Who Performed the Function?

A multinational files a patent for a new compound. Tax authorities in two countries want to know which entity in the group is entitled to the royalty stream the patent will eventually generate. The test they apply is old and, until recently, reasonably reliable: find out who performed the Development, Enhancement, Maintenance, Protection and Exploitation functions for the intangible - DEMPE, in transfer pricing shorthand - because whoever bears the risk and does the deciding gets the residual profit. For decades this worked because you could point to a building: a lab, a notebook, a committee that signed off on which candidate molecule to pursue. Increasingly, the person you would point to typed a prompt, set an agent running overnight, and reviewed a shortlist of candidates over coffee the next morning. The system generated the options, ran the simulations, in some cases proposed the formulation that went into the filing. Who, exactly, performed the function? 

This is not a hypothetical irritating a handful of transfer pricing specialists. An Australian tax advisory has recently flagged what it calls a DEMPE-shaped hole - cases where AI itself is doing the value-creating work and the existing test simply has no place to put that. A parallel problem is surfacing in patent law, where AI-generated inventions are quietly breaking the doctrine of inventorship the same way they are breaking the tax doctrine of significant people functions. Two different bodies of law, built for different purposes, are running into the identical wall: both assume that value is created by an identifiable human making an identifiable decision, and both are discovering that the human's contribution has thinned to something closer to selection and approval. 

 The instinct is to treat this as a compliance problem for corporate tax departments. It is that. It is also a preview of a question that is going to reach every individual who has taken the advice - now common, and not wrong - to stop being a mere user of AI and start being a builder with it. The advice is sound as far as it goes. But it assumes the world has a stable way of recognising, after the fact, that a given piece of work was built rather than merely retrieved. Increasingly, it does not. If the design decision, the judgment call, the actual creative leap happened inside the model, and the human's visible contribution is a prompt and a sign-off, then whatever institution eventually has to decide who gets the credit - a patent office, a performance review, a promotion committee, a funding panel, or a tax auditor deciding which entity in a group actually earned a royalty - is going to ask the same question the DEMPE test is asking of multinationals right now. Where, precisely, did you sit in this? 

It gets sharper still. Some of the institutions asking that question are, at the same moment, handing the question itself to AI. A peer-reviewed study on agentic transfer pricing work found it running nearly a hundred times faster than a human analyst, and wrong in roughly one case out of five or six. That is the position builders are actually in: producing work at a pace where the artifact looks finished, inside a system that is simultaneously trying to verify whether the artifact - or the reasoning behind it - was genuinely someone's, at a speed that does not allow careful verification either. Credit and reliability are being tested at the same moment, by the same overstretched apparatus, and neither test is mature. 

None of this means the advice to build rather than merely search was wrong. It means the second half of that advice has arrived earlier than expected: it is not enough to have used AI to produce something. What will be asked, by whoever is deciding whether the work was yours, is narrower and harder - what did you decide that the model could not have decided on its own; what judgment did you make that the output alone does not show; what risk did you actually carry if the decision turned out to be wrong. That residue is what DEMPE is trying, clumsily, to locate inside multinational R&D right now, and it is what will eventually be asked of anyone whose work passed through an agent before it reached a reader, a patent examiner, or a manager. 

The practical instruction for builders is not to use AI less. It is to keep a different kind of record than most people currently bother with - not a log of what the model produced, but a trace of the decision points where a different judgment would have produced a different outcome, and where that judgment was demonstrably yours. Tax authorities are already learning, case by case, that the old test - find the person who performed the function - cannot be answered by pointing at a finished patent or a tidy set of transfer pricing documentation. It has to be answered by reconstructing a decision trail. Builders who have not been keeping one are going to discover, the way multinationals currently are, that the absence of a trail is itself the answer to the question of who performed the function - and it is rarely the answer they wanted.