Benchmarking—the process of screening, selecting, and analyzing comparable companies—is time consuming. Analysts can spend innumerable hours every year preparing transfer pricing documentation, with a substantial portion of that time dedicated to benchmarking. Even with improvements in the quality of databases (which offer a vast array of quantitative and qualitative data), the sets of potential comparables that analysts must sift through are often enormous.

With the applications of artificial intelligence (or “AI”) expanding by the day, it is time to start thinking about whether AI could automate parts of the benchmarking process.


Continue Reading Artificial Intelligence for Benchmarking: The Wave of the Future

Consider the following hypothetical: Researchers at a US-parented drug company develop an artificial intelligence (or “AI”) system that can identify new therapeutic targets with minimal human intervention. The drug company sells the system to its foreign affiliate in a lower-tax jurisdiction. What is the appropriate valuation of the system on this outbound transfer (e.g., based on the cost to create it or based on the value of the IP it is likely to generate)? And, when the AI system later successfully creates a new therapeutic, which entity will be entitled to the non-routine returns from sales of the therapeutic: the US parent that developed the system, the foreign subsidiary that owns the system that developed the therapeutic, or some combination of both?

Continue Reading Transfer Pricing for AI-Generated Intellectual Property