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This study examines through a systematic review, the reference services rendered in academic libraries using artificial intelligence (AI) and by collecting data through environmental scanning. The objective of this systematic literature review is to provide a synthesis of empirical studies exploring the application of artificial intelligence for reference services in academic libraries. Data were collected from Web of Science, Scopus, and LISA databases. Following the rigorous/established selection process, a total of thirty five articles were finally selected, reviewed and analyzed. Thirty five papers were identified, analyzed and summarized on the subject relating to the application of AI and the methods which are most often used. The findings demonstrate that university libraries in Canada and China are leading in the deployment of AI for reference services. The AI techniques used mostly in the scanned university libraries are self-directed learning and natural language processing techniques; while the challenges of using AI for reference services are the problem of quality intelligence, linguistic style, privacy, a threat to intellectual freedom, bias, and cost; inadequate experts, poor network, poor training and lack of innovation, and limited knowledge about the technology. The study indicates university libraries take into account implementing AI for reference services. [ABSTRACT FROM AUTHOR]

• Develops a structure-agency analytical framework to examine the trajectories of emerging technologies in different national contexts. • Compares AI development and diffusion between a developed country and an emerging country based on 125 in-depth interviews. • Argues that the levels of institutionalisation exert different structural forces and leave different spaces for institutional work. • Yields practical implications for developing countries to address the trade-off between the opportunities and risks brought by emerging technologies. Development studies have paid less attention to the role of technological innovations and we are yet to understand how, and more importantly why, technological trajectories differ across countries. This gap becomes sharper as emerging technologies such as artificial intelligence (AI) are becoming increasingly important in addressing many world development challenges. Drawing on insights from institutional work literature, this paper develops a structure-agency interplay framework to unravel the various trajectories of emerging technologies at the national level and examines the development and diffusion of AI in Canada and China. The findings show that Canada's stable institutional environment, reinforced through institutional work by various actors, generated a national AI trajectory driven by technology development through a strong focus on scientific research and ethics, with slower organic commercialisation of AI. In China, a dynamic and loose institutional structure characterised by lax regulations, low entry barriers, and high openness to novelties has resulted in a market-driven AI trajectory focused on technology commercialisation, with domestic digital giants and the government as dominant players. National-level dynamics in formal institutions, informal institutions, technologies, and actor strategies determine heterogeneous approaches to technology development and diffusion, giving rise to varieties of technological trajectories. The levels of institutionalisation exert different forces and create different spaces for institutional work across different geographical contexts. [ABSTRACT FROM AUTHOR]