Yao Shi, University of North Carolina Wilmington

Lukas R. G. Fitz, Brandenburg University of Technology Cottbus – Senftenberg

Fanny-Eve Bordeleau, Dalhousie University

Claudia Pelletier, Université du Québec à Trois-Rivières

Judith Gebauer, University of North Carolina Wilmington

SMEs are significantly lagging behind large organizations in AI adoption due to structural and financial constraints, limited access to technology, insufficient data infrastructure, and workforce skill shortages. This growing digital divide threatens economic competitiveness and equity across regions. As SMEs form a critical part of global economies, their meaningful participation in AI-enabled digital transformation is essential for building resilient and fair economic systems.

This topical collection welcomes multidisciplinary research exploring AI adoption, implementation challenges, workforce development, ethical considerations, and best practices in SMEs. The collection invites theoretical, empirical, design-oriented, and technical contributions that address opportunities and strategies for AI-enabled transformation in the SME context, including case studies and innovation ecosystem perspectives.

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Potential topics

• AI adoption drivers, strategies, and readiness models for SMEs' digital transformation
• AI barriers, challenges, and failures for SMEs' digital transformation
• Skill gaps, workforce development, organizational learning and managerial capabilities for AI-enabled practices in SMEs
• Ethical and societal issues surrounding AI in SMEs and their environments
• Case studies of AI adoption and use in SMEs and their business ecosystems
• AI innovation ecosystems inclusive of SMEs
• Design of SME-suitable AI artefacts
• SME practitioner perspectives on AI
• Implementing human-centered AI for SMEs
• AI-enabled business model innovation pathways in SMEs
• AI governance frameworks for SMEs
• AI-driven shifts in SME strategies for competition, co-opetition, co-creation, and open innovation
• Development, configuration, and management of AI ecosystems for SMEs

Timeline

• September 15, 2026: Open for submissions
• March 15, 2027: Submission deadline

This Journal of Enterprise Information Management Special Issue seeks to understand Agentic Artificial Intelligence and Generative AI (GenAI) in healthcare, and how these technologies impact the governance, strategy, and value creation of healthcare organizations. In technological innovation, digital technologies are reconfiguring value creation processes and prompting organizations to develop new adaptive strategies. In healthcare, this transformation is driving the adoption of innovative solutions to enhance value for stakeholders while supporting more personalised, predictive, and preventive models of care. AI and GenAI are emerging as strategic levers for optimising resource allocation, supporting new care delivery paradigms, and accelerating research and development. The rapid emergence of Agentic AI systems introduces a further step in this transformation, with AI technologies moving from reactive tools towards semi-autonomous systems able to plan, coordinate and monitor actions across complex organizations.

Appel publié par Journal of Enterprise Information Management. Lire l'appel complet sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• How are GenAI and Agentic AI reshaping clinical, administrative, and managerial workflows in healthcare organizations?
• How do healthcare organizations govern Agentic AI systems across care pathways?
• What organizational capabilities are needed to move from experimental GenAI applications to integrated and scalable Agentic healthcare systems?
• How can healthcare organizations ensure meaningful human oversight when AI systems become more autonomous, proactive, and embedded in clinical or administrative processes?
• How do GenAI and agentic AI create, capture, or potentially destroy value for different healthcare stakeholders?
• How do Agentic and GenAI systems transform healthcare knowledge management?
• How can healthcare organizations evaluate and measure the clinical, organizational, economic, ethical, and societal value generated by GenAI and Agentic AI adoption?
• What governance mechanisms are needed to ensure accountability, transparency and regulatory compliance in AI-enabled healthcare organizations?
• How do GenAI and Agentic AI affect decision-making processes within healthcare organizations?
• How can healthcare organizations manage risks related to automation bias, inequitable outcomes and over-reliance on AI?
• How do agentic AI and GenAI support healthcare system sustainability?

Timeline

• January 1, 2027: Opening date for manuscript submissions
• June 30, 2027: Closing date for manuscript submissions