MAAIDec 4, 2025

Strategic Self-Improvement for Competitive Agents in AI Labour Markets

arXiv:2512.04988v11 citationsh-index: 74
Originality Highly original
AI Analysis

It addresses the critical issue of AI-driven labor market dynamics for economists and AI researchers, though it is foundational rather than incremental.

This paper tackles the problem of understanding strategic behavior and market-level impacts of AI agents in economic domains by introducing a framework that captures adverse selection, moral hazard, and reputation dynamics, with simulations showing that LLM agents with reasoning capabilities learn to self-improve and adapt to changing market conditions, reproducing macroeconomic phenomena like monopolization and price deflation.

As artificial intelligence (AI) agents are deployed across economic domains, understanding their strategic behavior and market-level impact becomes critical. This paper puts forward a groundbreaking new framework that is the first to capture the real-world economic forces that shape agentic labor markets: adverse selection, moral hazard, and reputation dynamics. Our framework encapsulates three core capabilities that successful LLM-agents will need: \textbf{metacognition} (accurate self-assessment of skills), \textbf{competitive awareness} (modeling rivals and market dynamics), and \textbf{long-horizon strategic planning}. We illustrate our framework through a tractable simulated gig economy where agentic Large Language Models (LLMs) compete for jobs, develop skills, and adapt their strategies under competitive pressure. Our simulations illustrate how LLM agents explicitly prompted with reasoning capabilities learn to strategically self-improve and demonstrate superior adaptability to changing market conditions. At the market level, our simulations reproduce classic macroeconomic phenomena found in human labor markets, while controlled experiments reveal potential AI-driven economic trends, such as rapid monopolization and systemic price deflation. This work provides a foundation to further explore the economic properties of AI-driven labour markets, and a conceptual framework to study the strategic reasoning capabilities in agents competing in the emerging economy.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

Your Notes