Problem
Research questions and friction points this paper is trying to address.
delegated decision-making
agent-mediated search
information quality
market structure
trust
The Evolution of Digital Search: From Blue Links to Delegated Decision-Making
🤖 AI Summary
This study addresses the paradigm shift in digital search from user-driven link browsing toward agent-driven decision-making, which introduces systemic challenges concerning transparency, competition, and incentive alignment. The work proposes reconceptualizing search not as a conventional interface tool but as an embedded agent-based decision system, integrating agent architectures, natural language understanding, and mechanism design. Through modeling grounded in economic theory and validated by market experiments, the research demonstrates that subtle design choices—such as information access modalities, option presentation formats, and execution strategies—profoundly influence market efficiency, competitive dynamics, and welfare outcomes for both users and firms. These findings underscore the critical importance of open, transparent, and competitive system design principles in shaping future AI-native search ecosystems.
📝 Abstract
Digital search is undergoing a fundamental transformation from a human-driven process of discovery to an agent-mediated system of delegated decision-making. In the traditional model of digital search, users translate intent into keyword-based queries, evaluate ranked lists of links, and execute decisions outside the search interface. In an AI-native world, users express goals in natural language, agents interpret these intentions, and outcomes are returned as recommendations or executed decisions. This shift moves search from a link-based user interface to an embedded system component, with implications for transparency, competition, and monetization. The resulting system design problem raises key questions about information quality and access, trust, incentive alignment, and market structure. Early evidence from experimental agent-mediated marketplaces and economic theory suggests that small design choices, such as how stakeholders access information, how options are surfaced, and how actions are executed, have first-order effects on efficiency, competition, and the welfare of consumers and firms. We propose that the future of search will be determined not by incremental improvements in ranking algorithms and natural-language interfaces, but by the design of open, transparent, and competitive agentic systems that govern how decisions are made and how markets operate, highlighting a set of grand challenges at the intersection of AI, economics, and system design.
Innovation
Methods, ideas, or system contributions that make the work stand out.
agent-mediated search
delegated decision-making
AI-native systems
market design
transparent agentic systems
🔎 Similar Papers
No similar papers found.
