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The field of knowledge management and knowledge management systems is evolving and dynamic. In the era of developed information technology systems, the dynamics of knowledge creation and dissemination have also changed. Generative artificial intelligence (GenAI)—an embedded entity in the knowledge management system—has become a prominent area of research…

Recent advancements in generative artificial intelligence have enabled its use for problem-solving across various fields. However, its effectiveness heavily depends on users' prompting ability, often limiting its potential. Additionally, valuable dialogue logs are frequently left unused. This study proposes a service that scores dialogue logs with…

Abstract Despite ongoing digitization in industry, many companies still work with paper instructions or ‘paper-on-glass’ solutions (e.g., PDF files on screens). In recent years, various digital work instruction (DWI) technologies have become available that provide shop-floor employees with information during their activities, e.g., sequences of…

Retrieval-Augmented Generation (RAG) enhances large language models (LLMs) by integrating external knowledge sources, which significantly improves response accuracy and contextual relevance. However, most existing RAG research implicitly assumes that all retrieved content is equally accessible to any user. This approach fails to address the complex…

The purpose of the study was to analyse the global experience of forming ethical and legal frameworks for the use of generative artificial intelligence in the media industry, publishing and public communications. The research methodology included a theoretical analysis of scientific sources to identify global challenges of artificial intelligence in the…

As AI is increasingly used across social and organizational domains, trust in AI has emerged as an important research topic. This study analyzes 605 articles from 2016 to 2025 to examine the intellectual structure and thematic evolution of the field. Bibliometric and BERTopic analyses were used to identify transitions before and after generative AI…

Purpose: To suggest how business schools can respond when generative AI automates routine, entry-level tasks and erodes early-career opportunities. The paper addresses a focused question: What can a business school do when graduates’ entry-level jobs are replaced or reconfigured by AI?Approach: This is a perspective article that synthesises recent…

This study investigates how emerging digital technologies, particularly generative AI tools, are transforming public sector communication in Europe, highlighting the profound intersection between public organizations, AI, and human interactions. In particular, it explores the opportunities and risks that public sector communicators face as they deal with…

Abstract In an era where artificial intelligence (AI) permeates every facet of our lives, the imperative to steer AI development toward enhancing human wellbeing has never been more critical. However, the development of such positive AI poses substantial challenges due to the current lack of mature methods for addressing the complexities that designing…

Artificial intelligence (AI), particularly large language models (LLMs), is rapidly transforming scholarly publishing by providing new tools for manuscript preparation, language enhancement, literature synthesis, and editorial workflows. While these technologies offer substantial benefits, including improved efficiency, accessibility, and support for…

When organisations deploy AI systems in high-stakes do-mains, they need risk assessments they can trust. Large language models offer a promising path to scalable assessment, but two problems under-mine their reliability: shallow reasoning that flags risks without tracing causal mechanisms, and untuned aggregate output that sits systemati-cally above…

Abstract As generative AI becomes more deeply integrated into society, building public trust in this technology has emerged as a key challenge for policymakers. Existing approaches, such as the European Commission’s Trustworthy AI framework, largely seek to tackle this issue by offering comprehensive technical and legal measures for promoting a more…

The integration of artificial intelligence into business communications has created new opportunities for real-time analysis of customer interactions. This study presents an integrative framework that combines Large Language Models (LLMs) with Customer Value Management (CVM) to enhance the understanding and management of Business-to-Business (B2B)…

Abstract Background: We designed an educational simulation, ‘MediCampus AI’, using a large language model with Retrieval-Augmented Generation to replicate realistic clinical scenarios aligned with evidence-based Current Care Guideline (CCG). We piloted the simulation to assess its usability for supporting clinical reasoning, patient interaction, and CCG…

The increasing adoption of AI-powered code generation tools has introduced a critical challenge in software engineering, the potential erosion of developer comprehension of codebases increasingly composed of AI-generated artifacts. Before examining this erosion, we establish that human code comprehension remains a functional requirement in AI-augmented…

Abstract This systematic literature review analyses AI literacy, focusing on the required competencies for, the obstacles arising from, and the benefits of, Generative AI (GenAI) in the fields of education and business. The analysis uses the PRISMA 2020 methodology with data from the SCOPUS and ERIC databases. A total of 538 articles were identified; of…