The use of AI in Tax Administration and Compliance

The Zimbabwe Revenue Authority (ZIMRA) introduced the Tax and Revenue Management System (TaRMS) as part of their strategy to transform the administration of taxes by using a system which simplifies registration, enhances online services and automates compliance checks. The efforts to enhance tax administration and compliance can also be enhanced through the use of Artificial Intelligence (AI) and Information and Communication technology (ICT).  The potential of AI to transform tax administration and systems demands scrutiny, evaluating not only the advantages but also the potential impact on taxpayer rights and the intricate web of interactions between tax authorities and citizens. This article explores the intersection of AI, ICT and tax administration to achieve a system which is efficient for taxpayers.

The introduction of AI in tax administration can use algorithms to check data submitted by taxpayers and also to use the data to restructure service provision. Tax administrations globally find themselves in an advantageous position due to their access to copious data of exceptional quality. Leveraging AI becomes imperative, not merely to combat tax fraud but to enhance taxpayer service and compliance. The European Commission highlights the pivotal role of data volume in AI’s efficacy. In this regard, tax administrations access to extensive data places them at the forefront of AI integration. The data they collect can help revenue authorities respond to taxpayer queries and enhance compliance checks ensuring a faster and easier process for taxpayers.

Reports from the OECD indicate a significant number of tax administrations actively employing or planning to adopt AI, indicating a global momentum towards AI integration in tax operations. The implementation of AI in tax systems extends to various domains. Other countries have deployed virtual assistants or chatbots to aid taxpayers in understanding their obligations and resolving queries dynamically. Spain’s collaboration with IBM Watson in creating an AI-based virtual assistant for VAT information is an example. According to the tax agency, this resulted in an eighty percent reduction in email enquiries to the revenue authority and a tenfold increase in queries within the initial week.

AI has also been deployed to detect irregularities, as seen in Spain where the Tax Agency alerted small businesses whose declared revenues deviated below sector averages based on AI derived insights. Other countries, including the United States and Canada, utilize big data and AI to assess tax risks, segmenting taxpayers by compliance probabilities and initiating controls accordingly.

The envisaged scope of AI integration extends comprehensively across tax procedures and administrative functions. Automation of administrative functions and management processes, exemplified by Spain’s General Directorate of Cadastre’s neural network-based real estate valuation, indicates the potential for AI in enhancing procedural efficiency such as advance tax rulings in the Zimbabwean context.

Looking ahead, AI might simplify collection processes by predicting bad debts, enabling prioritized enforced collections, as witnessed in Finland, Ireland, Singapore, and Sweden. The evolution may even encompass automated resolution of tax procedures without human intervention, though this remains a distant reality. The touted benefits of AI in taxation encompass improved compliance, streamlined processes, reduced errors, and enhanced service for taxpayers. However, this optimistic narrative intertwines with potential risks, necessitating ethical assessments and the adherence to principled guidelines.

Principles of prudence, non-discrimination, proportionality, transparency, and data governance should underpin the implementation of AI in tax administration. Prudence advocates for cautious progression and piloting programs before widespread adoption. Non-discrimination warns against the transfer of human biases or errors into algorithmic systems, highlighting the imperative to prevent algorithmic bias. Proportionality emphasizes the evaluation of interference in taxpayer rights, advocating caution in administrative actions based on AI-derived conclusions. Transparency calls for measures enabling taxpayers to understand decisions made through AI without compromising their right to a fair tax system. Data governance becomes pivotal, ensuring data security, privacy, quality, and integration in line with our data protection and privacy laws.

Ultimately, well-designed AI algorithms fed with taxpayer data should lead to a more effective tax system, streamlined administrative processes, enhanced legal certainty, reduced resolution times, and diminished conflict. The societal benefit of curbing tax fraud is evident. However, this technological journey must remain grounded in serving taxpayers and adhere to principled guidelines for ethical and equitable outcomes. Zimbabwe, amidst its socio-economic tapestry, stands at a crossroads where embracing AI in tax administration could redefine its fiscal landscape. In the next half a decade, with the TaRMS system and data available, Zimbabwe could see a big shift in tax and ai. This is in line with the world striving towards an AI-inclusive future, the principles guiding this transformation will determine whether it fortifies or falters the relationship between taxpayers and tax authorities.

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