
Image: Used with permission (Maryna Hryhorieva)
This striking graphic, created by IP lawyer Maryna Hryhorieva, is a great summation of the current state of play regarding the still very fluid issue of AI training and copyright. It compares how eight different regimes, the US, EU, Japan, South Korea, China, the UK, Canada and Australia, are addressing this thorny issue, and highlights the different frameworks used to determine what is legal and what’s not. Each is different with its own peculiarities. Navigating through them is not easy. What may apply in one jurisdiction will not apply in another. A use that is acceptable in Country A may result in an unfavourable court ruling in Country B. An AI company can decide to base its content use practices on the most AI-friendly regime in which it operates, staying onside in that jurisdiction, but then can still be found to be infringing elsewhere. Cross-border jeopardy is almost certain where an AI company wants to scoop up local cultural content, pitting it against determined rightsholders who will, among other things, invoke cultural sovereignty.
The essence of the issue goes back to the way in which international copyright law is structured. Each country sets its own rules, regulations and interpretations within a broad commonly agreed framework. That framework, based on the Berne Convention, results in common basic standards centred on some fundamental principles, incarnated in the famous “three step test”.[i] The result is a generally consistent pattern of protection for rightsholders but with some significant differences by jurisdiction, like duration of copyright protection for example. The same inconsistencies apply to data mining (or what I would call unauthorized content reproduction) for AI training. So, what is a poor little ol’ trillion-dollar AI developer to do? Guess what? There is a universally applicable solution. Can you guess what it is? I reveal all in the final paragraph.
First, let’s briefly summarize the chart.
The US approach is based squarely on litigation, letting the courts decide the parameters of fair use regarding the unauthorized taking of protected content for AI training. This case-by-case approach will provide case-by-case answers, depending on the circumstances, the judge in question and even the circuit within the US federal justice system in which the case is heard. A legal approach inevitably leads to risk and uncertainty. That is not to say that in the end, the US will not resort to legislation. Thee US Justice Department recently submitted a “Statement of Interest” in the OpenAI v New York Times case, stating that a ruling in favour of the Times and other news industry plaintiffs would “threaten US national security, give a competitive advantage to foreign adversaries”, and thwart “creative and scientific progress while hindering American prosperity”. The Statement of Interest tries to put its thumb on the scale of justice, weighing in in support of the OpenAI argument that its use of NYT content was “transformational”, and thus constituted fair use. The Court is under no obligation to accept this interpretation; its duty is to interpret the law as it stands. But if the DOJ statement represents the Trump Administration’s interpretation of the law, and that interpretation is not upheld by the courts, that potentially opens to door to legislative change, assuming that Congress can be convinced to act in the name of big tech. Either way, there is continued uncertainty.
The EU approach is based on a narrow text and data mining exception embedded in the Copyright Directive. Resort to the exception is limited in two ways; if rightsholders cannot opt-out, the exception is limited to scientific organizations and cultural heritage institutions for research purposes only. There is also a general exception that allows for commercial use but in this case, rightsholders can reserve their rights by opting out.
Japan is considered by many to have a very AI-friendly regime in terms of allowing copying for training purposes, but it is not as wide as many have claimed, as I pointed out in this blog posting a couple of years ago. South Korea is struggling with the issue, being whipsawed between AI developers promising the moon and its vibrant cultural industry. China likewise is still trying to determine which way to go. It does not have a text and data mining (TDM) in its law, nor does it apply a fair use doctrine. However, it has announced plans to deal with AI training rules through its copyright development plan covering the period 2026-30.
The UK has had several false starts. A TDM exception limited to non-commercial purposes only has been on the books for several years, but the Labour government tried to expand this by advocating for a regime that would allow AI developers to freely use copyrighted content for algorithm training unless rightsholders opted out. After a massive outcry and pressure from British cultural industries and prominent performers, the government retreated. Now Britain has gone back to the drawing board.
In the case of Canada, everything is up in the air. Canada has a fair dealing regime with no TDM exception. It has held several public consultations and is developing an AI strategy but has been very unclear about where the government comes down on the issue of freely using copyrighted material for AI training. Meanwhile several Canadian media outlets are suing OpenAI for copyright infringement. OpenAI lost its argument that Canadian courts had no jurisdiction in this case. Now the Canadian music collective SOCAN is suing AI music company Suno. While AI companies are arguing for a wide TDM exception in Canadian law, rightsholders are seeking to retain the current law and use it to protect their rights.
Australia on the other hand has spoken out strongly in defence of its cultural sector and has declared that it will not legislate a TDM exception. Australian Prime Minister Albanese has taken that a step further declaring that, “An artist’s creative endeavour is their work and their property. No company should use Australian books, music, art or news to build or train AI without the artist’s control. That includes the artist’s control of the price and value of their work.” What will happen next in Australia is unclear although some tech platforms continue to try to push various compulsory licensing regimes.
As you can see, the rules are diffuse and in flux. Frankly, it is all over the map. One thing seems to be clear. The push by the tech industry for widespread TDM exceptions seems to be stalling. The litigation route so favoured in the US is yielding uncertain results. Legal actions in fair dealing countries like Canada, the UK and Australia may bring varying results with complex rules governing applicability of judgements. All this leads to greater uncertainty, and costs. However, as mentioned above, there is one universal remedy, one that transcends all the jurisdictional issues and conflicting interpretations. It is called voluntary licensing.
Voluntary licensing between rightsholders and AI developers eliminates the jurisdictional problems, assuming the agreements are structured to provide wide coverage and indemnity. With a voluntary licence, it doesn’t matter if there is or isn’t a text and data mining exception, or if the use is for commercial purposes, or if the use is sufficiently transformational. It doesn’t matter whether the AI developer is truly “enjoying” (accessing the essence of the content), as in the case of Japan. Some jurisdictions have toyed with the idea of a compulsory licence, as in India, but not only has this been opposed by both rightsholders and the AI industry, it is jurisdictionally bound. Voluntary licences deal with this issue and, if properly structured, remove the hazard of conflicting jurisdictional rulings.
While it is not always easy to reach such deals, as the OpenAI v New York Times case illustrates, it is surely better and less costly than the alternative of endless litigation. This is why it is becoming the preferred solution. More and more licensing agreements are being negotiated across the full range of copyrighted content, including audio-visual, music and publishing industries for AI training and use. Voluntary licensing is a global solution–but it requires AI companies to recognize the value of the content they want for training, and to accept the right of creators to control the use of their content. If it requires a willing buyer, it also requires a willing seller and while not all rightsholders will be willing to sign a licensing agreement, the holdouts will be the exceptions if fair deals are offered. It is a far better solution for both sides, AI developers and rightsholders, than endless litigation or constant lobbying for (or pushing back against) legislative change. It’s a global solution to a global problem.
© Hugh Stephens, 2026. All Rights Reserved.
[i] Any exception must satisfy three requirements: (1) Limited to certain special cases:. i.e. the exception must be narrowly defined and clearly circumscribed, rather than acting as a broad or general exemption; (2) No conflict with normal exploitation: i.e.the use must not interfere with the ways the copyright owner routinely makes money or manages the market for their work; (3) No unreasonable prejudice to legitimate interests of rightsholders, i.e. the use must not cause unfair or excessive economic or legal harm to the author or right-holder









