As artificial intelligence (AI) and machine learning (ML) continue to revolutionize industries, tax preparers face new challenges in navigating the complex landscape of research and development (R&D) tax credits for their clients. The intersection of AI development and tax law presents unique challenges. AI and ML projects often blur the lines between traditional software development and research activities, making classification difficult for tax purposes. However, recent changes in tax legislation, particularly the Tax Cuts and Jobs Act (TCJA), have brought these activities more clearly into focus.
Under the TCJA, Section 174 now requires the amortization of research costs, including software development. This change has significant implications for AI and ML projects, which typically involve more modeling than traditional coding but still fall under the umbrella of research expenditures. Many AI R&D activities may also qualify for the research credit under Section 41.
When assessing AI and ML projects for tax purposes, tax preparers should look for technical activities aimed at resolving uncertainties. These efforts often qualify as research expenditures, regardless of whether they fit neatly into the category of software development or traditional research. It's important to note that the distinction between R&D and routine maintenance can be subtle in AI projects. Placing a product into production doesn't automatically disqualify it from R&D consideration. Tax preparers should use a facts and circumstances test to differentiate between ongoing development and routine updates.
Proper documentation is critical in substantiating AI R&D activities for tax purposes. Tax preparers should advise their clients to maintain detailed records of their research activities and associated costs. This documentation not only supports claims for tax credits but also provides a clear audit trail if needed. When it comes to cost allocation, consistency is key. Using similar methods for allocating costs between Sections 174 and 41 can streamline compliance and simplify potential audits. Tax preparers should also be mindful of the timing of expense recognition, particularly given the shift from immediate deduction to amortization under Section 174.
The regulatory landscape surrounding AI R&D tax treatment is still evolving. Tax preparers should stay informed about IRS and Treasury guidance on AI and ML in the context of R&D tax treatment. This may include watching for potential simplifying conventions or safe harbors that could benefit their clients.
As AI and ML continue to advance, their impact on tax law and R&D credits will only grow. Tax preparers will need to be taking a proactive approach towards understanding the potential tax implications to best serve clients.
Christine Gervais is a licensed CPA, using her skills to help businesses grow and achieve their fullest potential. Christine has a Master’s degree in accounting from Southern New Hampshire University in addition to holding her CPA license for over a decade. Notably, Christine is a nationally recognized speaker providing education to other CPAs on how to best serve clients as well as instruction on a wide variety of topics for business owners on how to maximize success. Christine prides herself on the value she can bring to clients with her extensive tax knowledge and provides strategic, forward-thinking financial strategies to help clients grow. When not behind her desk, you can find Christine spending quality time with her daughter and stepson or tending to the family’s excessively loved farm animals.
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