Table 1. Cluster analysis Component... | Emerald Publishing

Table 1.

Cluster analysis

Component	Cluster colour	Key concepts	Relevance to practitioners	Relevance to students	Example of literature
Digital infrastructure and AI readiness	Yellow	This cluster links AI adoption to broader accounting information systems, sustainability and education. It considers whether systems are adaptive enough to integrate AI and whether users are ready to accept it	Ensure that the organisation’s systems support AI use	Understand systems thinking and audit trails in AI-driven contexts	Assidi et al. (2025); Anomah et al. (2024)
Data analytics and curriculum integration	Red	There is an evolving need to integrate emerging technologies into accounting curricula. The research in this cluster emphasises the importance of upskilling future accountants in tools and methods necessary to engage with AI-driven data environments	Hiring graduates who can handle complex data tasks	Must be exposed to analytics and digital technologies early at tertiary institutions to remain relevant	Coyne et al. (2016); Polimeni and Burke (2021)
AI technologies and professional adaptation	Orange	This cluster illustrates how core AI technologies, such as machine learning and automation, are reshaping accounting tasks. Repetitive tasks are being handled by AI while accountants and auditors focus on judgment-based roles requiring human monitoring and decision-making	Adapt workflows to incorporate AI tools while ensuring accountability	Develop skills in critical thinking and adaptability to complement automation	Arise and Moloi (2025); Eisikovits et al. (2025)
Student engagement and learning transformation	Green	This cluster focuses on how AI tools, most commonly ChatGPT, are affecting student performance, assessment methods and academic integrity. It underscores the transformation in education delivery and post-implementation reviews of accounting programs	Engage with academia to guide practical AI applications	Learn how to ethically and effectively use AI as a support tool rather than a shortcut	Baldwin-Morgan (1995); Katz (2024), Wood et al., including multiple crowdsourced authors, 2023
Evolving competencies for the “AI-Accountant”	Blue	The focus of this cluster is on the underlying skill sets required to operationalise AI such as, communication, AI literacy and critical thinking. These complement technical knowledge to form a more holistic accounting professional who applies integrated thinking	Assess hiring and training priorities, policies and evaluations	Transition to an integrated approach to technical and professional competencies	Mcguigan et al. (2021); Imjai et al. (2025)
AI tools in teaching and learning environments	Purple	This cluster highlights the growing use of tools such as ChatGPT and chatbots in accounting education. It explores the benefits and challenges of using generative AI to assist in the learning process	Be aware of how such tools shape the skills of new graduates	Making use AI for personalised learning but importantly, evaluating the outputs	Baldwin-Morgan (1995); Handoyo (2024); Pinto et al. (2024)
Educator roles in AI transformation	Brown	This smaller cluster shows the pivotal role educators play in shaping accounting graduates’ preparedness for AI-integrated workplaces. It also assesses the perceived quality and integrity of accounting outputs from AI	Collaborate with educators to ensure alignment of learning outcomes with industry needs	Rely on educators to frame AI in accounting not just as a tool, but as part of continued professional development	Holmes and Douglass (2022)

Component	Cluster colour	Key concepts	Relevance to practitioners	Relevance to students	Example of literature
Digital infrastructure and AI readiness	Yellow	This cluster links AI adoption to broader accounting information systems, sustainability and education. It considers whether systems are adaptive enough to integrate AI and whether users are ready to accept it	Ensure that the organisation’s systems support AI use	Understand systems thinking and audit trails in AI-driven contexts	Assidi et al. (2025); Anomah et al. (2024)
Data analytics and curriculum integration	Red	There is an evolving need to integrate emerging technologies into accounting curricula. The research in this cluster emphasises the importance of upskilling future accountants in tools and methods necessary to engage with AI-driven data environments	Hiring graduates who can handle complex data tasks	Must be exposed to analytics and digital technologies early at tertiary institutions to remain relevant	Coyne et al. (2016); Polimeni and Burke (2021)
AI technologies and professional adaptation	Orange	This cluster illustrates how core AI technologies, such as machine learning and automation, are reshaping accounting tasks. Repetitive tasks are being handled by AI while accountants and auditors focus on judgment-based roles requiring human monitoring and decision-making	Adapt workflows to incorporate AI tools while ensuring accountability	Develop skills in critical thinking and adaptability to complement automation	Arise and Moloi (2025); Eisikovits et al. (2025)
Student engagement and learning transformation	Green	This cluster focuses on how AI tools, most commonly ChatGPT, are affecting student performance, assessment methods and academic integrity. It underscores the transformation in education delivery and post-implementation reviews of accounting programs	Engage with academia to guide practical AI applications	Learn how to ethically and effectively use AI as a support tool rather than a shortcut	Baldwin-Morgan (1995); Katz (2024), Wood et al., including multiple crowdsourced authors, 2023
Evolving competencies for the “AI-Accountant”	Blue	The focus of this cluster is on the underlying skill sets required to operationalise AI such as, communication, AI literacy and critical thinking. These complement technical knowledge to form a more holistic accounting professional who applies integrated thinking	Assess hiring and training priorities, policies and evaluations	Transition to an integrated approach to technical and professional competencies	Mcguigan et al. (2021); Imjai et al. (2025)
AI tools in teaching and learning environments	Purple	This cluster highlights the growing use of tools such as ChatGPT and chatbots in accounting education. It explores the benefits and challenges of using generative AI to assist in the learning process	Be aware of how such tools shape the skills of new graduates	Making use AI for personalised learning but importantly, evaluating the outputs	Baldwin-Morgan (1995); Handoyo (2024); Pinto et al. (2024)
Educator roles in AI transformation	Brown	This smaller cluster shows the pivotal role educators play in shaping accounting graduates’ preparedness for AI-integrated workplaces. It also assesses the perceived quality and integrity of accounting outputs from AI	Collaborate with educators to ensure alignment of learning outcomes with industry needs	Rely on educators to frame AI in accounting not just as a tool, but as part of continued professional development	Holmes and Douglass (2022)

Source(s): Authors’ own work