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Artificial intelligence (AI) will transform various processes by utilizing and sharing data and information. This transformation brings new opportunities and challenges to organizations. Effective leadership is essential to handle these changes. However, there is no scientific research on how AI affects the everyday lives of managers. Therefore, this paper aims to identify how AI can affect changes in the skills and personality traits of managers using AI.

A structured literature review identified leadership competencies relevant to the AI era. Three scientific databases were included in the search: (I) Scopus, (II) EBSCO Business Source Complete, and (III) Web of Science. A total of 730 articles were identified from the three databases under the topics “Digital Leadership,” “Leadership” AND “Artificial Intelligence,” “Future Leadership,” “Algorithm Leadership,” “AI Leadership,” “Artificial Leadership,” and “Data-driven Leadership.”

A total of 24 leadership competencies, including 12 personality traits and 12 skills, were identified from the literature. To adapt effectively to AI, leaders should focus on developing communication skills and forming high-performance teams working cross-functionally and in a symbiosis of humans and machines.

The article adds knowledge to leadership theories and provides a basis for future management education.

This conceptual paper provides an overview of eye-tracking technology (ETT) as a process-tracing method to study children’s consumer behavior. This paper aims to provide a literature review of the child as consumer-focused eye-tracking research, identifying theoretical and research gaps. This paper discusses the benefits, drawbacks and ethical implications of ETT and highlights opportunities and best practices for future research.

This paper details eye movement and how ETT captures it. This paper delivers a typology of different approaches to eye-tracking research and presents information about ETT equipment and metrics. This paper also summarizes previous studies using eye tracking to study children. This paper concludes with research questions and topics for future research where ETT can be used to study child consumers in contexts such as playing advergames, using social media and shopping (in-person and online).

ETT is commonly used to assess children’s behavior in a variety of contexts but has scarcely been used to study children’s consumer behavior. ETT has great potential to be used to better understand children as consumers.

To the best of the authors’ knowledge, this is the first paper to review using ETT to study children’s consumer behavior.

The advent of artificial intelligence (AI) in the accounting landscape marks a significant shift, promising gains in efficiency and accuracy but also eliciting concerns about job displacement (JD) and broader socio-economic implications. This study aims to provide an in-depth understanding of how AI’s integration in accounting contributes to JD, reshapes decision-making processes and reverberates across economic and social dimensions. It also offers evidence-based policy recommendations to mitigate adverse outcomes.

Leveraging a cross-sectional survey disseminated through Facebook, this research used snowball sampling to target a diverse cohort of accounting professionals. The collected data were subjected to meticulous analysis through descriptive and regression models, facilitated by SmartPLS 4 software.

The analysis revealed a significant correlation between AI’s increasing role in accounting and a heightened rate of JD. This study found that this displacement is not isolated; it has tangible repercussions on decision-making paradigms, economic well-being, professional work dynamics and social structures. These insights corroborate existing frameworks, including, but not limited to, theories of technological unemployment and behavioural adjustments.

Although providing valuable insights, this study acknowledges limitations such as the restricted sample size, the cross-sectional nature of the survey and the inherent biases of self-reported data. Future research could aim to extend these initial findings by adopting a longitudinal approach and potentially integrating external data sources.

As AI technology becomes increasingly ingrained in accounting practices, there is an urgent need for coordinated action among stakeholders. Policy recommendations include focused efforts on talent retention, investment in upskilling programs and the establishment of support mechanisms for those adversely affected by AI adoption.

By synthesising a range of theoretical perspectives, this study offers a comprehensive exploration of AI’s multi-dimensional impacts on the accounting profession. It stands out for its nuanced examination of JD and its economic and social implications, thereby contributing to both academic discourse and policy formulation. This work serves as an urgent call to action, highlighting the need for strategies that both exploit AI’s potential benefits and protect the workforce from its disruptive impact.