English

Agentization of Digital Assets for the Agentic Web: Concepts, Techniques, and Benchmark

Multiagent Systems 2026-04-07 v1 Artificial Intelligence

Abstract

Agentic Web, as a new paradigm that redefines the internet through autonomous, goal-driven interactions, plays an important role in group intelligence. As the foundational semantic primitives of the Agentic Web, digital assets encapsulate interactive web elements into agents, which expand the capacities and coverage of agents in agentic web. The lack of automated methodologies for agent generation limits the wider usage of digital assets and the advancement of the Agentic Web. In this paper, we first formalize these challenges by strictly defining the A2A-Agentization process, decomposing it into critical stages and identifying key technical hurdles on top of the A2A protocol. Based on this framework, we develop an Agentization Agent to agentize digital assets for the Agentic Web. To rigorously evaluate this capability, we propose A2A-Agentization Bench, the first benchmark explicitly designed to evaluate agentization quality in terms of fidelity and interoperability. Our experiments demonstrate that our approach effectively activates the functional capabilities of digital assets and enables interoperable A2A multi-agent collaboration. We believe this work will further facilitate scalable and standardized integration of digital assets into the Agentic Web ecosystem.

Keywords

Cite

@article{arxiv.2604.04226,
  title  = {Agentization of Digital Assets for the Agentic Web: Concepts, Techniques, and Benchmark},
  author = {Linyao Chen and Bo Huang and Qinlao Zhao and Shuai Shao and Zhi Han and Zicai Cui and Ziheng Zhang and Guangtao Zeng and Wenzheng Tang and Yikun Wang and Yuanjian Zhou and Zimian Peng and Yong Yu and Weiwen Liu and Hiroki Kobayashi and Weinan Zhang},
  journal= {arXiv preprint arXiv:2604.04226},
  year   = {2026}
}
R2 v1 2026-07-01T11:54:38.813Z