. Literature Review

2.1. Generative AI in Education

Given the pervasive nature of AI in society and its potential impacts (both good and bad), it is critical that educators gain a solid understanding of how its algorithms and analysis are impacting human experience. Around the pandemic period, Borenstein and Howard [15] noted that “although AI provides observable benefits, the collection, use, and abuse of data used to train and feed into AI, as well as the algorithm itself, may expose people to risks that they were not even aware existed.”

Beyond the challenges and opportunities, there is a short-term deficit in the access to, and engagement with, GPTs by many disciplines. Higher education offers an important space to experiment with exploring the integration of AI in practice for improved insight and competitive advantages [3].

Varying forms of AI, particularly generative pretraining transformers (GPTs) and Gen AI, are more directly pervading educational experiences, whether for students as a co-intelligence tool or learning aid and whether openly or in more hidden ways [10]. The use of AI in higher education has seen significant growth since the launch of ChatGPT in late 2022. Indeed, it has been shown that ChatGPT significantly impacts the learning of students. A recent study featuring Peruvian students noted that 71.30% of participants used ChatGPT for access to accurate and fast responses, due to it being free and easy to use [6].

Academics have recently debated the integration of Gen AI into higher education, as there is mounting evidence of a new era of student education through the transformation of aspects of its management and delivery, but this opportunity also presents significant challenges [9]. Some of the more significant challenges are addressing issues such as academic integrity, algorithmic biases, and crucially ensuring equitable access and positive outcomes for the entire student body [10].

On the positive side of the potential paradigm shift is the capacity of Gen AI to personalise the learning experience. Through its ability to create interactive content and facilitate assessments which are also more adaptive, AI can be applied in many ways that can potentially boost knowledge retention and learner engagement, but many challenges remain [15].

It is in this vein that this article will proceed to explore an example of such an experimental approach (through action research) focused on integrating the use and understanding of AI, targeting startups and tourism enterprises in developing countries. Firstly, we will discuss some of the literature on the adopted learning approach.

2.2. Asynchronous and Active Learning in Higher Education—Benefits/Challenges

Asynchronous learning is a form of learning that allows you to learn at your own pace and schedule, within a certain timeframe. An asynchronous learning network (ALN) is a form of e-learning experience that emphasises the use of internet-enabled elements to support class activities and discussions. Studies in marketing education have previously shown that “participation in the asynchronous setting relates significantly and positively to students’ academic outcomes”, such as final grades [16].

One of the key challenges of asynchronous learning is related to the quantity and quality of online interactions, which can undermine the aim of inquiry. Additionally, the challenge of keeping learners engaged emerges in online contexts, and, as such, there is strong pedagogic support for more active learning approaches to be applied [17]. Active learning sees students involved in their own education by encouraging their agency over applying and understanding learning materials. Linked to the higher levels of Bloom’s taxonomy [18], active learning often challenges students to develop their learning with a deeper mastery of curricular knowledge.

This is achieved by “applying concepts, analysing data, and creating novel synthesis or knowledge” [19]. It is with this focus that this study adopted the SOSTAC methodology of digital marketing as a means to provide an appropriate framework to stimulate the application of the various concepts explored within the asynchronous workshops [20]. SOSTAC is an acronym highlighting the steps to guide strategy development for marketers and stands for situation analysis, objectives, strategy, tactics, actions, and control.

3. Methodology

To facilitate a more involved approach with stakeholders, action research was undertaken due to its transformative approach to knowledge creation. The aim was to empower stakeholders and generate knowledge through action, rather than just understanding social arrangements [21]. Action research is a knowledge creation orientation that involves working with practitioners to effect the desired change and empower stakeholders. Some proponents of action research such as Bradbury-Huang [22] go as far as to propose that “only through action is legitimate understanding possible; theory without practice is not theory but speculation”. The current study focused on gaining valuable insight and experience that could support future theory development through a more action-oriented approach.

3.1. Participants

Subsequent to the initial call, 12 businesses/participants responded, and an online sign-up process was adopted. The welcoming email detailed the components of the programme as well as a short questionnaire designed to assess the participants’ current digital marketing competencies on a scale from 1 to 10. In addition, they also shared their primary digital marketing objectives (such as brand awareness, lead generation, sales conversion, customer engagement, content distribution, market research, customer retention, digital community building, positioning as a thought leader). The participants were also asked about their existing digital marketing strategies and how successful they were. This allowed for benchmarking against the development of digital skills following the completion of the programme.

As the focus of the onboarding process rested on the participants’ prior experience with AI, no demographic data were collected, such as age, educational background, or position within the business. The gender of the participants was inferred from the names collected during onboarding and future communications.

The signatories were all representatives of small and medium travel agents, travel-related startups, and tour operators located predominantly in Zambia, Botswana, and Uganda. They ranged from owners/co-owners to people in charge of the businesses’ marketing and communication.

The final list of participants comprised eleven tourism businesses located in Zambia and one in Uganda. Of the 12 representatives of these businesses, 5 were male, and 7 were female.

3.2. Phases of Implementation: Onboarding, Workshops, Flow, and Content

Following successfully securing funding from Ulster University, a research team was formed including academic advisors from the International Federation of IT in the Travel and Tourism (IFITT) network. Part of this advisory panel included the lead of chapters at IFITT who provided support in accessing startups and tourism enterprises in Africa. Following communication through the IFITT Africa chapter, 12 participants were recruited at the outset (who are all either running a startup or tourism enterprise or were in the process of setting one up).

Due to funding being available for a short 3-month period, an action research orientation was adopted, and 4 asynchronous workshops and 1 live follow-up workshop were proposed as the delivery model. The workshops were based on key topics identified by reviewing the requirements of digital marketing strategy and considered as integral to a more strategic approach to digital marketing.

The following topics (see

Table 1. Key frameworks and tools explored in the workshops.

Glossary of Terms	Description
SOSTAC®	A planning framework created by PR Smith for digital marketing that stands for situation analysis, objectives and strategy, tactics, action, and control.
PESTEL	A memory aid to study macro-environmental forces (political; economic; social; technological; legal; and environmental).
Unique Value Proposition	This is the unique benefit or value a brand offers to customers through its products and services.
RBV	A framework that helps determine how a firm can use its resources to gain a competitive advantage.
SWOT	A framework to explore internal strengths and weaknesses, as well as external opportunities and threats.
TOWS	A tool that helps organisations identify strategic options based on their strengths, weaknesses, opportunities, and threats.

) were integrated into a workshop structure that was informed by the SOSTAC model, which was created by author PR Smith [20] and is applied by companies like LinkedIn due to its more holistic treatment of digital marketing strategy.

For a more specific understanding of the flow and content delivered over the course of the 4 weeks of asynchronous workshops and the final live online event, please see Figure 1 below.

3.3. Interventions and Strategy Development

Following the onboarding process, the researchers had an overview of the participants and their digital needs, which allowed for the customisation of the material to be delivered via the workshops.

Four separate lessons were created in Nearpod, a platform which facilitated asynchronous delivery, allowing participants to engage with the content at their own pace (see Appendix A).

Each lesson was focused on a specific marketing theory and followed a pre-established pattern. The theoretical subject of each workshop was decided in such a way as to allow for a progressive build-up of the participants’ knowledge of marketing. In addition, AI tools were introduced in each workshop, and the participants were encouraged to explore the practical applications of these tools in relation to each theoretical concept.

Smith [20]’s SOSTAC methodology was presented as an overarching framework to be used to structure each digital marketing plan. This method ensured a comprehensive and systematic approach to participants’ marketing efforts. By integrating the insights gained from industry analysis and applying the SOSTAC methodology, businesses could effectively establish their unique value proposition (UVP), distinguish their offerings from competitors, and ensure targeted and impactful digital marketing efforts.

Workshop 1 was designed to introduce the concepts of AI in marketing research and unique value proposition (UVP). The first workshop also saw the presentation of the first free AI tool, Bizway, and through practical demonstration, allowed participants to use AI to identify and formulate their UVPs. It consisted of a combination of videos, information on theoretical background to the marketing concept, and practical activities.

Workshop 2 focused on performing an industry analysis as a crucial aspect of any digital marketing strategy. This was performed using the PESTEL framework. It allowed participants to assess the political, economic, social, technological, environmental, and legal factors that could impact their business. Understanding these external factors would ultimately help them identify trends, opportunities, and threats in the industry and tailor their marketing strategies accordingly.

Workshop 3 targeted competitor analysis as a critical aspect of strategic planning, as it allowed businesses to understand their market landscape, anticipate competitors’ strategies, and identify their own competitive advantages. When conducted effectively, it could inform businesses’ marketing strategy, product development, and overall corporate strategy.

Including AI as a tool to facilitate this analysis, the process of competitor analysis was shown to be even more efficient and sophisticated. AI could process vast amounts of data at high speed, uncovering patterns and insights which could give businesses a significant edge. This could lead to more accurate predictions about competitors’ actions, and, ultimately, more informed business decisions.

The final asynchronous workshop (4) was dedicated to examining the businesses’ strengths, weaknesses, opportunities, and threats. The participants were able to gain a comprehensive understanding of their current situation. This analysis allowed them to utilise their strengths, work on their weaknesses, seize opportunities, and prepare for potential threats. It helped them form a strategy that aligned with each business’ goals and make informed decisions to drive growth in the digital marketplace. By using AI, an SWOT analysis (analysing strengths, weaknesses, opportunities, and threats) was shown to be even more effective. AI can help analyse large amounts of data quickly and accurately, uncovering patterns and insights that may not be immediately apparent. For instance, it can identify strengths by analysing customer feedback and reviews, detect weaknesses by looking at areas where performance is lagging compared to competitors, find opportunities in market trends, and alert to potential threats such as emerging competition or regulatory changes. Thus, leveraging AI for conducting SWOT analyses can provide a more detailed, accurate, and real-time understanding of businesses’ position in the digital marketplace.

The live workshop was designed to further refine each theoretical concept explored in previous lessons through more practical applications. It also served as an opportunity to gather feedback through an extensive discussion to gain an understanding of everyone’s experience in applying the principles and the SOSTAC strategic framework using the AI as a co-intelligence tool.

4. Findings and Discussion

4.1. Marketing Competency and Gen AI Application

The iterative process revealed week on week the participants’ growing familiarity and competency with the application of Gen AI toward the creation of better marketing strategies and the effective outcomes of AI use in various aspects of their digital marketing, as seen below in

Table 2. Evidence of competency in AI use in digital marketing.

Participants	Evidence of AI use in digital marketing
Participant 1	[…] this is an opportunity I think for us and [...] the resources can be invested in other you know in in other needs of the company for the company to grow. I can surely say that with the right prompts […] we’ll be able to do our things on our own.
Example Content Co-created with Gen AI: Participant 1 UVP	I help young Kenyan travellers that have a dream of visiting Victoria Falls in Zambia and the rest of Southern Africa reach their desired outcome of experiencing the most affordable, exceptional, and adventurous tour packages on the market. Unlike other alternatives, my solution takes a unique approach by providing not just destinations, but lifetime memorable experiences.
Participant 8	We couldn’t […] establish what our unique proposition was because […] everyone is doing tours in Zambia, and all that. But through the AI tools we were able to identify what our unique value proposition is and then we were able to come up with a marketing strategy within seconds. […] using AI it helped us within seconds […] also it simple things like how to develop content for a social media page. It’s been able to help us with, you know, give us content for a week content ideas which I think is going to help us help our business to thrive […].
Example Content Co-created with Gen AI: Participant 8 UVP	I help young professional tourists visiting Africa who want to explore Zambia but do not know how or where to start to reach their desired outcome of exploring new places. Unlike other alternatives, my solution provides clear roadmaps of places to explore with prices and a human touch, along with personal guidance 24hrs.
Participant 11	‘I can surely say that with the right prompts […] we’ll be able to do our things on our own. […] this is an opportunity I think for us and [...] the resources can be invested in other you know in in other needs of the company for the company to grow. I can surely say that with the right prompts […] we’ll be able to do our things on our own.
Example Content Co-created with Gen AI: Participant 11 UVP	I help holiday travellers who are searching for safe and comfortable accommodation, transport, and activities reach their desired outcome of a stress-free travel experience. Unlike other alternatives, my solution takes a unique approach as a One Stop Travel Advisory Service.

.

4.2. Experience of the Asynchronous Approach

The following section relates several of the key insights garnered from the participants of the asynchronous experience and highlights the impact of this on enabling skill, knowledge, and application competencies for participants. In such an educational setting, there is a recognised need to have a lesson that is well structured and paced, combined with the clear communication of expectations and establishing relations of trust between educators and participants [23].

The asynchronous approach revealed some inherent challenges, such as maintaining a higher level of engagement from all participants week on week, as also found by Aalst [17]. As such, the data relating to participation were mixed, highlighting both the opportunities and challenges, particularly where support was intercultural and intercontinental.

Following each workshop, data relating to participants’ engagement were collected through Nearpod reports. This allowed the educators to follow the level of completion of tasks within each workshop, as well as the overall completion rate per participant. The data were introduced in a table detailing the level of completion per workshop, as well as an overall one. Full engagement with the course was defined by the educators as participants having achieved 100% in each of the four asynchronous workshops and the final, live one. According to this setting, three participants achieved 100 percent overall. Some participants completed two workshops to the 100% level, while others achieved this score in three of the workshops, only completing the fourth one up to 25%. The nature of the learning setting did not allow the educators to see how the participants engaged with each workshop, as some of the tasks set allowed the viewers to progress through the lecture without having to answer questions or provide examples. There was evidence on Nearpod, however, of participants opening a workshop, even if they did not answer all the questions/tasks set in the lesson. Further engagement with the learning experience was evident through member participation in WhatsApp discussions relating to workshop topics between educators and participants.

To summarise, out of the 12 members who signed up and completed the first workshop, 3 completed all elements of the entire course (with a further 3 completing more than 75%). There was participation via WhatsApp from all individuals, demonstrating a level of interest in some form of interaction with the course. Below is some of the feedback from the participants in the workshops (see

Table 3. Feedback on asynchronous workshops in digital marketing.

Participants	Evidence of Impact
Participant 1	The learning experience is far better than I had expected before the beginning of the sessions and the learning materials are also quite helpful to understand the sessions. More practice will help us get better in delivering the best outputs.
Participant 5	This is amazing! Liked the introduction and how the learning will be done. It’s very impressive the way that you are delivering the learning materials and makes it easy to understand. Thank you for this opportunity.
Participant 8	The knowledge acquired is very helpful for business. I managed to acquire a competitor analysis in seconds. I would not change anything about the workshop.

below).

5. Discussion (Insights for More Effective Pedagogy with AI Integration)

The insights from the co-created AI inputs provided by the participants through the workshops and in the final live workshop provided valuable examples of how AI can be effectively integrated into tourism marketing strategies. The approach offers an opportunity to bridge the gap between education and practical applications. The workshops focused on using AI as a strategic digital marketing partner, which can be better understood through the following insights:

• Real-World Examples and Case Studies: The experiences shared by several participants highlight the practical benefits of leveraging AI in digital marketing strategy, such as creating unique value propositions and generating insight on the macro-environment. Workshops could incorporate real-world examples such as case studies, allowing participants to analyse and discuss how AI tools were applied in a given situation, the challenges faced, and the outcomes achieved. This approach not only makes the learning process more engaging but also provides concrete illustrations of AI’s potential impact.
• Hands-On Training with AI Tools: One of the critical gaps in educational workshops is often the lack of hands-on experience. Participants should not only learn about AI capabilities theoretically but also have direct interaction with AI tools during the workshop. For instance, conducting demonstrations and allowing participants to use AI to develop marketing strategies or content could help solidify their understanding and boost their confidence in applying these tools in real scenarios.
• Addressing Risk Management and Ethical Considerations: The discussion in the final workshop highlighted concerns around job displacement and the ethical implications of using AI, such as protecting intellectual property and ensuring the authenticity of creative outputs. Workshops should address these concerns by including sessions on risk management, ethical AI use, and how to integrate AI into business practices responsibly.
• Pedagogic Challenges: The research team discussed the challenges of circumstances where the use of AI was appropriate for learning purposes and where AI could potentially undermine knowledge development in the participants. Of critical importance to this decision was awareness of what is a “fundamental” of knowledge (such as the logic of a strategic model or framework) vs. what is an “application” of that knowledge and how to ensure that the learning of fundamentals would allow individuals to develop their understanding independently of AI, prior to its application.
• Interactive and Iterative Learning: Reflecting the interactive nature of the workshops’ content, the research team felt that making workshops incorporate interactive elements such as a Q&A (a live drop-in session or office hours, for example), discussion boards, and feedback sessions would strengthen the learning outcomes. This approach would encourage more active participation and allow for the iterative tweaking of participants’ strategies based on real-time feedback, which can enhance learning outcomes.
• Continuous Learning and Community Building: Finally, as AI and digital marketing landscapes evolve rapidly, workshops should promote continuous learning. Establishing communities or networks where participants can share ongoing experiences, challenges, and advancements post workshop can provide sustained support and learning opportunities.
• By focusing on these aspects, workshops on using AI as a strategic digital marketing partner can more effectively bridge the educational gap and empower entrepreneurs to harness AI technologies not just as tools but as integral components of their marketing strategy.

6. Conclusions

The use of Gen AI to actively integrate sustainable marketing practice into digital marketing (such as through improving value propositions) supports sustainability efforts by aligning this project’s outcomes with the UN Sustainable Development Goals [12], particularly Goal 8 (Decent Work and Economic Growth) and Goal 12 (Responsible Consumption and Production).

This focus supports an overall strategy for building capacity in LDCs in Africa by empowering participants from these regions to leverage AI for sustainable tourism management and build localised competitive advantage for participating organisations. As a result, in this study, insights and best practices for supporting enterprises in LDCs in actively participating in and benefiting from global tourism opportunities were explored and better understood in the context of leveraging Gen AI. The hope is that this will lead to more long-term sustainability and the resilience of organisations during this paradigm shift [1].

7. Future Research

There are opportunities to develop this research in the following areas:

• Developing a framework for the better integration of AI in pedagogy through an asynchronous approach, which can be used in a multi-disciplinary manner;
• Creating a repository of case studies and success stories from this research that can serve as a reference for future initiatives aimed at integrating AI into sustainable tourism practices;
• Potential for expanding this project to other sectors and regions.