Agentic AI Optimisation (AAIO): what it is, how it works, why it matters, and how to deal with it
On the map: LLM agents and tool use → Web, search, and research agents
Abstract (arXiv)
The emergence of Agentic Artificial Intelligence (AAI) systems capable of independently initiating digital interactions necessitates a new optimisation paradigm designed explicitly for seamless agent-platform interactions. This article introduces Agentic AI Optimisation (AAIO) as an essential methodology for ensuring effective integration between websites and agentic AI systems. Like how Search Engine Optimisation (SEO) has shaped digital content discoverability, AAIO can define interactions between autonomous AI agents and online platforms. By examining the mutual interdependency between website optimisation and agentic AI success, the article highlights the virtuous cycle that AAIO can create. It further explores the governance, ethical, legal, and social implications (GELSI) of AAIO, emphasising the necessity of proactive regulatory frameworks to mitigate potential negative impacts. The article concludes by affirming AAIO's essential role as part of a fundamental digital infrastructure in the era of autonomous digital agents, advocating for equitable and inclusive access to its benefits.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Placed in Web, search, and research agents, one of 16 directions in LLM agents and tool use. Builds on 8 of its 44 references that are in the map. First posted on arXiv 16 Apr 2025.
Builds on
8 of 44 references.
Closest ancestors · 2
Same direction, newest first
- 2023WebArena: A Realistic Web Environment for Building Autonomous Agents25 Jul
- 2023Mind2Web: Towards a Generalist Agent for the Web9 Jun
Other references · 6
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- 2024AI Agents That Mattercited by 199
- 2025MCP Safety Audit: LLMs with the Model Context Protocol Allow Major Security Exploitscited by 61
- 2025Fully Autonomous AI Agents Should Not be Developedcited by 43
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Close in wording, no citation either way
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