GUEST COLUMN.
HOW CAN AI MODERNIZE TAX ADMINISTRATION?
By Dan Chenok, Executive Director, IBM Center for the Business of Government
Interest in artificial intelligence (AI) has surged across all levels of government. There appears to be a natural fit between this new technology and revenue agencies – and they’re following through on the opportunity. In fact, over 80% of tax agencies around the world are implementing leading-edge techniques, notably AI, to leverage data to create more efficiency and improve the taxpayer experience, according to the Organization for Economic Cooperation and Development.
To better understand opportunities and considerations, the IBM Center for The Business of Government, in collaboration with the American University - Kogod School of Business Tax Policy Center, recently hosted two discussions focused on AI and the Modern Tax Agency. A new report emanated from those sessions, which explains that as a result of “common access to AI and the potential benefits of generative AI, the U.S Internal Revenue Service (IRS) and tax agencies around the world are now focusing on how the technology could improve tax administration while minimizing some of the risks.”
In addition, the IBM Center published a series of blog posts related to this topic including: Pathways to Trusted Progress With Artificial Intelligence, Artificial Intelligence in the Public Sector: A Maturity Model, and More Than Meets AI (published with the Partnership for Public Service).
Based on the Center’s findings, AI can help tax agencies make progress in three areas:
Better enabling taxpayers, including small businesses, to navigate tax filings through an improved user experience
Streamlining operations to improve tax administration
Enhancing governance and development of transparent and ethical AI
Streamlined Tax Agency Operations
AI can be used in multiple ways to improve tax agency performance. It can optimize audit activities, increase tax compliance rates, and improve processing and reporting to drive better tax administration outcomes. Specific results that can help tax agencies include the following:
Improve customer/taxpayer experience and satisfaction, offering personalized support and assistance through various channels, such as phone, email, and live chat, and by implementing user-friendly features like auto-population of tax return information, electronic signature options, and instant confirmation of receipt.
Process refunds faster, by implementing a streamlined refund process that reduces processing time and issues refunds promptly, and by providing taxpayers with real-time updates on the status of their refunds through online portals or mobile apps.
Provide increased personalization, by using data analytics and machine learning algorithms to identify patterns and trends in taxpayer behavior and tailor communications and services accordingly, and by offering personalized tax planning resources and recommendations based on taxpayers' individual circumstances and goals.
Increase audit speed and efficiency, by:
Implementing data-driven audit selection and risk assessment processes to identify high-risk returns and allocate resources more effectively.
Using machine learning and natural language processing to automate the review of tax returns and identify potential issues before they are identified by human auditors.
Providing taxpayers with real-time updates on the status of their audits and offering digital tools for submitting documentation and responding to audit inquiries.
Tax agency leaders can achieve these results in a variety of ways, include training tax agency officials on the appropriate use of AI to best understand the benefits and constraints; using demonstrations to enable users to visualize the advantages of using AI; developing models for future auditing via a more efficient use of resources; leveraging AI to provide personalized taxpayer and workforce experiences; and using AI to provide faster refunds and streamlined communication between the government and taxpayer:
Risk and Governance
While appreciating the opportunities, tax agencies understand that using newer, Generative AI capabilities creates some risks, which must be mitigated. Tax agencies, for example, are keenly aware of the potential for bias and unexplainable analytics. Moreover, assuring taxpayers that their data is secure is key to establishing the necessary trust agencies need for successful AI deployment.
Key success factors that AI programs and governance programs should consider on an ongoing basis to protect taxpayers and ensure efficiency include ensuring safe and trustworthy AI training, alignment with useful outcomes, and acknowledging and complying with law and policy.
Effective AI governance includes embracing transparency, ensuring fairness and privacy, and fostering accountability—an approach that demands ongoing attention to ethics and governance. Human-centered AI development is critical to controlling AI risks. As governments increasingly use AI and other new technologies, they must focus on ethical governance, human-centered design, and collaborative innovation.
Innovation and Governance
Within a governance framework, fostering a culture of innovation is critical. At the same time, tax agencies must also work to develop appropriate guardrails.
Governance programs, which may often be federated, can be used as a forum to share best practices and lessons learned across the agency. Well-executed governance programs provide opportunities to share workable, high-value opportunities across the organization. Concepts include creating a Center of Excellence to support business units with both technology insights and leading ideas on transparency, ethical use, and governance processes.
Supporting innovation while driving ethical, unbiased, and transparent AI is of paramount importance. Beyond the tax roundtables, the IBM Center for the Business of Government and the Partnership for Public Service hosted an event on Ethical and Effective AI. That discussion laid out approaches to maintain a culture of innovation while delivering ethical AI. Approaches include a heavy focus on AI Literacy, collaborating to develop agency-specific AI strategies, and using hack-a-thons to exchange information. Phaedra Boinodiris, IBM’s Global Leader for Trustworthy AI discussed this in a blog.
I will be discussing some of these issues in more detail in a session at the upcoming annual meeting of the Federation of Tax Administrators, which is the association of tax leaders from across all 50 States and several large cities, on June 11 (see full agenda here).
The contents of this Guest Column ’reflects the sentiments of the author and not necessarily Barrett and Greene, Inc.
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