Beyond GPT Ownership: Intelligent and Autonomous Possession as a General Framework for Need-Driven Access to Resources, Capabilities, and Services
Abstract
The development of generative artificial intelligence has largely been organized around identifiable products, models, and agents. Users select a particular system, interact with it, and obtain services within the capabilities and constraints of that system. However, users' underlying objectives may not require ownership of, or long-term commitment to, any particular artificial intelligence model. Instead, they may seek continuous and reliable access to desired capabilities, resources, and outcomes. This paper introduces Intelligent and Autonomous Possession (IAP), a conceptual framework that shifts the primary unit of provision from a specific technological artifact to the intelligent, adaptive, and potentially autonomous maintenance of a desired possession state. Under this framework, a user specifies what they want to possess, access, or be able to accomplish, while an intelligent system determines how that requirement can be satisfied through the dynamic selection, acquisition, configuration, coordination, replacement, and release of underlying resources. The resources may include artificial intelligence models, agents, software, data, computational infrastructure, physical assets, and external services. The framework distinguishes desired possession states from implementation mechanisms, identifies multiple modes of possession, and formulates a decision model for selecting resource configurations under quality, cost, reliability, availability, privacy, and control constraints. It further introduces a possession lifecycle comprising requirement interpretation, capability decomposition, resource discovery, configuration, operation, adaptation, and termination. The paper develops conceptual propositions, identifies research questions, and proposes an empirical evaluation agenda. Rather than claiming that need-driven resource provision is entirely unprecedented, this work seeks to establish a unified research perspective in which intelligent possession, rather than the identity of a particular model or product, becomes the primary object of system design and evaluation.
Related
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BibTeX
@misc{zhang2026beyond,
title = {{Beyond GPT Ownership: Intelligent and Autonomous Possession as a General Framework for Need-Driven Access to Resources, Capabilities, and Services}},
author = {Jincheng Zhang},
howpublished = {Zenodo},
year = {2026},
month = oct,
doi = {10.5281/zenodo.23591737},
url = {https://zenodo.org/records/23591737},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - Beyond GPT Ownership: Intelligent and Autonomous Possession as a General Framework for Need-Driven Access to Resources, Capabilities, and Services
AU - Jincheng Zhang
PY - 2026
DA - 2026/10/23
PB - Zenodo
DO - 10.5281/zenodo.23591737
UR - https://zenodo.org/records/23591737
AB - The development of generative artificial intelligence has largely been organized around identifiable products, models, and agents. Users select a particular system, interact with it, and obtain services within the capabilities and constraints of that system. However, users' underlying objectives may not require ownership of, or long-term commitment to, any particular artificial intelligence model. Instead, they may seek continuous and reliable access to desired capabilities, resources, and outcomes. This paper introduces Intelligent and Autonomous Possession (IAP), a conceptual framework that shifts the primary unit of provision from a specific technological artifact to the intelligent, adaptive, and potentially autonomous maintenance of a desired possession state. Under this framework, a user specifies what they want to possess, access, or be able to accomplish, while an intelligent system determines how that requirement can be satisfied through the dynamic selection, acquisition, configuration, coordination, replacement, and release of underlying resources. The resources may include artificial intelligence models, agents, software, data, computational infrastructure, physical assets, and external services. The framework distinguishes desired possession states from implementation mechanisms, identifies multiple modes of possession, and formulates a decision model for selecting resource configurations under quality, cost, reliability, availability, privacy, and control constraints. It further introduces a possession lifecycle comprising requirement interpretation, capability decomposition, resource discovery, configuration, operation, adaptation, and termination. The paper develops conceptual propositions, identifies research questions, and proposes an empirical evaluation agenda. Rather than claiming that need-driven resource provision is entirely unprecedented, this work seeks to establish a unified research perspective in which intelligent possession, rather than the identity of a particular model or product, becomes the primary object of system design and evaluation.
ER -