Intent-Driven Internet Resource Economics: Modeling the Economic Allocation and Consumption of Distributed Digital Capabilities

The rapid development of generative artificial intelligence (AI), autonomous agents, cloud computing, application programming interfaces (APIs), search services, and distributed digital platforms is transforming the structure of Internet-based service consumption. Traditionally, users access digital services through applications, websites, subscriptions, and platform-specific interfaces. The economic organization of these services is generally based on predefined pricing models, individual transactions, subscription plans, usage-based billing, and platform-controlled resource allocation. However, as intelligent systems increasingly interpret user intentions and autonomously coordinate heterogeneous digital capabilities to accomplish complex tasks, the mechanisms through which Internet resources are valued, allocated, consumed, and compensated may require a broader conceptual foundation. This paper proposes Intent-Driven Internet Resource Economics (IDIRE), a conceptual research framework for investigating the economic organization of distributed digital capabilities within an intent-driven Internet. Rather than treating digital services exclusively as independent products or applications, IDIRE conceptualizes them as economically measurable capabilities that can be dynamically discovered, evaluated, selected, combined, and consumed according to user intentions and task requirements. The proposed framework introduces six interconnected economic mechanisms: Intent-Based Resource Valuation, Distributed Capability Pricing, Economic Execution Modeling, Multi-Service Cost Allocation, Budget-Constrained Capability Consumption, and Economic Incentives for Capability Providers. These mechanisms establish a conceptual relationship between human intentions, task-level economic value, capability-level resource requirements, service-provider pricing, execution costs, and the distribution of economic rewards. To formalize the framework, this paper develops an intent-driven resource valuation model, a capability-level cost representation, a budget-constrained economic execution model, and a multi-provider resource allocation mechanism. It further introduces the concepts of intent-conditioned marginal resource value, execution-dependent economic consumption, resource scarcity valuation, and task-oriented economic settlement. The framework distinguishes between the economic price of a digital capability, its actual execution cost, its contextual contribution to task completion, and the value of the final outcome. A central argument of this research is that the economic value of a digital capability cannot necessarily be determined independently of the intention it serves. The same AI model, search service, API, or computational resource may have substantially different economic utility depending on the task, execution context, alternative capabilities, budget constraints, and contribution to the intended outcome. Consequently, resource allocation in an intent-driven Internet may need to move beyond isolated service selection toward coordinated economic optimization across multiple heterogeneous capabilities. The paper also investigates potential advantages concerning resource utilization, economic efficiency, service-provider participation, distributed capability markets, task-level pricing, adaptive budgeting, and cross-platform economic coordination. It proposes research propositions and an evaluation methodology for examining these mechanisms under different resource availability, pricing structures, task complexity, and economic constraints. Importantly, IDIRE is presented as a conceptual research framework rather than an experimentally validated economic system. It does not claim that intent-based resource allocation, dynamic pricing, or multi-service economic coordination has never previously been investigated. Instead, it seeks to establish a broader economic perspective in which human intentions and intended task outcomes become organizing principles for the valuation, allocation, consumption, and compensation of distributed Internet capabilities.