# The Agentic Economy

arXiv: https://arxiv.org/abs/2505.15799 · HTML: https://mlsanity.com/paper/2505.15799/

## Key facts

- Cited by 9 papers in the map (data through 14 Oct 2026).
- Placed in Social simulation and multi-agent debate, one of 16 directions in LLM agents and tool use.
- Builds on 1 of its 12 references that are in the map.
- First posted on arXiv 21 May 2025.

## Placed in

- LLM agents and tool use / [Social simulation and multi-agent debate](https://mlsanity.com/agents/social-simulation-and-multi-agent-debate/)

## Builds on (most cited first, 1 of 1)

- [Evaluating Language Model Agency through Negotiations](https://mlsanity.com/paper/2401.04536/) (2024)

## Built on by (most cited first, 9 of 9)

- [Agentic Web: Weaving the Next Web with AI Agents](https://mlsanity.com/paper/2507.21206/) (2025)
- [Magentic Marketplace: An Open-Source Environment for Studying Agentic Markets](https://mlsanity.com/paper/2510.25779/) (2025)
- [Auditing Preferences for Brands and Cultures in LLMs](https://mlsanity.com/paper/2603.18300/) (2026)
- [Holos: A Web-Scale LLM-Based Multi-Agent System for the Agentic Web](https://mlsanity.com/paper/2604.02334/) (2026)
- [Agentic Inequality](https://mlsanity.com/paper/2510.16853/) (2025)
- [Reasonably reasoning AI agents can avoid game-theoretic failures in zero-shot, provably](https://mlsanity.com/paper/2603.18563/) (2026)
- [From Product Search to Preference Articulation: The Economics of Agentic Commerce](https://mlsanity.com/paper/2608.08395/) (2026)
- [Microeconomic Foundations of Multi-Agent Learning](https://mlsanity.com/paper/2601.03451/) (2026)
- [Collaborating in Multi-Armed Bandits with Strategic Agents](https://mlsanity.com/paper/2605.13145/) (2026)

## Abstract (arXiv)

Generative AI has transformed human-computer interaction by enabling natural language interfaces and the emergence of autonomous agents capable of acting on users' behalf. While early applications have improved individual productivity, these gains have largely been confined to predefined tasks within existing workflows. We argue that the more profound economic impact lies in reducing communication frictions between consumers and businesses. This shift could reorganize markets, redistribute power, and catalyze the creation of new products and services. We explore the implications of an agentic economy, where assistant agents act on behalf of consumers and service agents represent businesses, interacting programmatically to facilitate transactions. A key distinction we draw is between unscripted interactions -- enabled by technical advances in natural language and protocol design -- and unrestricted interactions, which depend on market structures and governance. We examine the current limitations of siloed and end-to-end agents, and explore future scenarios shaped by technical standards and market dynamics. These include the potential tension between agentic walled gardens and an open web of agents, implications for advertising and discovery, the evolution of micro-transactions, and the unbundling and rebundling of digital goods. Ultimately, we argue that the architecture of agentic communication will determine the extent to which generative AI democratizes access to economic opportunity.