Amenaza al sistema fiscal: ¿Quién tributará cuando trabaje la IA?

The German Ministry of Finance has sounded the alarm over an aspect of artificial intelligence (AI) that is often overlooked in conventional technological debates: its direct impact on the sustainability of public accounts. Through an analysis of the transition to the AI economy, the German government warns that the automation of cognitive tasks could displace a significant portion of labor income towards capital income.

In a country like Spain, where personal income tax (IRPF) and social contributions form the backbone of the welfare state, this warning carries immediate strategic relevance.

Spain's fiscal model is built on the premise that work sustains the state. Tax revenues from IRPF and social contributions represent the majority of ordinary public income earmarked for financing healthcare, education, and the pension system. However, as AI evolves from a supportive role to one that substitutes for judgment, writing, analysis, or programming functions, the labor market could experience a contraction in its wage pool.

The Berlin report points out that unlike previous digitalization, AI not only reduces storage costs for information but also makes computational capacity a scalable service capable of handling tasks that previously required higher education.

Moreover, there is a geopolitical factor that complicates the scenario. The bulk of AI infrastructure and technological development is concentrated outside European borders. According to Germany's data analysis, around 74.5% of the computational capacity of major AI clusters is located in the United States, compared to only 4.8% in the European Union.

If Spanish companies massively adopt foreign-developed AI services to maintain their competitiveness, a substantial share of efficiency gains could transfer abroad in the form of licensing, subscriptions, and usage fees. This would leave Spanish tax authorities with a much narrower revenue margin.

The transition is also expected to be neither simple nor linear. Economists warn of a J-shaped productivity curve. Initially, organizational investments, process restructuring, and personnel training necessary to integrate AI may temporarily reduce recorded productivity before the real benefits become apparent. Spain, which already suffers from structural productivity problems, could be exposed to this temporary setback at a time of high public expenditure pressure due to demographic aging.

Facing this landscape, the German recommendation is pragmatism and anticipation. The German government's report advocates for a fiscal monitoring system of AI to assess whether the economy is moving towards a model where technology complements workers or replaces them. For Spain's situation, this approach suggests opening a rigorous debate on diversifying public income sources.

If economic value progressively shifts from human effort to algorithms, the almost exclusive dependence on labor taxes becomes risky. German experts point to the need to explore reforms that tax data flows, computational capacity, and the extraordinary benefits of global technological platforms. It also poses the convenience of designing mechanisms that allow citizens to share in the returns of technological capital, preventing the wealth generated by automation from concentrating in a small group of corporations.

Technology does not negate economic laws, but it does alter where wealth is generated. Spain's challenge is to adapt its tax structure before traditional bases of taxation face irreversible transformation.