Many governments are focusing on adopting Artificial Intelligence (AI)-based chatbot technology to enhance work efficiency and improve e-government services. Jordan was among the first Middle Eastern countries to implement AI chatbots to offer various e-services to its citizens. While previous studies have examined the adoption of AI chatbots, they have not explored citizen adoption within the Jordanian context. This research investigates the key factors influencing citizen adoption of e-government chatbot services in Jordan by extending the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) theory with additional external variables. A longitudinal survey of 319 Jordanian citizens was conducted, with data collected at two different points using Structural equation modeling to test the hypotheses. Results demonstrate that attitude, performance expectancy, effort expectancy, social influence, hedonic motivation, facilitating conditions, self-efficacy, anthropomorphism, personal innovativeness, and trust all positively impacted Jordanian citizens' intentions to use e-government chatbot services, whilst anxiety had a negative effect. Behavioral intentions, facilitating conditions, synchronicity, active control, and ubiquitous connectivity, positively influenced usage behavior, which in turn significantly influenced satisfaction. Satisfaction also influenced citizens' future continuance usage intentions. This study offers valuable insights for enhancing e-government chatbot features to meet citizens' needs within a Middle Eastern context.

In an era increasingly dominated by artificial intelligence (AI), the essence of human conversation is undergoing significant transformation. Once exclusively human, conversation is now increasingly mediated by AI agents, voice assistants, and digital platforms. This paper critically explores this profound shift, examining the nature and implications of hybrid human machine discourse. Addressing three fundamental questions, we interrogate what constitutes genuine conversation when one party lacks consciousness and emotion; how traditional norms of human dialogue translate into human-machine interactions; and what considerations developers and governance frameworks must prioritize in this evolving context. Building upon Nass and Brave’s (2005) concept of “voice activation,” which demonstrates humans’ inherent social responses toward artificial speech, this study identifies the dual promise and peril of conversational AI, emphasizing the risks of confusion, over-trust, and emotional misdirection. Arguing that AI-driven dialogue is not merely automation but a profound cultural and ethical shift, this research advocates for new literacies, ethical frameworks, and a re-evaluation of what authentic communication entails. By tracing the philosophical roots and current technological practices of conversation, the study underscores the urgency of rethinking communication ethics, literacy, and practice in our increasingly hybrid human-machine conversational landscape.

Purpose-This conceptual article proposes and explores Agent Project Management (APM) as a governance-first model for integrating AI agents into project workflows. We examine how AI agents can revolutionise project management by boosting efficiency and enhancing decision-making, while addressing critical governance, accountability and risk concerns. Design/methodology/approach-This viewpoint article synthesises existing research to develop a novel APM model. It is framed through an original integration of three complementary lenses: socio-technical systems, governance and decision rights, and project-as-practice. Findings-The article presents the APM model, built upon four core constructs (data maturity; transparency/ auditability; conditional autonomy with escalation; benefits-aligned objectives), and formulates four testable propositions linking these constructs to project performance, trust, and value. Originality/value-The article's primary contribution is the development and positioning of the APM model, which provides a structured framework for human-agent teamwork with conditional autonomy and inspectable accountability. The integration of the three theoretical lenses and the articulation of the four propositions offer distinct and actionable foundations for future research and practice.

PurposeThis paper aims to explore how biomimetic principles can inform governance models for agentic artificial intelligence (AI) systems, autonomous, adaptive entities that challenge traditional oversight frameworks. It argues that nature-inspired governance offers a dynamic alternative to static, compliance-based models. Design/methodology/approachThis study adopts a conceptual viewpoint approach. It synthesizes literature on AI governance, systems theory and biomimicry, applying thematic analysis to existing frameworks and mapping identified gaps to five natural principles: symmetry, fractals, cymatic feedback, self-organization and phase transitions. FindingsCurrent governance frameworks lack mechanisms for managing emergent behaviors and distributed agency in agentic AI. The proposed biomimetic lens offers a conceptual scaffold for adaptative, decentralized governance aligned with ethical norms. Research limitations/implicationsNo empirical validation is provided; future research should use simulation or design science to test biomimetic governance in real-world contexts. Practical implicationsThis paper offers actionable guidance for policymakers and system designers to adaptive, resilient governance mechanisms into agentic AI architectures. Originality/valueIntroduces “Biomimic AI” as a novel paradigm for governing agentic systems, extending systems theory and responsible AI discourse through nature-inspired design logic.

It is widely accepted that the impact of Generative Artificial Intelligence (GenAI) has been nothing short of transformational, with tangible impacts on industry, education, healthcare and government. But beyond the headlines, how are organisations actually using GenAI, what are the key challenges experienced by decision makers and has the reality on the ground matched the hype? This study adopts a mixed-methods approach, utilising the Technology-Organisation-Environment (TOE) framework to reveal greater insights to how organisations are adopting GenAI, the drivers that affect decision making and the key challenges associated with greater use of the technology. This research adopts a mixed method approach incorporating an explorative qualitative step with industry participants followed by a survey of 304 (three hundred and four) decision makers from a cross section of industry sectors from around the world including: North America, Europe, Africa, Australia and Asia, to gain further insight to the underlying factors that drive GenAI adoption. The research model was validated using Structural Equation Modelling (SEM) and reveals the intricate and inherent complexities related to greater levels of GenAI adoption. The analysis highlights the critical role of change capacity of the organisation in moderating complexity and staff skills. This research provides valuable and timely insights for senior management and policy makers that are attempting to better understand the interdependencies and perspectives on the key challenges facing organisations looking to deliver greater impact on organisational performance through GenAI.

The integration of generative artificial intelligence (GenAI) holds great potential to transform the project management profession, which can bring both substantial benefits and significant disruption. This study argues that effective GenAI adoption requires not only technical skills but also mindfulness to navigate its complexities and challenges. This study explores how mindfulness supports project managers in leveraging GenAI technologies to innovate work practices. We argue that project managers with higher mindfulness levels tend to be more open, attentive, and creative in crafting their immediate work environment. This, in turn, encourages project managers to explore how GenAI can optimise workflows, and ultimately improve the frequency and effectiveness of GenAI use. The mediating role of job crafting was verified in this study using a two-wave time-lagged design among 441 project managers. The moderating role of project complexity and GenAI knowledge were also validated in this mediation model. This study provides timely guidance on developing mindfulness and job crafting strategies to support project innovation in an era where emerging technologies are transforming traditional project management practices.

The project management profession is undergoing transformative change with the integration of Artificial Intelligence (AI), redefining core methodologies and decision-making processes. As societal expectations rise and technological complexity intensifies, project managers face unprecedented challenges. By 2030, AI-driven predictive insights and modelling capabilities are expected to significantly enhance efficiency, raising critical questions about the evolving role of human project managers. Will AI take the lead in key decisions, or will human attributes such as creativity, ethical judgment, and emotional intelligence remain essential? Framed as PM2030, this study explores future scenarios through expert insights from academia and industry. Using an opinion-based approach, we introduce two conceptual models: the AI-Augmented Ethics-Centric Model and the Predictive Model for AI Adoption and Human Trust. These models offer a forward-looking vision of project management shaped by automation, ethics, and human-AI collaboration. This study contributes to the growing discourse on the human-centric evolution of AI-enabled project management.

PurposeThe launch of ChatGPT has brought the large language model (LLM)-based generative artificial intelligence (GAI) into the spotlight, triggering the interests of various stakeholders to seize the possible opportunities implicated by it. Nevertheless, there are also challenges that the stakeholders should observe when they are considering the potential of GAI. Given this backdrop, this study presents the viewpoints gathered from various subject experts on six identified areas.Design/methodology/approachThrough an expert-based approach, this paper gathers the viewpoints of various subject experts on the identified areas of tourism and hospitality, marketing, retailing, service operations, manufacturing and healthcare.FindingsThe subject experts first share an overview of the use of GAI, followed by the relevant opportunities and challenges in implementing GAI in each identified area. Afterwards, based on the opportunities and challenges, the subject experts propose several research agendas for the stakeholders to consider.Originality/valueThis paper serves as a frontier in exploring the opportunities and challenges implicated by the GAI in six identified areas that this emerging technology would considerably influence. It is believed that the viewpoints offered by the subject experts would enlighten the stakeholders in the identified areas.

The emergence of AI agents and agentic systems represents a significant milestone in artificial intelligence, enabling autonomous systems to operate, learn, and collaborate in complex environments with minimal human intervention. This paper, drawing on multi-expert perspectives, examines the potential of AI agents and agentic systems to reshape industries by decentralizing decision-making, redefining organizational structures, and enhancing cross-functional collaboration. Specific applications include healthcare systems capable of creating adaptive treatment plans, supply chain agents that predict and address disruptions in real-time, and business process automation that reallocates tasks from humans to AI, improving efficiency and innovation. However, the integration of these systems raises critical challenges, including issues of attribution and shared accountability in decision-making, compatibility with legacy systems, and addressing biases in AI-driven processes. The paper concludes that while agentic systems hold immense promise, robust governance frameworks, cross-industry collaboration, and interdisciplinary research into ethical design are essential. Future research should explore adaptive workforce reskilling strategies, transparent accountability mechanisms, and energy-efficient deployment models to ensure ethical and scalable implementation.

Purpose-Artificial intelligence (AI) agents and agentic systems have the potential to transform the tourism and hospitality (T&H) industry by automating existing processes and improving operational efficiency. This viewpoint paper aims to explore and analyze the potential opportunities and challenges, and establish a comprehensive research agenda for developing AI agents and agentic systems within the T&H industry. Design/methodology/approach- This article comprehensively analyzes current literature, user sentiment analysis and market trends assessment on AI agents and agentic systems. It identifies critical areas where these technologies can transform the T&H industries, providing valuable insights into this emerging field and its potential for driving innovation and efficiency. Findings- Sentiment analysis reveals that 65% of social media users positively view OpenAI's new AI agent, praising its automation capabilities. Meanwhile, 22% raise concerns about technical flaws, accessibility and ethics, while 13% remain neutral. AI agents offer opportunities to enhance efficiency, personalize services and support sustainability in T&H. However, challenges persist in development and implementation, with concerns from businesses, customers and regulators. This article highlights both the opportunities and challenges AI agents present in T&H industries. Research limitations/implications- This paper provides valuable insights for stakeholders in the T&H industry, considering the adoption of AI agents. The authors present an overview of the potential challenges involved in adopting this emerging technology and discuss key organizational barriers. Originality/value- This study examines the application of AI agents and agentic systems in T&H, highlighting opportunities and challenges may face during their adoption. The paper contributes original insights into how these systems can reshape industry practices, providing a foundation for future research and practical applications.

The proliferation of generative artificial intelligence (GenAI) has disrupted academic institutions across the world, presenting transformative challenges for decision makers, and leading to questions around existing methods and practices within higher education (HE). The widespread adoption of GenAI tools and processes highlights an ongoing change to existing perceptions of the role of humans and machines. Academics have expressed concerns relating to: academic integrity, undermining critical thinking, lowering of academic standards and the threat to existing academic models. This study presents a mixed methods approach to developing valuable insight to the key underlying challenges impacting GenAI adoption within HE. The results highlight many of the key challenges impacting decision makers in the formation of policy and strategic direction. The findings identify significant interdependencies between the key underlying challenges associated with GenAI adoption in HE. We further discuss the implications in the findings of the high levels of driving power of the factors: (i) perceived risks from Large Language Model training and learning; (ii) the reliability of GenAI outputs in the context of impact on creativity and decision making; (iii) the impact from poor levels of GenAI platform regulation. We posit this research as offering new insight and perspective on the changing landscape of HE through the widespread adoption of GenAI.

Social commerce has evolved into a mainstream channel for marketers and businesses for selling products online. However, consumers in many developing economies have yet to fully adopt social commerce technology. This research, therefore, aims to develop and empirically validate a conceptual model for understanding the factors influencing consumer adoption of social commerce in Bangladesh using an adapted and extended version of the Meta-UTAUT model. Analysis was undertaken to determine the appropriateness of external constructs such as trust, social support, anxiety, grievance redressal, innovativeness, and continuous participation intention. This research collected data from 402 social commerce users from Bangladesh to test and validate the proposed research model. The results suggest that performance expectancy, effort expectancy, innovativeness and trust have a direct influence on consumer attitude, whilst social influence, grievance redressal, facilitating conditions, social support, anxiety, and attitude, significantly influence usage behavior. The results also found that usage behavior is a strong predictor of continuous participation intention. This research contributes to existing knowledge by conceptualizing and validating a technology adoption model, which emphasizes the role of anxiety and grievance redressal in consumer acceptance of social commerce.

Since the advent of the digital age, the transformation of government operations, policy-making, citizen engagement, and public services has fundamentally reshaped the relationships between citizens and public institutions. Digital government, as a field of study, has evolved to address the complex challenges at the intersection of technology, governance, and society. Over the past decades, Government Information Quarterly (GIQ) has played a pivotal role in documenting and shaping this evolution from basic computerization to sophisticated digital transformation initiatives. The impact of digitalization extends across all aspects of public administration, from service delivery and policy-making to citizen engagement and democratic processes. This study brings together perspectives from leading digital government scholars to examine the nature of digital government research. Through the analysis of the journal's distinctive identity and characteristics, evolution, theoretical landscape, and methodological approaches, it offers insights into how GIQ has evolved to a transdisciplinary platform that bridges theoretical foundations with practical applications while consistently addressing emerging technological challenges, fundamental public sector values, and high-value public policy goals.

Generative AI (GenAI) is disrupting global IT management and challenging established practice. The increasing use of GenAI technology is redefining localization, transforming existing workforce roles, outsourcing strategy, and team dynamics. Simultaneously, GenAI's security complexities have prompted the rethinking of existing risk frameworks to meet a new set of challenges from GenAI enhanced cyber threats. This article explores these complex and converging factors, providing a roadmap to address GenAI's significant impact on global IT management. We advocate the responsible adoption of GenAI and importance of building resilient, value-driven, globally consistent IT ecosystems able to adapt to the significant challenges and opportunities from the use of GenAI.

Purpose This article aims to explore the transformative potential of generative artificial intelligence (GenAI) in procurement and supply chain management (SCM), with a focus on its practical applications, strategic implications and integration challenges. Design/methodology/approach Adopting a conceptual approach, this article presents the authors’ views and arguments, supported by a review of existing literature and informed by insights from discussions with industry experts. The discussion in this conceptual article is anchored in the supply chain operations reference model. Findings This research addresses critical questions regarding the practical and strategic impacts of GenAI, emphasizing its ability to simulate scenarios, deliver real-time insights and enable data-driven decision-making. At the same time, it acknowledges the barriers to adoption, including system integration challenges, data privacy and security concerns and the skills gap in effectively deploying GenAI tools. Research limitations/implications This work focuses on selected industries and regions, and it needs to be extended further to increase the generalizability of the findings. Ethical, technical and social dimensions, such as bias, data privacy and workforce implications, are briefly addressed but require deeper exploration. Additionally, the dynamic nature of GenAI may render some recommendations obsolete over time, making continuous evaluation necessary as the technology evolves. Originality/value This article provides recommendations and identifies future research trajectories to guide researchers and practitioners in harnessing the potential of GenAI for impactful and sustainable transformation in supply chain and procurement.

The rise of the metaverse—a convergence of virtually enhanced physical reality and persistent virtual spaces—presents transformative potential for the healthcare sector. This study systematically explores how metaverse technologies, such as virtual reality (VR), augmented reality (AR), mixed reality (MR), and digital twins, contribute to achieving United Nations Sustainable Development Goal 3 (SDG3), which focuses on good health and well-being. By integrating these technologies, the metaverse offers innovative solutions for telemedicine, medical training, mental health support, public health education, and global medical research collaboration. This study maps the current research landscape, highlighting the capacity of metaverse technologies to address critical healthcare challenges and improve patient outcomes. We analyze the evolution of metaverse-related topics, tracking the shift from technological development to healthcare applications for SDG3. We map keyword trends to show how metaverse technologies are increasingly applied to improve healthcare and support SDG3. This study reviews the highly cited publications for each major topic identified by BERTopic modeling in the context of integrating digital twins and VR technologies in healthcare. Digital twins enhance healthcare processes by improving diagnosis and treatment, contributing to SDG3 targets. VR technologies in rehabilitation show promising results in improving physical and cognitive health, aligning with SDG3 targets. The role of VR in addiction recovery and mental health highlights its potential as an innovative therapeutic method. The integration of metaverse technologies, such as AR and VR, improves training, surgical precision, and pain management, advancing global health goals and supporting various SDGs. High acceptance rates among healthcare professionals and patients reflect the perceived benefits and alignment of these technologies with existing practices. However, successful adoption requires addressing ethical, legal, and privacy concerns, as well as ensuring equitable access and robust regulatory frameworks. This study underscores the metaverse’s potential to revolutionize healthcare delivery, training, and research, supporting the attainment of SDG3.

The digital transformation of the FinTech industry has revealed a plethora of significant challenges for industry decision makers and wider stakeholder groups as organisations contend with the onset of new regulatory frameworks, legacy systems, flexible business models and alignment with corporate social responsibility practice. The reshaping of organisations and drive to greater levels of decentralisation and employee centric practice, presents a cultural shift for the sector, with implications for the success and resulting benefits of change across the industry. This study aims to develop novel insight to the ‘lived in’ impact of digital transformation within the FinTech industry from a factor interdependency perspective. This research adopts a mixed methods approach incorporating Interpretive Structural Modelling, Analytical Hierarchy Process and interviews with expert participants, to offer a unique perspective on the challenges and unintended consequences of industry level technological change. The findings highlight the high levels of interdependency and priority for challenges related to the investment in products and infrastructure for new markets, criticality of stakeholder support and development of a digital mindset for the adoption of new technologies.

“Artificial Intelligence” in all its forms has emerged as a transformative technology that is in the process of reshaping many aspects of industry and wider society at a global level. It has evolved from a concept to a technology that is driving innovation, transforming productivity and disrupting existing business models across numerous sectors. The industrial and societal impact of AI is profound and multifaceted, offering opportunities for growth, efficiency, and improved healthcare, but also raising ethical and societal challenges as the method is integrated into many aspects of human life and work. This editorial is developed by contributors of the 4th Royal Society Yusef Hamied Workshop ( in 2023 devoted to Artificial Intelligence), designed to enhance collaboration between Indian and the UK scientists and to explore future research opportunities. The insights shared at the workshop are shared here.