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Will Tax Accountants Become Obsolete or be Replaced by AI?

Will Tax Accountants Become Obsolete or be Replaced by AI Featured image

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Many of us have heard the buzz about artificial intelligence (AI) changing the way we work. It might seem like tax accountants are next in line to be replaced by AI. 

But the short answer is: generally, no, that won’t happen. Let’s go through the reasons and understand more about this debate.

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What can AI do in tax preparation?

Before diving deeper into AI’s role in the tax world, let’s address the elephant in the room – the bad news. 

For those of us with straightforward financial situations, such as earning a regular W-2 salary without complex deductions or additional income sources, AI has made remarkable advancements in recent years and will likely be capable of preparing taxes for us. In many cases, AI-driven software can now handle basic tax preparation swiftly and efficiently.

Just to give a few examples: 

  • AI can automatically scan and input data from W-2 forms, eliminating manual entry errors and speeding up the process.
  • AI-powered platforms can guide taxpayers through a series of tailored questions to ensure all relevant information is collected and to perform a well-informed calculation, such as deciding between standardized and itemized deductions.
  • AI can cross-check data for discrepancies or potential flags that might increase the risk of an audit, alerting the taxpayer and offering corrections.

Does this remind you of the typical tax preparation software? The truth is not everyone is familiar with the tool, and some still resort to tax preparers for filing basic tax returns. There is nothing wrong with that. The argument is the rise of AI will only make this process more user-friendly and accessible to the general public.

So, if you are a tax accountant specializing in preparing basic tax returns, your career may face challenges due to the advancements of AI.

What can’t AI do in tax preparation?


Tax is interpretative. Tax preparation isn’t just about inputting numbers; it involves understanding and interpreting complex situations. AI is known for its inability to comprehend nuanced language, such as those in the legal setting.

Tax is not always black and white. Just to name a few simple examples:

  • Schedule K-1 (Partner’s Share of Income, Deductions, Credits, etc.): For individuals involved in partnerships or S corporations, the distribution of income, losses, or deductions isn’t always straightforward. For instance, if there’s a special allocation agreement among partners, where one partner receives a larger share of profits up to a certain amount, it’s a nuanced situation. 
  • Foreign Earned Income Exclusion: U.S. citizens working abroad might qualify for the Foreign Earned Income Exclusion if they meet certain residency tests. But situations like extended visits back to the U.S. or working in multiple foreign countries can blur the lines of qualification.
  • Transfer Pricing: Multinational corporations that transact with their subsidiaries face the challenge of setting prices for these transactions. Tax authorities require these prices (transfer prices) to be at an arm’s length, resembling market rates. However, determining arm’s length prices, especially for unique goods or services, can be a matter of significant judgment.
  • Start-Up Costs: New businesses often have expenses before they start operating. While some of these can be deducted immediately, others need to be amortized over time. Deciding which costs are organizational (like setting up a legal structure) versus operational (like market research) can be a gray area, especially if activities overlap.
  • Research & Development (R&D) Tax Credits: Many countries offer tax credits for companies conducting R&D. However, determining what qualifies as R&D, especially in fields like software development, can be murky. For instance, does refining an existing product qualify, or must it be a brand-new invention?

Consider how frequently online tax answers conclude with the advice to “Consult a tax professional.” One-size-fits-all answers aren’t practical, as individual tax situations often require interpretation.

Adaptation to Changes

Think about how often we hear about new tax laws or changes in the news. Tax rules are always evolving, adjusting to our ever-changing world. 

While AI models, especially language-based ones, are pretty good at understanding and processing vast amounts of historical context, they rely on previously acquired data. When tax laws get a sudden update or makeover, AI can sometimes be a step behind. 

With their real-world insight, human tax accountants are often better at understanding newly introduced laws that lack historical precedent, spotting details and meanings that AI might overlook.

Just to name a few recently passed law changes:

  • Selling Items via Digital Platforms: If you’ve been selling items through digital platforms like Facebook Marketplace, Etsy, Poshmark, etc., there was a new tax rule introduced that may require taxpayers to file a tax form (1099-K).
  • ACA Marketplace Healthcare Coverage: A temporary rule change has been introduced that allows more people to utilize the Premium Tax Credit (PTC).
  • Clean Vehicle and Energy Credits: The Inflation Reduction Act of 2022 introduced multiple changes to the new clean vehicle credit for qualified motor vehicles. It also added credits for previously owned and commercial clean vehicles.

Ultimately, it’s a bit like a game of tag between AI and new tax laws. No matter how swift and smart AI gets, it’s always running a bit behind. While AI is helpful in many ways, human tax accountants often have an advantage with the constant changes in tax rules.

Personal Touch

Think about how many times you call a customer service number and go straight to the option to “speak to a representative.” I will assume that this preference is even stronger with tax-related questions.

There’s something comforting about sitting down with a real person when you’re dealing with numbers and laws that might affect your future. Especially in taxing situations, we lean into human experience. Why? Because we trust the real person. We trust the experience this tax accountant gained from dealing with the tax codes and tax authorities.

There are countless examples of how personal interaction is needed when dealing with tax. To name a few:

  • Facing Tax Audits: This example is self-explanatory. If you were attending a court hearing, you would likely choose a human attorney over an AI robot. The same principle applies here.
  • Business Deductions: Imagine a small business owner trying to determine which expenses from a business trip can be written off. While an AI tool can provide general guidelines, an experienced tax accountant might remember a similar case they handled years ago and give advice tailored to that business’s specific situation.
  • Estate and Inheritance Tax: Every family has its own story and special quirks. Think of it like this: a computer tool might give you a basic roadmap, but a human tax accountant is like that friend who knows all the shortcuts and hidden gems. They have assisted numerous families and are skilled at navigating unique situations to find optimal solutions.

AI is known for not being able to adjust to unseen or uncertain situations. Therefore, even with all the AI advancements, tax accountants remain super valuable. Their years of experience and understanding of tax situations really set them apart. 

Beyond the personal connection, there’s also the question of accountability. With a human tax accountant, someone is responsible for advice and decisions. If things don’t go as planned, there’s a tangible responsibility. In contrast, no matter how sophisticated, AI remains just a tool. And who wants to try holding a machine accountable when the stakes are high? In fact, there is currently no clear oversight over the accountability of AI tools.

Key Takeaways & Infographic

  • AI is likely to take over basic tax return preparation that doesn’t involve complex tax situations. Tax preparation software is already heading in that direction.
  • However, AI can’t replace tax accountants or make them obsolete:
    • Interpretation: Tax laws have nuances and are not always clear-cut. Situations like special allocations in partnerships, determining eligibility for Foreign Earned Income Exclusion, or defining what counts as R&D can be complex. AI struggles with these gray areas.
    • Adapting to Changes: Tax laws frequently change. AI, although good at processing historical data, can lag behind when laws are suddenly updated. Human accountants often excel at understanding these new, unprecedented changes.
    • Personal Touch: People trust human tax accountants because of their real-life experience. They help in tricky situations like tax audits, give advice based on past cases they’ve seen, and understand unique family tax challenges. Plus, if anything goes wrong, there’s a real person who’s responsible, which isn’t the case with AI tools.
Will tax accountants become obsolete or be replaced by AI? infographic

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