IA en los sistemas de recaudación gubernamental: Una oportunidad estratégica para la eficiencia fiscal y el crecimiento económico

Generado por agente de IAEvan HultmanRevisado porAInvest News Editorial Team
lunes, 15 de diciembre de 2025, 9:36 pm ET2 min de lectura

The integration of artificial intelligence (AI) into government revenue systems is no longer a speculative exercise but a transformative force reshaping fiscal governance. From the United States to Singapore, tax authorities are leveraging AI to enhance compliance, optimize enforcement, and unlock new revenue streams. For investors, this shift represents a high-impact opportunity: public-sector AI adoption is not merely a cost-saving measure but a catalyst for broader economic growth, driven by improved fiscal efficiency and systemic innovation.

Fiscal Efficiency: The Case for AI-Driven Tax Administration

AI's ability to process vast datasets and identify non-linear patterns has revolutionized tax administration. The U.S. Internal Revenue Service (IRS), for instance, has deployed ensemble methods and network analysis to target high-complexity cases-such as large partnerships and sophisticated business structures-where traditional methods falter. This approach

within early implementation phases, demonstrating AI's capacity to uncover hidden compliance risks. Similarly, the UK's HM Revenue and Customs (HMRC) has leveraged its decade-long Connect program to integrate data from hundreds of sources, including banking and property transactions, into comprehensive taxpayer profiles. By combining graph database technologies with robust governance frameworks, HMRC .

Singapore's Inland Revenue Authority of Singapore (IRAS) offers another compelling example.

By applying risk-based profiling systems that blend traditional compliance indicators with behavioral analytics and predictive modeling, IRAS has improved enforcement effectiveness while maintaining procedural fairness. These case studies underscore a universal truth: AI-driven tax systems thrive when supported by foundational data infrastructure and sustained investment in both technology and human expertise .

Quantifying the Impact: Revenue Gains and Operational Improvements

The fiscal benefits of AI are not abstract. In the past 12 months alone, AI-driven audit selection

, significantly boosting enforcement effectiveness without proportional increases in staffing. California's tax collections, for example, , partly attributed to AI-enhanced compliance monitoring in a tech-driven economy. On a global scale, the UK AI sector's revenue grew by 68% in 2024, reaching £23.9 billion, as diversified AI applications expanded into public-sector use cases .

These gains are not limited to direct revenue recovery. By reducing compliance costs and fraud, AI also fosters a more equitable tax environment. The OECD

the accuracy and efficiency of tax administration, indirectly supporting economic stability by ensuring fairer distribution of fiscal burdens.

Challenges and Mitigation: The Road Ahead

While the potential is vast, challenges remain. A critical risk lies in the emergence of AI-driven entities that exploit legal loopholes to avoid tax obligations. A 2025 study warns that such "agent tax evasion" could lead to a $2.7 billion revenue shortfall if unaddressed

. This underscores the need for adaptive governance frameworks that evolve alongside AI capabilities.

Investors must also consider the upfront costs of data integration and talent development. HMRC's Connect program, for instance,

to achieve its current scale. However, these costs are offset by long-term gains in operational efficiency and compliance, making AI a sound long-term bet.

Conclusion: A High-Return Investment in Public-Sector AI

The convergence of AI and government revenue systems is a strategic inflection point. For investors, this sector offers dual returns: tangible fiscal gains through improved compliance and indirect economic benefits via enhanced governance. As AI continues to redefine tax administration, early adopters-both in government and private capital-will reap disproportionate rewards. The question is no longer whether AI will transform public finance but how quickly investors can align with this inevitable shift.

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Evan Hultman

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