The Integration of Artificial Intelligence against Tax Evasion and Smuggling
In an era where public revenues are under increasing pressure and tax evasion is constantly evolving, leveraging artificial intelligence (AI) by tax and audit authorities has become a strategic necessity. Greece has already begun moving in this direction, strengthening the digital transformation of its tax mechanisms and fiscal governance.
Artificial Intelligence as an Ally in the Fight Against Tax Evasion
As noted by the Governor of the Independent Authority for Public Revenue (AADE), Mr. George Pitsilis, during the 6th International Conference of the Economic Chamber of Greece, artificial intelligence can serve as a “front-line” tool for detecting undeclared income, suspicious transactions, and tax inconsistency. The use of predictive models and risk analysis allows for the development of targeted audits while also facilitating a more efficient allocation of the limited resources of auditing services.
With the integration of AI, tax authorities will soon be able to detect patterns of unusual financial activity, identify discrepancies between declared and actual data, assess the risk of tax evasion per business or sector, and recommend automated actions, such as alerts or even preliminary inspections.
Using Benchmarking and Other Analysis Strategies to Track Market Trends and Competitor Performance
Beyond tax evasion, AI also holds great potential in combating smuggling, particularly in sectors like fuel, tobacco, and alcohol. By cross-referencing data from checkpoints, warehouses, customs systems, and IoT sensors, AI systems can detect suspicious routes, leaks, or violations. The prevention and deterrence of such phenomena is expected to significantly reduce revenue losses and simultaneously strengthen fair competition in the market.
The Need for Institutional Frameworks and Knowledge Infrastructure
As highlighted by Antonis Oikonomou, Commercial Director of Microsoft Greece, artificial intelligence should not make decisions independently, but rather function as a tool to support human judgment. Algorithms must be transparent, free from bias, and operate under clear accountability structures. At the same time, continuous training for public officials and system users is essential to ensure responsible use of AI tools and reduce vulnerability to emerging forms of digital fraud.
Ethical and Social Considerations
The expansion of AI in collection and auditing mechanisms also raises significant ethical and social questions. What data is being collected, and based on which criteria? How is citizens’ privacy protected? What safeguards exist to prevent abusive use?
These issues cannot be addressed solely at a technical or administrative level. First, a clear legal framework is needed to define the boundaries and permissible uses of AI in the tax domain. Additionally, broad public consultation—with active involvement from citizens and professional bodies—is necessary to shape policies that affect personal and professional data. Finally, ongoing evaluation of the social impacts of AI systems is vital to ensure transparency and the preservation of social equity.
Investment in Skills and Infrastructure
Greece, through initiatives like the PHAROS program and by utilizing European Union resources, is investing in the creation of AI infrastructure and the enhancement of digital skills. According to recent data, approximately 20% of employees in Greece already use AI in their daily work. Increasing these numbers is essential if the country is to keep pace with international developments.
To Conclude
The integration of artificial intelligence in the fight against tax evasion and smuggling is not merely a technological innovation—it is a critical step toward enhancing transparency, efficiency, and social justice. However, this path is neither easy nor one-dimensional. It requires collaboration between the public and private sectors, continuous education, ethical data use, and sustained institutional vigilance.
Technology may offer the answers, but political will and social sensitivity must ask the right questions.
