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The International Standard Classification of Education defines adult learning as specifically targeting individuals who are regarded as adults by the society to which they belong to improve their technical or professional qualifications, further develop their abilities, enrich their knowledge to complete a level of formal education, or acquire knowledge, skills, and competencies in a new field or to refresh or update their knowledge in a particular field. This also includes what may be referred to as ‘continuing education,’ ‘recurrent education,’ or ‘second chance education. (United Nations Educational, Scientific and Cultural Organization, Institute for Statistics, 2012, p. 78)
A broad definition of AI: “Computers which perform cognitive tasks, usually associated with human minds, particularly learning and problem-solving” (p. 10). AI is not a single technology but an umbrella term that describes a range of technologies and methods, such as machine learning, natural language processing, data mining, neural networks, or algorithms. (Baker & Smith, 2019)
Top1. Introduction
According to the Organization for Economic Cooperation and Development (Verhagen, 2021), AI can improve and replace current technologies in delivering training, spreading information on skill requirements and relevant training courses, and personalizing the matching of job seekers to available learning opportunities. Adult learners, as digital natives, are comfortable using generative AI tools to access information and with education institutions diving deep into the analyses of large databases to track their progress and performance (Impact Research, 2023).
To prepare the global workforce to transition from an information society to an intelligent society, the United Nations Educational, Scientific and Cultural Organization (UNESCO) developed a global framework to help define and measure digital literacy (2018). The framework has seven competency areas: devices and software operations, information and data literacy, communication and cooperation, digital content creation, safety, problem-solving, and career-related competencies, which suggest that AI's application in adult education is strategically significant to training an innovative, scientific, and technologically talented workforce. Such a move requires educators to develop an open, flexible, active, and innovative adult education ecosystem to promote quality education and ensure education equity (Kang, 2023). In 2019, UNESCO published a report entitled “Artificial Intelligence in Education: Challenges and Opportunities for Sustainable Development,” which highlighted the increasing role of AI in influencing students’ access to education, learning performance, teaching andragogy, educational data analysis and management.
The World Economic Forum (WEF) estimates that almost one-third of all jobs worldwide are likely to be transformed by technology in the next decade (Zahidi, 2020) and that essential technical and vocational skills are currently underemphasized in education systems (Strategic Intelligence, 2020). Consequently, there is an urgent need to replace the traditional andragogical model of adult training with a new dynamic structural model (Storey & Beeman, 2023), more suited to creating new learning content. Generative AI tools are ideally positioned to fill this role, given their ability to access and synthesize a wide range of human knowledge into specific outputs (Leiker et al., 2023). However, it is challenging to create this new path as it depends on adult educators having the required knowledge and skills. It is, therefore, incumbent on all educators to continue their learning to adapt, overcome barriers, and effectively integrate AI into programs for future developments (Kaliisa et al., 2022).
The subsequent sections of this article are organized into four distinct parts. Section 2 presents an overview of AI-driven educational technologies within the context of adult learning and discusses the challenges of integrating AI into adult education. Section 3 explores the ethical implications of AI in adult education, including academic integrity, data privacy, algorithmic bias, and copyright. Section 4 is focused on emerging trends and future directions for adult education. Finally, policy implications and recommendations for adult educators are made to develop AI-enriched adult education.