Intent-Driven Interaction: Toward a New Paradigm of Human–Internet Interaction Through Autonomous Capability Orchestration

The evolution of human–computer interaction has been characterized by successive efforts to reduce the distance between human intentions and computational capabilities. From command-line interfaces and graphical user interfaces to search engines and conversational artificial intelligence, each technological generation has introduced new ways for users to communicate with and access digital systems. However, despite these developments, users are still frequently required to determine which tools, applications, or services are appropriate for their objectives and how to coordinate them effectively. This paper proposes Intent-Driven Interaction (IDI) as a conceptual paradigm for the next stage of human–internet interaction. Under this paradigm, users express their intended outcomes rather than selecting and operating individual digital tools. Intelligent systems interpret these intentions, assess the capabilities required, and autonomously orchestrate available digital resources to accomplish the requested tasks. Building upon the author's previously published research framework, Generative AI and Search Engine Orchestration: A Unified Framework for Intent-Driven Internet Task Routing and Hybrid Execution (Zhang, n.d.), this paper extends the original investigation from the coordination of generative AI and search engines toward a broader conceptual examination of human–internet interaction. While the earlier GASEO framework addresses how generative AI and search capabilities can be dynamically selected and coordinated, the present paper examines the more fundamental interaction paradigm underlying such orchestration: the transition from tool-centered interaction toward intent-centered interaction. To operationalize this paradigm, this paper introduces Intent-Driven Capability Orchestration (IDCO), a conceptual framework comprising five interconnected stages: intent understanding, capability assessment, orchestration planning, adaptive execution, and outcome evaluation. It further examines the relationship between IDI and existing approaches to human–computer interaction, intelligent information retrieval, generative AI, and autonomous agent systems. The paper proposes a set of research propositions and identifies challenges concerning intent ambiguity, capability discovery, orchestration reliability, computational efficiency, transparency, and human oversight. Rather than claiming that intent-based computing or autonomous tool orchestration has never previously been explored, this work seeks to establish a broader conceptual perspective in which user intent becomes the primary organizing principle of digital interaction and heterogeneous computational capabilities are dynamically coordinated around intended outcomes.