The study aims to identify the knowledge, skills and competencies required by accounting and auditing (AA) professionals in the context of integrating disruptive Generative Artificial Intelligence (GenAI) technologies and to develop a framework for integrating GenAI capabilities into organisational systems, harnessing its potential to revolutionise lifelong learning and skills development and to assist day-to-day operations and decision-making. Through a systematic literature review, 103 papers were analysed, to outline, in the current business ecosystem, the competencies’ demand generated by AI adoption and, in particular, GenAI and its associated risks, thus contributing to the body of knowledge in underexplored research areas. Positioned at the confluence of accounting, auditing and GenAI, the paper introduces a meaningful overview of knowledge in the areas of effective data analysis, interpretation of findings, risk awareness and risk management. It emphasizes and reshapes the role of required skills for accounting and auditing professionals in discovering the true potential of GenAI and adopting it accordingly. The study introduces a new LLM-based system model that can enhance its GenAI capabilities through collaboration with similar systems and provides an explanatory scenario to illustrate its applicability in the accounting and audit area.

Hyperautomation is a business-driven approach, conceptualized in 2019 by Gartner Inc., that combines various technologies such as Artificial Intelligence (AI), Robotic Process Automation (RPA) and integrated platforms as a service (iPaas) with the aim of making business processes more efficient by substituting human intervention. Among these, implementations of AI within business services use technologies like Natural Language Processing, Voice and Image Recognition, Virtual Agents, Machine Learning or Deep Learning platforms. Acknowledging this reality, we are interested in developing answers to the following research questions: (1) What are the main categories of business services which integrate specific AI tools? (2) What are the transformed business processes and their operations provided by AI tools? (3) What are the benefits related to AI integrated tools? For this triadic purpose, a systematic literature review on the implementation of Artificial Intelligence in the field of business services was carried out. Only works indexed in the Web of Science database, published in the last 5 years, were selected. Moreover, the websites of the main developers and client companies were investigated. Our findings include a selection of identified AI solutions, structured by main business services categories; we have also outlined the performed tasks and the resulting benefits of each listed AI tool. The synopsis of AI-powered tools presented in the paper could serve professionals, managers and researchers in designing future policies, operational procedures and research approaches to cope with new challenges of disruptive technologies from the AI spectrum.

Recently, in the Hospitality 5.0 era, the Smart Tourism industry has experienced disruptions due to the widespread integration of cutting-edge technologies (Artificial Intelligence, Internet of Things, Robots, Big Data, and others) enabling the overall tourist experience enhancement. This study aims to identify the main clusters of technologies adopted and to highlight the competitive advantages resulting from their implementation in Smart Tourism. A meta-analysis was conducted on a final WoS sample of 60 papers published between 2015 and 2023. Four synoptic tables showcase the technologies, the processes they facilitate, the competitive advantages, and the smart destinations where they have been implemented. The originality of this research consists of the 70 competitive advantages identified across the industry, leveraged in designing the CECoR map (Customer Experience, Costs, Revenues) and the CAdSTT framework (Competitive Advantage-driven Smart Tourism Technologies). Guidelines for supporting managers in planning and initiating projects aiming at integrating technology to increase organisational value were proposed.

Motivation: The relationship between ESG factors and sustainability is a widely debated topic in the literature, but to our knowledge, there is a gap concerning the investigation of links between groups formed with ESG and other sustainability concepts, such as corporate social responsibility (CSR), green economy, circular economy, digitalization, technology, industry 4.0, and industry 5.0. Idea: The objective of this study is to identify the interest of researchers, their visibility, as well as the trends among publications, regarding the ESG factors in relation to other concepts within the realm of sustainability, like CSR, green economy, circular economy, digitalization, technology, industry 4.0, and industry 5.0. Data: The selected sample for the research includes 1430 papers screened from the Web of Science database. Tools: The aim of this study is achieved by conducting a bibliometric analysis, using VOSviewer and PowerBI. Findings: The findings of this study include the interconnectivity of selected concepts, the co-occurrence of authors’ keywords, the number of publications over time, as well as the paper types, the publishing activity by journal, the most productive authors, the co-authorship, their affiliation, the papers’ length, references, and citations trend, the most cited papers, the publishing activity by country and the collaboration patterns between countries. Contribution: This analysis supports the identification of potential gaps in current ESG-related research and points toward new areas of investigation. It also contributes to the advancement of ESG research and to the achievement of sustainable development goals.

The integration of emerging technologies in Enterprise Resource Planning systems has the potential to enhance security, automation, decision-making, and predictive capabilities. However, this also introduces new cybersecurity challenges, as the systems may become targets for malicious attacks or data breaches. Understanding the nexus between organizational systems, artificial intelligence (AI), and cyber-security requirements, offers new insights for the modern business environment. Our study begins with an exploration of recent cases of AI-enhanced cybersecurity tools implemented within organizational information systems, as these currently stand. This research landscape is our starting point for an analysis of the impact of these tools on different types of systems, of the cyber risks reported in recent literature, and the configuration of cyber-security solutions tailored after current vulnerabilities of the business environment. We also identify trends and gaps in the existing research that suggest possible new topics for further investigation.