Defining the AI App Economy: A Quantitative Analysis of Generative Artificial Intelligence Applications

The recent uproar in generative artificial intelligence (AI) increasingly poses the need to study these emerging technologies. A first step is to analyse the economic structure, which echoes the structures of the app economy that emerged with the advent of smartphones and digital platforms in the late 2000s. Although the app economy revolutionised interaction with technology, it also revealed critical issues such as market saturation and uncertain profitability due to fierce competition and the proliferation of applications with low practical utility. Similarly, today's AI app economy is characterised by a rapid proliferation of AI applications, many of which lack a clear business model or significant added value for the end-user, but with a major economic, energy and social impact.

This study aims to define the AI app economy as a research field through a quantitative analysis of its economic characteristics. Data from 2023 to 2024 were collected from the three main aggregators of generative AI applications, using descriptive analysis and text mining techniques on application descriptions to obtain data on the type of economic model. This made it possible to identify application sectors, specific uses and service types.

The results provide insights into the distribution of applications across sectors and the prevalence of specific use cases. By mapping the landscape of the economics of artificial intelligence applications, it contributes to understanding how emerging technologies are reshaping economic and, consequently, social structures.

This analysis addresses the methodological challenges in the study of emerging technologies and provides a basis for future research on the implications of AI applications in society, so as to develop an environment in which to analyse the uses and impacts of generative artificial intelligence.