Abstract
This book chapter systematically reviews AI's transformative impact on higher education marketing. It further explores the challenges of integrating AI within existing educational frameworks, emphasising the importance of AI literacy in curricula and addressing ethical considerations like data privacy and the balance between technology and human interaction. Moreover, it synthesises diverse literature to develop a framework for utilising AI in marketing, focusing on strategy, stakeholder experiences, and AI-driven initiatives. The research addresses AI integration challenges, AI literacy, and ethical concerns and aligns with Oman's Vision 2040 and digital strategies. It highlights the current state of AI in education and pinpoints gaps in existing literature, paving the way for future investigations within the Omani context. It emphasises strategic planning, campaign execution, and balancing technology with human aspects, offering insights for Oman's institutions to effectively utilise AI, highlighting current trends and future research directions in the Omani context.
TopIntroduction
In the ever-changing world of higher education, the arrival of artificial intelligence (hereafter AI) jointly with technology has sparked the transformation of the traditional meeting point between academic administration, marketing, and technology. Analysis of different studies prompts higher education institutions to have a deeper understanding of AI's effective integration and impact on their operations. Consistent with the larger Vision 2040, Oman’s National Digital Economy Program is simply a reflection of the change that is happening as it adopts AI and digital technology in its education sector. This chapter investigates the way AI’s impact on higher education marketing redefines conventional methods with data-driven tactics and personalized student socialization.
Introducing AI in academic and administrative educational practices is not just a technological invasion but an attempt to nuances of student needs and behaviours. In line with Oman’s ambitious digital transformation objectives, this strategic vision reiterates the aims of AI powered enhanced learning and administrative efficiencies (MTCIT 2021). AI enables educational organizations to personalize their marketing approaches via ChatGPT, machine learning, predictive analytics, student targeting, interactions, and engagement. Nevertheless, these technological progressions bring a critical problem of balance of automation and the human element in the marketing of educational institutions (Baidoo-Anu and Owusu-Ansah, 2023; Jain and Aggarwal, 2020).
Moreover, various studies show that AI is implemented at the operational management level in different higher education institutions (PWC, 2016). This is a direct outcome of government initiatives such as the National Digital Economy program, which focuses on utilising AI for operational efficiencies and increasing its applications to develop educational systems further. At an operational level, AI is increasingly used by administrators to optimise resource management systems, enhance student services, and influence student recruitment and retention, which highlights its importance in achieving higher institutional performance and reshaping the general traditional education landscape (Cihelkova et al., 2020; Zemanova, 2015). Therefore, reflecting these developments, the idea of this chapter stems from the potential role of AI in transforming higher education. More specifically, this chapter explores its application in Oman through the National Digital Strategy and other frameworks that may provide us with the
In Oman, precisely, this exploration coincides with the national digital strategy, signalling the role of AI in improving educational experiences and achieving institutional objectives in the digital era. Hence, this chapter offers reflective knowledge for academics, administrators and marketers alike to enable them to understand the evolving link between strategy development, emerging technologies, and human communication in the current times.
As we start this exploration, we will provide an overview of the utilisation of AI in higher education in general and Oman in particular through its Vision 2040 and Digital Economy Program and review any ethical issues linked with its innovative usage. Therefore, in its comprehensive review, the current chapter implies AI's transformative possibilities in higher education and emphasises the intelligent and flexible technology application in designing a more integrated, responsive, and comfortable learning environment (Carroll et al., 2009; Lancioni, 2013).
In conclusion, incorporating AI into higher education is the transition to a more progressive and adaptable educational model. The chapter aims to map it out by offering discussions and advice about how to optimise the power of AI in the best way to overcome the challenges and get the opportunities from AI in the constantly changing world of higher education.
In Oman, the convergence of traditional education with modern AI technologies, as the National Digital Economy Program promoted, is a primary part of this evolutionary path.
Key Terms in this Chapter
Data Privacy: The aspect of data protection that deals with the proper handling, processing, and storage of data to protect individuals' personal information and confidentiality.
Machine Learning: A branch of AI where algorithms use statistical methods to enable machines to improve their performance on a specific task with data, without being explicitly programmed.
Artificial Intelligence (AI): A branch of computer science focused on creating autonomous intelligent systems that replicates human intelligence and capable of performing tasks such as learning, decision-making, and problem-solving.
Digital Marketing: The use of digital channels, tools, and methodologies for marketing products and services, particularly involving the internet and other digital forms of communication.
Robotisation: The process of replacing human labor with robotic technology or automated systems, often seen in industrial and increasingly in service sectors.
Predictive Analytics: A technique that uses statistical algorithms and machine learning tools to predict a future outcome based on historical data.
“Blue-Collar” Jobs: Refers to manual labor occupations, typically involving skilled or unskilled manual labor in various fields such as; manufacturing, mining, oil field work or similar types of physical work.
“White-Collar” Jobs: Refers to occupations that are typically salaried and involve administrative or professional work, often in an office or other clerical setting, as opposed to manual labor.
Academic Integrity: The ethical code of academia, which includes values such as honesty, fairness, and responsibility in the creation, dissemination, and application of knowledge in the educational and research environment.
STEM Fields: An acronym for Science, Technology, Engineering, and Mathematics, referring to disciplines that are focused on scientific concepts, practical applications, and technical knowledge.
E-Learning and Innovation: The use of digital technologies to create, adopt, and implement new and improved teaching and learning methods, often involving online and interactive learning platforms.