AI to modernize tax administration: the story behind Armenia’s success

Tax audit planning in Armenia has traditionally been conducted manually with some elements of automation, similar to many tax administrations worldwide. So, the leadership of the State Revenue Committee (SRC) began exploring the application of artificial intelligence (AI) to leverage the significant opportunities provided by AI, utilizing the extensive historical data available at the SRC.  

Armenia is now piloting the use of AI to improve tax compliance, risk management, and fraud detection. Supported by the World Bank, SRC has collaborated with the American University of Armenia (AUA) to develop expertise and build capacity in utilizing an AI-powered tax administration tool.

Armenia’s early adoption offers valuable insights for other governments considering the use of AI in public services. We share below six tips on how to succeed:

1. Identify effective leaders to affect change. In Armenia, reform was spearheaded by the SRC Chair, who prioritized solving business problems over following technology trends. This high-level commitment and problem-centric approach were critical in implementing significant changes.

2. Partner with academia and the private sector to overcome limited technical capacity. SRC utilized AUA’s data science expertise, providing hands-on experience for researchers and students while expanding government capability. The World Bank’s Public Sector Modernization Project which is in its fourth phase is anchored on the Government’s newly adopted Digitalization Strategy which emphasizes that the development of advanced technologies plays a decisive role in the competitiveness, security, and living standards of the state. It invested in creating the knowledge by connecting academia’s R&D with the public sector.

3. Collaborate to overcome AI talent shortages. AI expertise — including data scientists, architects, and developers — is limited and costly. Armenia addressed hiring bottlenecks by collaborating with the World Bank to design competitive procurement processes. Partnering with AUA provided benefits for both parties: students gained practical experience through projects, and the government got the necessary skills.

4. Prioritize solving problems over flashy tech. Armenia’s first use case is to improve tax compliance using AI to read invoices, detect fraud rings, and flag anomalies like duplicate filings and identity mismatches. According to conservative estimates, it is reasonable to expect 10-15% increase in voluntary and enforced tax compliance through the use of AI. In addition to improving the backend operations, AI has also the potential to improve service delivery - chatbots answer tax queries, AI can speed up tax refunds and prefill tax filings, benefiting the public directly.

5. Manage risks early. AI is not without risks — including bias, data privacy, security, job displacement. Armenia addresses these concerns by focusing on four pillars: explainability (using clear, non-technical logic), transparency (open-source data), robust cybersecurity (aligned with ISO standards), and stakeholder engagement (involving tax firms, media, and civil society in oversight). In the future. Algorithm Impact Assessment (AIA) could be carried out to mitigate the risks. AIA is a self-assessment carried out to determine the impact of the algorithm on the citizens to ensure privacy, ethics, and human rights – for example, right to fair and equal treatment that could be compromised due to bias.

6. Focus on results. AI technology is prevalent, but not always necessary. Armenia has emphasized measurable, problem-driven goals rather than adopting technology for its own sake. Success is evaluated based on tangible outcomes. Countries like India and Brazil have reported 10–30% higher tax collection through the use of AI.

To conclude, Armenia’s experience demonstrates that small nations have a unique advantage in driving change and becoming early adopters of innovations. With effective leadership, strategic partnerships, and a clear focus on outcomes, the integration of AI in tax administration is not a merely a future aspiration—it’s currently being implemented.