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Since the release of ChatGPT by OpenAI in November 2022 – with its ability to create compelling, relevant content, new large language model (LLM) technology – business leaders, especially CEOs, are being pressured to accelerate new generative AI investments. IBM IBV surveyed executives to assess their progress and concerns and their adoption strategies.

Adoption of generative AI is still in its very early stages. Most organizations are only beginning to figure out how and where to make use of it. In fact, as few as 6 percent of executives in new surveying conducted by the IBM Institute for Business Value say they are operating generative AI in their enterprise today.

In contrast to many peoples’ expectations about AI, automating tasks is not the top priority for executives looking to tap generative AI to grow business value. Looking at benefits by function, research and innovation is the primary area where organizations see opportunities for generative AI.

IBM IBV's recent survey of executives found that the key barriers to the effective deployment and use of generative AI are linked to security, privacy, ethics, regulations and economics – not access to the underlying technology itself.

Organizations will have to evaluate where in their enterprise the potential gains and cost efficiencies outweigh the risks of possible errors or unintended consequences from the use of generative AI along with broader ethical considerations. Ecosystems expand generative AI opportunities to harness data, insights and technology capabilities from across partners and stakeholders while enabling control over the capabilities that are most central to an organization’s value proposition.

This study offers practical insights into how generative artificial intelligence (AI) can enhance responsible manufacturing within the context of Industry 5.0. It explores how manufacturers can strategically maximize the potential benefits of generative AI through a synergistic approach.

The study developed a strategic roadmap by employing a mixed qualitative-quantitative research method involving case studies, interviews and interpretive structural modeling (ISM). This roadmap visualizes and elucidates the mechanisms through which generative AI can contribute to advancing the sustainability goals of Industry 5.0.

Generative AI has demonstrated the capability to promote various sustainability objectives within Industry 5.0 through ten distinct functions. These multifaceted functions address multiple facets of manufacturing, ranging from providing data-driven production insights to enhancing the resilience of manufacturing operations.

While each identified generative AI function independently contributes to responsible manufacturing under Industry 5.0, leveraging them individually is a viable strategy. However, they synergistically enhance each other when systematically employed in a specific order. Manufacturers are advised to strategically leverage these functions, drawing on their complementarities to maximize their benefits.

This study pioneers by providing early practical insights into how generative AI enhances the sustainability performance of manufacturers within the Industry 5.0 framework. The proposed strategic roadmap suggests prioritization orders, guiding manufacturers in decision-making processes regarding where and for what purpose to integrate generative AI.

The purpose of this paper is to share findings from empirically driven conceptual research into the implications for English teachers of understanding generative AI as a “tool” for writing.

The paper reports early findings from an Australian National Survey of English teachers and interrogates the notion of the AI writer as “tool” through intersectional feminist discursive-material analysis of the metaphorical entailments of the term.

Through this work, the authors have developed the concept of “coloniser tool-thinking” and juxtaposed it with First Nations and feminist understandings of “tools” and “objects” to demonstrate risks to the pursuit of social and planetary justice through understanding generative AI as a tool for English teachers and students.

Bringing together white and First Nations English researchers in dialogue, the paper contributes a unique perspective to challenge widespread and common-sense use of “tool” for generative AI services.

We use design thinking in the context of accounting pedagogy to exploit recent advances in cybernetics in the form of generative artificial intelligence technology. Relying on the intuition that supplementing or augmenting human argumentation (natural intelligence or NI) with parallel AI output can produce better student written assignments, we posit the “augmentation premise,” that is, ((NI + AI) > AI > NI). To test the augmentation premise, we compare student written submissions in an Accounting Information Systems (AIS) course with and without the benefit of parallel generative AI output. We then evaluate how the generative AI output enhances student-crafted revisions to their initial submissions. Using a summative quality improvement index (QII) consisting of quantitative and qualitative assessments, we present preliminary evidence supporting the augmentation premise. The augmentation premise likely extends to other accounting subdisciplines and merits generalization for enriching accounting pedagogy.

This study aims to uncover the ongoing discourse on generative artificial intelligence (AI), literacy and governance while providing nuanced perspectives on stakeholder involvement and recommendations for the effective regulation and utilization of generative AI technologies.

This study chooses generative AI-related online news coverage on BBC News as the case study. Oriented by a case study methodology, this study conducts a qualitative content analysis on 78 news articles related to generative AI.

By analyzing 78 news articles, generative AI is found to be portrayed in the news in the following ways: Generative AI is primarily used in generating texts, images, audio and videos. Generative AI can have both positive and negative impacts on people’s everyday lives. People’s generative AI literacy includes understanding, using and evaluating generative AI and combating generative AI harms. Various stakeholders, encompassing government authorities, industry, organizations/institutions, academia and affected individuals/users, engage in the practice of AI governance concerning generative AI.

Based on the findings, this study constructs a framework of competencies and considerations constituting generative AI literacy. Furthermore, this study underscores the role played by government authorities as coordinators who conduct co-governance with other stakeholders regarding generative AI literacy and who possess the legislative authority to offer robust legal safeguards to protect against harm.

This commentary discusses the value of generative artificial intelligence (AI) for qualitative research in phygital settings to understand the customer experience.

The critical and logical analysis is based on current knowledge of generative AI.

Generative AI seems very useful for qualitative research in phygital settings to understand the customer experience and should be used in qualitative research projects. Generative AI can provide much-needed validation of the subjective nature of qualitative research and can also generate insights beyond human intuition.

The study is based on current technology, which changes fast. In the future, the skills of qualitative researchers may become outdated, relegating them to the role of prompt engineers.

Technology, and especially generative AI, will be a key tool for practitioners as they conduct practical research.

Qualitative researchers should overcome potential anti-technology speciesism and embrace the potential of generative AI.

This commentary provides insights into the role of generative AI for qualitative research in phygital settings.

The primary purpose of this paper is to examine how generative Artificial Intelligence (AI) such as ChatGPT may serve as a new context for management theories and concepts.

The paper presents the analyses of selected management theories on decision-making, knowledge management, customer service, human resource management and administrative tasks and explains what may change after generative AI adoption.

The paper indicates that some management theories and concepts need to be studied in the generative AI environment that may influence managerial work at the strategic, functional and administrative levels.

This paper is an opinion piece article and does not refer to empirical data. It formulates some conclusions to further empirical research studies.

The paper analyzes selected management theories in a new technological setting. The paper also provides information about the functions of generative AI that are useful in understanding and overcoming how new technology may change organizations and management.

This chapter provides preliminary evidence to show that financial accounting students would use generative artificial intelligence (AI) tools to improve their learning if given the opportunity to do so by their instructors. Most students who completed the exercises we used in the study did so diligently and modified their answers after using a generative AI tool in a manner that suggests beneficial effects. It appears that the more prior knowledge a student had about the subject matter, the more beneficial was the experience. Pitfalls still exist, however. For example, students without knowledge of the subject matter struggled with crafting queries and judging the efficacy of their answers. Moreover, although a minority, some students tended to duplicate their original answers without utilizing the responses generated by the generative AI tool. Additionally, certain students merely copied the answers generated by the AI tool without providing any additional critique or analysis. Implications for teaching and learning and opportunities for future research are discussed.

Generativity is defined in this chapter as the creation of new images, metaphors, physical representations, and so on that have two qualities: they change how people think so that new options for decisions and/or actions become available to them, and they are compelling images that people want to act on. Research and experiences that suggest “positivity,” particularly positive emotion, is not sufficient for transformational change, but that generativity is a key change lever in cases of transformational change, are reviewed. A model of different characteristics of generativity is offered and ways in which appreciative inquiry can be a generative process, increase generative capacity, and lead to generative outcomes, are discussed. Ways to increase the generativity of appreciative inquiry through generative topics, generative questions, generative conversations, and generative action are offered.

With the rapid advancement of generative artificial intelligence (AI), it is important to consider how young people are making sense of these tools in their everyday lives. Drawing on critical postdigital approaches to learning and literacy, this study aims to center the experiences and perspectives of young people who encounter and experiment with generative AI in their daily writing practices.

This critical case study of one digital platform – Character.ai – brings together an adolescent and adult authorship team to inquire about the intertwining of young people’s playful and critical perspectives when writing on/with digital platforms. Drawing on critical walkthrough methodology (Light et al., 2018), the authors engage digital methods to study how the creative and “fun” uses of AI in youths’ writing lives are situated in broader platform ecologies.

The findings suggest experimentation and pleasure are key aspects of young people’s engagement with generative AI. The authors demonstrate how one platform works to capitalize on these dimensions, even as youth users engage critically and artfully with the platform and develop their digital writing practices.

This study highlights how playful experimentation with generative AI can engage young people both in pleasurable digital writing and in exploration and contemplation of platforms dynamics and structures that shape their and others’ literate activities. Educators can consider young people’s creative uses of these evolving technologies as potential opportunities to develop a critical awareness of how commercial platforms seek to benefit from their users.

This study contributes to the development of a critical and humanist research agenda around generative AI by centering the experiences, perspectives and practices of young people who are underrepresented in the burgeoning research devoted to AI and literacies.