Disruptive technologies have profoundly changed the operational pathways of organizations (Lee et al., 2021; Carlucci et al., 2013). Enabling and supporting technologies, such as artificial intelligence in its various forms—Artificial Narrow Intelligence (ANI), Artificial General Intelligence (AGI), and Artificial Super Intelligence (ASI)—are becoming the main drivers of this transformation (Damar et al., 2024).
Artificial Narrow Intelligence (ANI), of which Generative AI is a part, is marking a paradigm shift in machine intelligence, offering increased generalization capabilities with greater accessibility and equity for nontechnical users (Rawat et al., 2023). Large Language Models (LLMs) lead conversational interfaces, such as the popular ChatGPT. Although inventors, developers, and users of these models often lack a complete understanding of their operations, capabilities, and limitations, Generative AI is being rapidly adopted or considered for adoption across various industries and research fields.
Over time, several theories have emerged regarding the benefits and threats of these technologies. Among the most adverse concerns are the risks of workforce reduction and the flattening of human capital. On the other hand, advocates emphasize their versatility, speed, and the qualitative substitution of traditional knowledge resources (Krieger et al., 2024; Candrian and Scherer, 2022; Castelo and Ward, 2021).
In this contrasting scenario, several implications arise from the potential of this technology to transform social habits and industry sectors that heavily depend on human capital, such as education (Nguyen and Hekman, 2024; Paoloni et al., 2021), enterprises (Bouhia et al., 2022; Frank et al., 2022), healthcare (Bologheanu et al., 2023; Esmaeilzadeh et al., 2021), manufacturing (Cavazza et al., 2023), and critical infrastructure (Damar et al.,2024).
According to De Silva (2024), the main practical contributions of Generative AI can be recognized in four key areas closely tied to knowledge: Augmenting Learning and Teaching Experience, Accelerating Academic Research, Supporting Industry Engagement, and Increasing Social Impact.

• Augmenting Learning and Teaching Experience: Generative AI can enhance active learning experiences in classrooms and small group settings. For example, chat functions and specific teaching teams can address challenges and ensure equitable learning, reducing disparities. The selective construction of meaning through multiple associations between taught curricula and pre-existing knowledge can be augmented through AI’s human-like conversational skills (Rospigliosi, 2023; Mcmurtrie, 2018).
• Accelerating Academic Research: Generative AI can assist in developing and refining research ideas, brainstorming, and understanding societal and practitioner implications. By strengthening the connection between universities and the social contexts scholars are studying, AI fosters more impactful academic research (Xu et al., 2021).
• Supporting Industry Engagement: Generative AI can improve decision-making by implementing models that account for choices or resource constraints, thereby enhancing firms’ operational efficiency and profitability (Arujo et al., 2020; Atwal and Bryson, 2021; Silva et al., 2023).
• Increasing Social Impact: Generative AI can be instrumental in stakeholder engagement, particularly through social media platforms that reach diverse demographic groups such as investors, leaders, employees, students, and consumers. In general, technology increases the potential for social inclusion, making communication more effective and serving as a useful tool to combat various forms of discrimination (Ashrafi and Easmin, 2023; Bao et al., 2022; Park et al., 2022).

As AI and emerging technologies become embedded in modern business practices, their implications for gender dynamics in the workplace and the economy are profound and multifaceted (Paoloni et al., 2019). Gender issues may emerge as obstacles or opportunities related to the use of these technologies in different contexts (Paoloni et al., 2023; Cosentino and Paoloni, 2021; Paoloni and Modaffari, 2018). For example, one might consider the benefits female entrepreneurs could gain from using technology in their businesses (Modaffari et al., 2023), as well as the threats female workers might face, including the exacerbation of gender disparities in the workplace (Paoloni, 2024; Paoloni et al., 2022).
This call seeks to explore how AI and digital technologies intersect with gender, reshaping business processes, organizational cultures, and economic and social opportunities. Historically, technological shifts have provided opportunities for progress, while also risking the reinforcement of entrenched inequalities. The rapid integration of AI into decision-making processes across sectors—ranging from human resources to finance, operations, and social relationships—calls for a critical examination of its potential to both worsen and alleviate gender disparities.
The purpose of this call is to generate a comprehensive and interdisciplinary examination of how AI and emerging technologies are reshaping business paradigms in ways that intersect with gender. We aim to push the boundaries of current scholarship, offering both critical analyses of the risks and optimistic explorations of how technology can be leveraged to create a more equitable and inclusive business landscape. We invite submissions of original qualitative, quantitative, critical, and discussion-based research on the following sub-topics:

• AI as a facilitators or hostile drivers to gender equality;
• AI to support innovative female-led enterprises;
• The impact of emerging business technologies on gender dynamics;
• Gender issues in new business models;
• Gender and technologies in the development of private and public organizations;
• Gender and technologies for achieving the Sustainable Development Goals (SDGs);
• Ethical, policy, and governance considerations in the field of gender and emerging technologies.

Paola Paoloni, Sapienza University of Rome, Italy
Giuseppe Modaffari, Sapienza University of Rome, Italy