AI Literacy for an Ageing Workforce: Leveraging the Experience of Older Workers

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Abstract
This study delves into the potential benefits of Artificial Intelligence (AI) literacy training for late-career-stage workers approaching retirement. These workers often possess extensive experience but may lack the necessary digital and AI skills. AI literacy training can empower them to leverage their experience and become proficient contributors to the digital economy. Furthermore, the article describes how these workers might benefit from AI training, particularly when employing practical applications of AI in their specific field or industry. The article argues that these workers’ knowledge, insights and experience are valuable assets that can be exploited to benefit the business. Their abilities allow them to calibrate the prompts used in Generative-AI systems, maximizing the quality of the AI-generated content. Prompt engineering is a new career path that has followed the rapid emergence of Generative AI content creation. Late-career-stage workers are well suited to act in this role, leveraging their business knowledge to produce quality outputs. The study argues that employers should integrate domain-specific knowledge into the training program's structure, allowing late-career-stage workers to understand the relevance of Generative AI systems and calibrate prompts based on their experience and knowledge. Developing their AI skills can ultimately lead to increased productivity and efficiency. Moreover, this article emphasizes the potential benefits for these workers and businesses in providing AI literacy training. It not only enables late-career-stage workers to enhance their skills, but it can also bring valuable insights and experience to the business, ultimately leading to the growth and success of the business. These opportunities empower such workers to access more strategic positions in their institutions and gain a sense of fulfillment in their roles. The methodology for this study will follow a scoping literature review of academic articles. This approach allows for examining existing research on AI literacy training for late-career-stage workers. Articles were sourced through a comprehensive search of academic databases such as ScienceDirect, EbscoHost and Scopus. Search terms included AI literacy, digital literacy, aging workforce and prompt engineering.

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