Strategic Perspectives on Artificial Intelligence Applications in Ocular Oncology: Managerial Insights and General Use Cases

Purpose: A pivotal dimension of healthcare’s digital transformation lies in the progressive integration of information and communication technologies (ICT), with Artificial Intelligence (AI) emerging as a cornerstone of this evolution. Among the most transformative advancements is the deployment of AI-driven methodologies within oncology. Within this context, ocular oncology represents a critical and increasingly prioritized area for innovation. This study concentrates on the possible strategic application of AI technologies from the management perspective with the vision to optimize healthcare processes encompassing, for example, diagnosis, education, therapeutic interventions, and longitudinal monitoring of ocular malignancies. Methods: Prior to initiating AI-driven interventions, healthcare management must rigorously assess which use cases yield the greatest potential for strategic and economic impact, given the substantial resource requirements typically associated with such initiatives. To systematically identify these use cases, this study adopts the Design Science Research (DSR) methodology. DSR provides a structured framework for analyzing organizational needs at the Enterprise Architecture (EA) level, enabling the alignment of functional domains and technological components with prioritized use cases. Through this qualitative, design-oriented approach, critical application requirements are elicited, thereby substantiating the feasibility and relevance of AI-enabled solutions in advancing strategic objectives and contributing to the overarching vision of healthcare digital transformation. Results: The research process facilitated the identification of several generic use cases within ophthalmology, ultimately converging on ocular oncology as the focal domain. Within this framework, the functional and structural components of ICT were systematically aligned with the established linkages between healthcare management imperatives and the prioritized use cases. The overarching aim of the proposed AI-driven initiative is to advance healthcare management practices through targeted technological integration. For this goal, special applications are envisioned to incorporate the AI-powered modules or AI agents within existing health information systems, in vision supporting also the three-dimensional image data for the augmented and/or virtual reality platforms. Conclusion: AI-driven methodologies should be strategically employed to automate non-manufacturing processes within healthcare domains that exhibit the greatest need for innovation, such as ocular oncology. In this context, informed managerial decision-making can substantially accelerate service delivery by reducing turnaround times, mitigating reliance on highly specialized personnel, and ultimately improving patient-centered outcomes and satisfaction in healthcare services.