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.
Healthcare is a relevant setting for examining how innovation management shapes competitiveness, sustainability, and value-creation capabilities. Recent debate has shifted from a focus on the technical performance of AI systems to broader concerns related to implementation, accountability, trustworthiness, evaluation, and organisational sustainability. This shift is crucial in healthcare, where Agentic AI and GenAI are not merely digital transformation tools, but sociotechnical systems that potentially affect clinical practices, decision-making processes, care coordination, patient-doctor relationships, resource allocation and costs optimization.
AI and GenAI are sociotechnical systems with growing autonomy and interactive capabilities, thereby raising new questions around trust, responsibility, human oversight, and governance. As such, they pose a significant challenge to enterprise information management, affecting processes, data, professional roles, compliance, procurement, and monitoring systems.
The deployment of Agentic AI and GenAI occurs in high-risk, highly regulated, data and human-intensive settings. Healthcare organizations must balance innovation with patient safety, care quality, ethical and regulatory issues, data protection and human oversight preservation. Errors, biases and unclear accountability may affect patients, professionals and healthcare ecosystems.
This Special Issue seeks theoretical and empirical contributions examining how health systems, healthcare organizations, and providers develop capabilities, governance structures, and evaluation practices to move from experimentation to technology adoption and integration. Particular attention will be given to agentic workflow integration, responsible value creation, data governance, clinical and managerial accountability, human oversight, professional role reconfiguration, patient-doctor relationship, organisational capabilities and compliance with existing regulatory frameworks.
By focusing on healthcare as the empirical and theoretical context, this Special Issue aims to generate new insights into how Agentic and GenAI systems can be responsibly embedded in healthcare organizations while balancing innovation, safety, equity, trust, regulatory compliance and measurable clinical, organisational, and societal value.