Intent-Driven Interface Generation: Dynamically Constructing Task-Specific Digital Interfaces from Human Intentions

The evolution of digital interfaces has largely followed an application-centered design paradigm in which software developers define interface structures, interaction components, and functional boundaries in advance, requiring users to adapt their activities to the capabilities and organizational logic of individual applications. Although graphical user interfaces, adaptive interfaces, conversational artificial intelligence, and generative user interfaces have progressively expanded the possibilities of human–computer interaction, users frequently remain constrained by predefined application structures and must manually navigate multiple interface environments to accomplish complex objectives. This creates a potential mismatch between the flexibility of human intentions and the relatively fixed interaction structures through which digital capabilities are accessed. This paper proposes Intent-Driven Interface Generation (IDIG), a conceptual framework for dynamically constructing task-specific digital interfaces according to human intentions. Rather than requiring users to locate and operate predefined application interfaces, IDIG interprets an intended outcome, identifies the information, capabilities, and interactions required to achieve it, and generates a corresponding interface environment. The resulting interface may contain dynamically composed information panels, comparison tables, visualizations, interactive controls, execution components, contextual explanations, and external service entry points. Its structure is determined primarily by the requirements of the current task rather than by the predefined organization of an individual application. To operationalize this approach, the paper introduces the Intent-to-Interface Transformation Framework (IITF), comprising seven interconnected stages: intent acquisition, intent interpretation, task and information modeling, interface requirement derivation, dynamic component composition, interactive execution, and contextual interface reconstruction. The framework further introduces a task-oriented interface representation that connects user intentions with functional requirements, information structures, component specifications, interaction dependencies, and execution constraints. It also examines ephemeral task interfaces, which are dynamically generated for particular objectives and may be modified, retained, reconstructed, or discarded according to subsequent user requirements. A central distinction of IDIG is that it treats the interface not merely as a visual representation of an existing application, but as a dynamically constructed interaction environment organized around the completion of an intended task. This perspective potentially enables more flexible task organization, reduced application-navigation overhead, cross-capability interaction, personalized information presentation, and more direct coordination between human objectives and available digital resources. Importantly, these advantages are presented as theoretically motivated possibilities rather than experimentally established outcomes. Building upon the broader research direction of Intent-Driven Interaction and Intent-Driven Internet, this paper positions Intent-Driven Interface Generation as an interface-level mechanism through which intent-centered computing can be translated into concrete and executable human–digital interaction environments. The paper develops its conceptual architecture, formal representation, design principles, research propositions, potential advantages, evaluation methodology, and implementation challenges. It presents a research framework and does not claim completed experimental validation or demonstrated performance superiority.