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Artificial Intelligence R&D is Booming — Ensure Your Organization is Claiming R&D Tax Credits


Jonathan Cardella

Strike Summary

  • There are certain restrictions when taking advantage of both Sections 174 deduction/capitalization and Section 41, which can be seen in Section 280C.
  • Businesses that choose to elect Section 280C for their federal taxes could also lower their state taxes as well.
  • Taxpayers that want to use Section 280C must plan ahead because it can only be used on an originally filed return.
  • The recent passage of the Tax Cuts and Jobs Act may have have affected whether a taxpayer should use Section 280C in their tax strategy.

Work with Strike to navigate tax changes with ease.

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According to the 2019 Artificial Intelligence (AI) Index Report, research into AI is experiencing all-around growth and is poised for logarithmic growth in the coming years. With AI and machine learning (ML) increasingly becoming part of every company’s future-proofing strategy, companies are investing heavily into their development and implementation. These investments meet the definition of Qualified Research Activities (QRAs) and can be claimed under the R&D tax credit.

To understand how AI ties into R&D tax credits, let’s take a closer look at what aspects of AI are considered QRAs and why they are so prevalent in the tech industry today. 

How Well Does AI Fit Under QRAs?

Artificial Intelligence development is the essence of QRA, and like most software innovation, almost always meets the Four-Part Innovation Test requirements:

1. Permitted Purpose

Businesses involved in developing a product or process for AI software can claim R&D credits for the development expenses. For example, a company creating an AI customer support software to improve the end-user experience can claim the development as a QRA.

2. Technological Uncertainty

Any work done to resolve technological uncertainty will likely be classified as a QRA. AI research readily qualifies for the R&D credit as developers and engineers encounter technological uncertainty regarding the optimal design or development methodology due to AI’s relative infancy in the marketplace.

3. Process of Experimentation

Software developers in AI R&D are constantly creating new code or refining existing code. This requires planning, reviews of various coding methodologies, trial and error, and testing to evaluate whether the design meets the functional/performance intent. As they explore the boundaries of natural language processing and deep learning, developers naturally engage in the process of experimentation.

4. Technological in Nature

The steps taken to achieve the desired software, product, or process must fundamentally rely on principles of the physical or biological sciences, engineering, or computer science. Computer science is the root of AI development and passes the process of experimentation test needed to qualify the development expenses.

Why AI?

It’s no wonder that AI is becoming increasingly integral to today’s top-performing companies. To put it simply, AI is the key to streamlined workflows, innovation, and increased bottom lines. Investments in AI technology can make a significant impact on your business, and the costs of that investment could be offset through the R&D tax credit. If your company is problem-solving with AI technology, you should get credit for the work that you're doing. Learn more about our team and how we can help here.

Work with Strike to navigate tax changes with ease.

Schedule a MeetingBook a Consultation

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