Taxpayers cannot risk automation without clear rules of the road
For certified public accountants, AI is a powerful tool with great potential to enhance efficiency; however, its implementation requires a thoughtful approach. For taxpayers, AI presents many compelling use cases but raises unsettling questions about accuracy and privacy. Ultimately, overreliance on AI, particularly in areas requiring professional expertise and judgment, poses risks for both CPAs and the taxpayer. This emerging technology in the accounting field requires careful use, but there are still no clear rules of the road for CPAs.
The substantial lack of guidelines has led to a surge of new companies emerging seemingly overnight in the tax space, driven by AI programs. These firms market their services as a fast and easy alternative for tax filing.
AI-powered tax solutions offer convenience, but their use in corporate tax settings warrants caution. Often, businesses have complex tax filings, nuanced interpretations for certain credits and jurisdiction-specific requirements that go beyond what current AI tools can reliably handle. Accounting firms cannot rely on AI alone, rather AI is a supplemental tool and not a replacement for the real human judgment of CPAs.
These startups are operating without the standards that professional CPAs must uphold. Pair this lack of industry consensus on accuracy and privacy with the lack of federal oversight, it's easy to anticipate a 'Wild West' scenario. These companies, and their unbeknownst clients, are letting AI software conduct important finance calculations and tax filings without asking the hard questions. How are these AI tools trained? What happens if they're wrong? How can we protect the taxpayer from scams?
Because of serious consequences for taxpayers and tax professionals, Americans must have a framework for AI use in tax services. Taxpayers deserve transparency about the tools being used to calculate their finances and tax returns. We need to ensure accounting expertise is not undercut by unregulated, shady algorithms.
The tax system is too important to be left to chance. Take the research and development tax credit for example. This credit can offer significant financial benefits to a wide range of businesses, including those in manufacturing, biotech and software development. While an array of companies can qualify, it requires a nuanced understanding of IRS rules, including detailed documentation and in-depth interviews with employees to determine which activities qualify.
Accountants run into roadblocks when the records are not detailed, and interviews help solidify a filing, regardless of the level of documentation. Determining eligibility for the R&D tax credit is not simple. It is not a fill-in-the-blank form that an automated system can do easily. It requires professional judgment and industry expertise, which includes human interaction. If companies only use AI systems and forgo interviews, they put their clients at risk of costly audits and breaking the law.
Another danger is the payment schemes of these companies, which take a percentage of the credits that their clients receive. While this appears to be a sensible method, it deserves a closer look. AI can be trained to err on the side of qualifying for a tax credit even if the R&D activity doesn't truly qualify. This puts clients at risk of audits, fines and being found responsible for breaking the law if the company's activities do not actually qualify for a credit per tax code.
Tax fraud is a criminal offense, and often, a company's leadership, such as the CEO or CFO, can be held liable. We need to protect American businesses from these serious consequences and ensure AI use is smart and not excessively relied upon when making important decisions.
As AI becomes more integrated into financial services, there must be no confusion between automation and accountability. AI can be a powerful tool, but it is not a substitute for professional judgment, ethical responsibility or compliance with the law. Businesses that place blind trust in AI systems to handle complex tax matters risk more than filing errors. AI must be used to support, not replace, skilled human oversight.
When it comes to taxes, the stakes are too high to let an algorithm make the final call.
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