Exploring the Commercial Trajectories of LLMs: Business Models and Advertising Perspectives

Abstract

As large language models (LLMs) gain millions of individual and business users, their rapid adoption has raised critical questions about economic sustainability and commercialization strategies. This paper examines monetization strategies for LLMs, providing a structured overview of existing and emerging revenue models, including subscription and pay-per-use access plans. Particular emphasis is placed on the potential of advertising-based models that leverage the unique strengths of LLMs. The paper also presents eight potential scenarios for the commercial future of LLMs, ranging from advertising-based, hybrid, and public sector funding models to the dominance of open source solutions and blockchain-based microtransactions. Drawing parallels to the evolution of search engine monetization, the authors argue that hybrid approaches (e.g., combining advertising revenue with other sources) may represent the most viable future for funding LLMs. This work contributes to a deeper understanding of the commercial forces shaping the next phase of generative artificial intelligence deployment.

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