AI Training and Copyright Law in Switzerland Copyright © by Valery Frischknecht is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, except where otherwise noted.

© 2025 – CC-BY-SA (Text)

Author: Valery Frischknecht
Publisher: EIZ Publishing (eizpublishing.ch), Bellerivestrasse 49, 8008 Zürich, eizpublishing@europa-institut.ch
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DOI: https://doi.org/10.36862/6GRK-8DSQ
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1

Next Generation

The “Next Generation” series offers a platform for young academics in all areas of law. The aim is to promote the visibility of special talents at an early stage. The volumes in this series are published in Open Access and can therefore be shared and distributed via social media and other channels. Each contribution undergoes a peer review process before it is published.

AI Training and Copyright Law in Switzerland

Is AI training legally justified under copyright law, or will it be in the future?

Valery Frischknecht

Valery Frischknecht completed her Bachelor of Law at the University of Zurich in the summer of 2024. Toward the end of her Bachelor, she began gaining practical experience as a legal assistant at a law firm specializing in labor, tenancy, criminal, and insurance law. She is currently pursuing her Master of Law at the University of Zurich. Following her graduation, she will commence her legal traineeship at a law firm in the city of St. Gallen in the spring of 2026.

Valery Frischknecht explores the profound interconnection between AI training and copyright law, revealing how technological innovation challenges established legal frameworks. Focusing on Swiss copyright law and its ability to keep pace with the rapid development of generative AI. The study offers a comprehensive analysis of legal boundaries, European influences, and potential legislative reforms. It provides new perspectives on balancing innovation with the protection of intellectual property and outlines possible pathways toward a modern, equitable legal framework for Switzerland.

Table of Content

List of Statues

List of Materials

Bibliography

Introduction

AI Definition

AI Training

Supervised Learning

Self-Supervised Learning

Unsupervised Learning

Reinforcement Learning

Preliminary Conclusion

Copyright Law in Switzerland

Use for Private Purposes

Private Use

Use in Schools

Internal Business Use

Temporary Reproduction

Use of Works for the Purpose of Scientific Research

Extended Collective Licences

Guidelines on Artificial Intelligence

Preliminary Conclusion

Practical Challenges

The “Black Box”

Territorial Borders

Excursus on the Regulations in the European Union

The AI Act

The AI Convention

Ratification of the AI Convention

Outlook

The Gössi Motion

The Emerging Challenges for AI Providers

Possible Implementation of an AI Act in Switzerland

The Complete Exemption

The Content Flat Rate

Exemption with Opting-Out

The Hybrid Model

Conclusion

List of Statues

AI Act

Regulation (EU) 2024/1689 of the European Parliament and of the Council of 13 June 2024 laying down harmonised rules on artificial intelligence and amending Regulations (EC) No 300/2008, (EU) No 167/2013, (EU) No 168/2013, (EU) 2018/858, (EU) 2018/1139 and (EU) 2019/2144 and Directives 2014/90/EU, (EU) 2016/797 and (EU) 2020/1828 (Artificial Intelligence Act) (2024/1689).

AI Convention

Council of Europe Framework Convention on Artificial Intelligence and Human Rights, Democracy and the Rule of Law, Council of Europe Treaty Series 225 – Artificial Intelligence, 5.IX.2024.

URG/ CopA (Swiss copyright law)

Federal Act on Copyright and Related Rights (SR 231.1).

ZPO/ CPC (Civil Procedure Code)

Swiss Civil Procedure Code (SR 272).

List of Materials

Botschaft

Zur Änderung des Urheberrechtsgesetzes sowie zur Genehmigung zweier Abkommen der Weltorganisation für geistiges Eigentum und zu deren Umsetzung (2017) (quote: Botschaft).

Bundesamt für Kommunikation BAKOM

Auslegeordnung zur Regulierung künstlicher Intelligenz, Bericht an den Bundesrat (2025) (quote: BAKOM).

Bundesrat

Leitlinien “Künstliche Intelligenz” für den Bund Orientierungsrahmen für den Umgang mit künstlicher Intelligenz in der Bundesverwaltung (Bern 2020) (quote: Bundesrat).

Staatssekretariat für Bildung, Forschung und Innovation SBFI

Herausforderung der künstlichen Intelligenz, Bericht der interdepartementalen Arbeitsgruppe “Künstliche Intelligenz” an den Bundesrat (2019) (quote: SBFI).

Bibliography

Unless otherwise stated, the following works are cited with the author’s name and page number (if available).

B. Balzli, Bessere Rahmenbedingungen für KI: Bundesrat Albert Rösti sollte unbedingt noch einen Schritt weitergehen (Neue Zürcher Zeitung Article, 2025).

D. Barrelet/W. Egloff (Hrsg.), Das neue Urheberrecht, Kommentar zum Bundesgesetz über das Urheberrecht und verwandte Schutzrechte (4th edition, Bern 2020) (quote: Das neue Urheberrecht-Barrelet/Egloff, URG margin note).

A. Boos/N. M. Pompe, Die demokratische Legitimation der Anwendung Künstlicher Intelligenz in der Rechtsprechung (Zürich 2020).

P. Dany, Die Offenbarung von KI-Patenten (Zürich/Genf 2024).

T. W. Dornis/S. Stober, Urheberrecht und Training generativer KI-Modelle. Technologische und juristische Grundlagen (1st edition, Sachsen 2024).

L. Finger, Europa verliert im KI-Wettbewerb – mit dramatischen Konsequenzen (Neue Zürcher Zeitung Article, 2025).

A. Gierbl et al., Künstliche Intelligenz in der Prüfungspraxis (Expert Focus Article, 2020).

R. M. Hilty, Urheberrecht (2nd edition, Bern 2020).

R. Köchli, Die Wegleitung für den Umgang mit künstlicher Intelligenz SAV (Anwaltsrevue Article, 2024).

B. Kohn, Künstliche Intelligenz und Strafzumessung (1st edition, Sachsen 2021).

S. Krempl, Studie für Rechtsinhaber: KI-Training ist Urheberrechtsverletzung (heise online Article, 2024).

S. Marmy-Brändli/I. Oehri, Das Training künstlicher Intelligenz (sic! Article, 2023).

E. Mühlemann/N. Ritter, Teil 10: Urheberrecht und KI: Verantwortlichkeit von Anbietern und Nutzern (VISCHER Article, 2024).

C. Neuhaus/B. Skinner, Petra Gössi macht den Chatbot-Test: Klaut sich die KI ihre Inhalte aus Zeitungen zusammen? (Neue Zürcher Zeitung Article, 2024).

C. Neuhaus, Petra Gössi und der Bundesrat bieten Chat-GPT und Co. die Stirn (Neue Zürcher Zeitung Article, 2025).

J. Quang, Does Training AI Violate Copyright Law?, (Berkeley Technology Law Journal Article, 2021) (quote: J. Quang).

M. Rehbinder/L. Haas/K. Uhlig, Kommentar zum URG, Urheberrechtsgesetz mit weiteren Erlassen und internationalen Abkommen (4th edition, Zürich 2022) (quote: M. Rehbinder/L. Haas/K. Uhlig, URG margin note).

C. Semmelmann, Künstliche Intelligenz und Urheberrecht: Stand zu Training und Output 2024 (sic! Article, 2024).

F. Steiner, GEMA verklagt OpenAI: Auf Klau gebaute Songtexte? (heise online Article, 2024).

F. Thouvenin et al., Keine Netzsperren im Urheberrecht (sic! Article, 2017) (quote: F. Thouvenin).

F. Thouvenin et al., White Paper: Urheberrecht (Zürich/Basel 2025) (quote: F. Thouvenin, White Paper: Urheberrecht, page).

F. Thouvenin et al., White Paper: Transparenz (Zürich/Basel 2024) (quote: F. Thouvenin, White Paper: Transparenz, page).

F. Thouvenin/P. Picht, AI & IP: Empfehlungen für Rechtsetzung, Rechtsanwendung und Forschung zu den Herausforderungen an den Schnittstellen von Artifical Intelligence (AI) und Intellectual Property (IP) (sic! Article, 2023) (quote: F. Thouvenin/P. Picht).

L. Waltle, Ein “Hammer-Urteil”: Thomson Reuters siegt mit einer Urheberrechtsklage gegen eine KI-Firma (Neue Zürcher Zeitung Article, 2025).

M. Wullschleger, Die Durchsetzung des Urheberrechts im Internet (Bern 2015).

I. Introduction

Artificial intelligence (AI) has become an integral part of our daily lives, seamlessly embedded in technologies such as powering search engines, speech recognition, translation, facial recognition, media recommendations, and spam filters. We have become accustomed to these innovations and take them for granted. But AI is not static; it is constantly evolving, driven by advances in training methods. By mimicking the complex decision-making processes of the human brain, AI has opened up unprecedented possibilities. However, these advancements bring urgent legal and ethical concerns, especially concerning copyright issues in AI training. This paper explores the technical underpinnings of AI training, its intersection with copyright, and the complex challenges posed by the use of copyrighted works as training data. Firstly, the concept of AI, its definition and its training are introduced, followed by an examination of Swiss copyright law, including a brief excursus on European Union (EU) regulations. Finally, the paper explores possible future developments in jurisprudence and legislation in Switzerland.

II. AI Definition

So far, there is no generally accepted understanding of the term “artificial intelligence”. A relatively recent, legally oriented definition is provided in Article 3 of the European Union’s Artificial Intelligence Act (AI Act). According to this definition, AI includes all machine-based systems designed for varying degrees of autonomous operation, which may be adaptable after deployment, and which are capable of deriving explicit or implicit goals from received inputs, such as making predictions, providing content recommendations, or generating decisions that can impact physical or virtual environments.[1] The training and its individual components will be explained in the following chapter.

S. Marmy-Brändli/I. Oehri, page 656. ↵

III. AI Training

For AI models to produce the desired results, they must be trained using various methods. One of the most important techniques is machine learning, particularly deep learning, which utilizes artificial neural networks to replicate the complex decision-making structures of the human brain.[1] Machine learning processes rely on optimizing model parameters so that the trained model can process data as efficiently as possible. Parameter adjustment is carried out using statistical methods, typically based on large datasets. These datasets often contain complete works and are extracted from the Internet using automated tools, known as crawling and scraping software’s.[2] This poses a significant issue, as copyrighted content is frequently included in training data without explicit permission.[3]

There are three fundamentally different types of learning tasks: supervised learning, unsupervised learning, and reinforcement learning.

Supervised Learning

In supervised learning, each training example contains both an input and the desired output that the model should learn to reproduce as accurately as possible. If the output is a categorical assignment, the problem is called classification. If the output consists of continuous values, it is called a regression problem. It is therefore possible to check whether AI has solved the task correctly by actually generating the desired output.[4]

Self-Supervised Learning

Self-supervised learning is known as a specific form of supervised learning. In this approach, the training data does not contain explicit outputs, but a supervised learning task can still be formulated by inferring outputs from the available training data. Typically, some of the information is masked, hence it is not available as input, and the model must learn to fill in the missing parts. This is usually done by comparing the model’s predictions with the actual values, which allows for error calculation. In many cases, the underlying problem cannot be translated directly into an optimizable function. In such cases, a surrogate function is used: one that is optimizable and closely approximates the underlying problem.[5]

Unsupervised Learning

In unsupervised learning, the training examples do not contain output data, making it much more difficult to define an optimization function. One approach is to identify groupings where examples within the same group are as similar as possible, while examples in different groups are as different as possible. Although the learning task is less explicitly defined, unsupervised learning can reveal valuable insights, such as patterns or structures within the data.[6]

Reinforcement Learning

Reinforcement learning is a method in which an AI model, acting as an agent, learns to perform a specific task by interacting with its environment. The model maximizes “rewards” and minimizes “penalties”, it learns which behaviors or actions produce the best results in a given situation. A particular challenge of reinforcement learning is that the outcome of an action may take many steps to become apparent. For example, an agent learning to play chess does not know whether it has won or lost until the end of the game.[7]

Preliminary Conclusion

All these training methods share a common requirement: They rely on large datasets of training material. This data, often extensively sourced from the Internet, forms the foundation of AI development. However, this presents a significant challenge as it raises concerns about potential copyright infringement, particularly when protected works are used without obtaining the necessary licenses. Whether copyright is being infringed will be clarified in the next chapter.

J. Quang, page 1410; P. Dany, page 9. ↵

J. Quang, page 1411 perge perge. ↵

J. Quang, page 1411 perge. ↵

P. Dany, page 8; A. Gierbl et al., page 614. ↵

T. W. Dornis/S. Stober, page 73. ↵

P. Dany, page 9; A. Gierbl et al., page 614. ↵

A. Gierbl et al., page 614. ↵

IV. Copyright Law in Switzerland

In the legal sense, works protected by copyright are intellectual creations in literature and art that possess an individual character (Article 2 I of the Swiss copyright law). This includes, in particular, literary works (Article 2 II letter a of the Swiss copyright law), musical works (Article 2 II letter b of the Swiss copyright law), pictures and photographs (Article 2 II letters c and g of the Swiss copyright law), and computer programs (Article 2 III of the Swiss copyright law). Training AI systems with copyrighted texts, images, songs or source code could therefore constitute a legally relevant act under copyright law.

In Switzerland, there is broad agreement that not every interaction with a work constitutes a “use” within the meaning of Article 10 of the Swiss copyright law, especially not the mere enjoyment of a work.[1] The enjoyment of a work, such as reading a book, watching a film, or listening to music should be available to everyone.[2] However, using a work beyond simple enjoyment requires permission from the creator. This permission typically comes in the form of a license, which can be purchased.

However, the legal literature on Swiss copyright law interprets the concept of reproduction broadly. Reproduction includes any independent, tangible fixation of a work which directly or indirectly serves to make the work perceptible to the human senses or in any way enables such perception. This includes storing data on a storage medium or downloading content from the Internet.[3] Copyrighted works are copied during data collection, partially or fully represented in AI models, and ultimately reproduced by end users. The training process involves multiple instances of reproduction of copyrighted works. This begins with their collection, preparation, and storage. During both pre-training and fine-tuning, relevant copies are created inside the model. While no explicit storage mechanism is implemented, current generative models “remember” training data, effectively storing it in their internal memory.[4]

Copyright law is relatively strict in this regard: The author has the exclusive right to determine if, when and how his work is used, according to Article 10 I of the Swiss copyright law. This is called the exclusive right. Swiss copyright law limits the exclusive right in certain areas through so-called limitations in order to protect the public interest. Within these limitations, copyrighted works may be used without a license.[5] The next chapters will analyze four of these limitations to assess whether they allow the use of copyright-protected works for AI training without a license.

Use for Private Purposes

Article 19 of the Swiss copyright law covers certain uses of works under the term “private use”, which covers three specific groups of particularly privileged circumstances of use. These include use for personal purposes, use in the context of school lessons, and use for internal business purposes. These privileges are based on the fact that such uses are practically impossible to prevent because the copyright holder lacks the necessary control mechanisms in the first place. In addition, such controls would be undesirable in light of the protected right to privacy.[6]

Private Use

Private use is the use of a work by natural persons for personal purposes or within a circle of closely connected persons, such as family and friends (Article 19 I letter a of the Swiss copyright law), regardless of the purpose of the use of the work. This also includes groups of individuals not explicitly mentioned in the law, as long as their members are closely linked by personal relationships.[7] Private use includes all types of use of a work. In addition to the uses described in Article 10 I and II of the Swiss copyright law, it also includes the right to modify the work (Article 11 I of the Swiss copyright law).[8]

Use in Schools

The permission to use works in the classroom pursuant to Article 19 I letter b of the Copyright Act primarily reflects an educational policy consideration, namely that teaching should not be hindered by the need to obtain individual copyright permissions. The provision applies to both teachers and students. As with private use, all types of use of a work are covered; however, there is an implicit limitation in that the use must serve educational purposes, in particular by supporting the illustration and explanation of the subject matter being taught.[9]

Internal Business Use

In addition, the reproduction of works is permitted within companies, public administrations, institutions, committees and similar organizations for internal information or documentation purposes (Article 19 I letter c of the Swiss copyright law).[10]

However, the AI models in question are publicly available and can be used by anyone. As a result, the private use, use in schools and internal business use limitations do not apply in this case. The works incorporated in these publicly available models may be used by a wide range of individuals, making it difficult for such uses to fall within the privileged scope of internal business or private use as defined by the Act.[11]

Temporary Reproduction

In order to use works in digital form, it is often necessary to store them temporarily, for example in the system memory. To make this possible without the author’s consent, an exception in the form of temporary reproduction (Article 24a of the Swiss copyright law) was introduced.[12]

This limitation was originally introduced to enable the operation of internet servers without their operators continuously infringing upon an unmanageable number of copyright provisions.[13] It is questionable, however, whether this exception can also be applied to the training of artificial intelligence.

Temporary reproductions occur when data, including digitized copyrighted works, are transmitted via electronic communication technologies such as the Internet. These reproductions are typically technical requirements of the process, that is they are not based on a decision by the user of the work. They are usually temporary in nature and hence are automatically deleted after a period of time, just as they were created.[14] Additionally, temporary reproduction must not have independent economic significance.[15]

For most of the relevant processes involved in training generative AI models, the key feature of temporary reproduction is already missing. Both web scraping and the creation and storage of a data corpus are not limited to short periods of time.[16]

Furthermore, deletion is not automatic; it always depends on a deliberate action by the operators of AI systems.[17] Independent economic significance arises when copyrighted works are used to train AI applications, particularly when the provision of AI applications and the enabling of a particular output negatively impact the exploitation of the copyrighted work.[18]

Use of Works for the Purpose of Scientific Research

The scientific research exception (Article 24d of the Swiss copyright law) allows the reproduction of works for the purpose of scientific research without remuneration. The subsequent storage of such works is also permitted for backup and archival purposes. The aim of this exception is to facilitate automated data analysis. It applies when reproduction is required by the application of a technological process, hence reproduction is necessary to carry out a particular technological process. It also requires that there is lawful access to the works concerned. This applies to works made freely available on the Internet by the rightsholder as well as to works lawfully borrowed or purchased.[19]

The primary purpose of reproduction must be scientific research. According to the Swiss government, this means “the systematic search for new knowledge within the various scientific disciplines and across their boundaries”.[20] Commercial research is also covered by this exception. This exception is also known as the text and data mining exception. It covers analysis and evaluation methods that rely on algorithms, neural networks, and machine learning to derive statistical insights, identify correlations or trends. Typical steps include accessing training material, extracting and/or copying data and text, creating a data set, and preparing and analyzing the corpus.[21]

The training of generative AI applications is not, as provided in Article 24d of the Swiss copyright law, aimed at the systematic search for new knowledge. Instead, it involves programming an algorithm based on existing data and probabilities from the past, which is the exact opposite of searching for new insights and creativity.[22] Furthermore, the potential long-term goal of applying the trained algorithms to models and systems of generative AI is too open in terms of application possibilities to justify the training itself under the scientific research exception.[23]

Extended Collective Licences

In addition to statutory limitations, there is another mechanism that allows the lawful use of copyright-protected works in the context of training artificial intelligence systems. Under certain conditions, such use can be secured through an extended collective license as set forth in Article 43a of the Swiss Copyright Act. This legal instrument, introduced in the 2019 revision of the Act and modeled on provisions from Scandinavian jurisdictions has, with its implementation, also been given a more narrowly defined legal basis within European copyright law. The primary purpose of this instrument is to enable uses that are not covered by existing exceptions but for which individual licensing is impractical. The intention is therefore twofold: to provide legal certainty for users while ensuring that rights holders receive fair remuneration.[24]

Article 43a establishes a multi-layered system designed to protect the interests of rights holders as comprehensively as possible. The decisive factor is the manner in which works covered by such a collective license are to be utilized. Uses that would interfere with the regular economic exploitation of the works by their owners are excluded. Furthermore, it is required that the relevant collecting society represents a significant proportion of rights holders, provided it has been entrusted with the management of rights in a substantial way within the given sector.[25]

In practice, the conditions for applying for an extended collective license are usually met. This is especially the case when large volumes of works are involved, where their use does not impede ordinary commercial exploitation. Collecting societies generally represent a considerable share of rights holders in the fields where such licenses are relevant, thus ensuring broad coverage. A further prerequisite is that only published works may be included in the training of artificial intelligence systems.[26]

If both conditions are fulfilled and a license is granted, this must be publicly announced in an appropriate manner. Rights holders are thereby given the opportunity to opt out of the collective licensing scheme. However, pursuant to Article 42 paragraph 4 of the Copyright Act, the authorization to use the works remains valid until the collecting society receives such a declaration.[27]

One of the main advantages of this model lies in the fact that rights holders can decide whether their works may be used and, if they are, receive compensation in return. Nevertheless, such a license is always granted to a specific licensee. This means that while the mechanism is, in principle, suitable for enabling a company to make lawful use of protected works for training artificial intelligence, the responsibility remains with the system provider to apply for the necessary licenses directly or through intermediaries. Considering the vast amounts of data required for training, this process may involve a significant administrative effort as well as considerable licensing costs.[28]

Guidelines on Artificial Intelligence

Although there is currently no specific legislation on artificial intelligence (AI) in Switzerland, this does not mean that the issue has been neglected. The Swiss Federal Council is closely monitoring developments in the field of AI and has already taken various measures. At the national level, the Federal Council established the Interdepartmental Working Group on Artificial Intelligence (IDWG AI ) in 2018.[29] In its 2019 report entitle “Challenges of AI”, the working group concluded that Switzerland was, at that time, generally well positioned in the field of AI, and that the existing general legal framework was, in principle, sufficient to address the challenges associated with AI.[30] At the same time, the report identified a need for clarification and regulatory action in certain specific areas of application.[31]

In response to these findings, the Federal Council adopted strategic guidelines in 2020 to govern the use of AI within the federal administration.[32] These seven guidelines provide a general framework for orientation and are subject to regular evaluation. A core objective of the guidelines is the protection of human dignity and individual well-being, with particular emphasis on the safeguarding of fundamental rights. At the same time, the Federal Council aims to ensure that appropriate conditions are in place to promote the optimal development and application of AI. Responsibility for the use of AI must be clearly defined and cannot be delegated to machines. It should be noted that these guidelines are not legally binding for private individuals or AI providers, nor do they constitute a substitute for legislation.[33]

To further promote cooperation and knowledge exchange, the Federal Council established the Competence Network for Artificial Intelligence (CNAI) in 2022. This network supports coordination and collaboration on specific AI-related projects within the federal administration. At the international level, Switzerland has been actively involved for several years in shaping global regulatory frameworks on AI, including through its participation in the Council of Europe, the OECD, and UNESCO.[34]

Preliminary Conclusion

The use of copyright-protected works for the training of generative AI models with a primarily commercial focus is, under current Swiss copyright law, scarcely possible without the consent of the rights holders. An alternative approach lies in the application of an extended collective license, which could provide a contractual basis for such use. However, this mechanism entails significant administrative effort on the part of AI providers.

While the issue of artificial intelligence has not been overlooked in Switzerland, the measures taken thus far are limited to provisional guidelines that primarily serve guiding purposes and do not offer a definitive legal resolution. A comprehensive legislative framework or binding jurisprudence has yet to emerge.

Potential legislative adjustments and reform proposals are examined in detail at the conclusion of this thesis. How Swiss courts will ultimately address this complex matter remains to be seen. What is clear, however, is that legal practice faces substantial challenges. These will be discussed in greater detail in the following chapter.

Das neue Urheberrecht-Barrelet/Egloff, URG 10 margin note 8. ↵

S. Marmy-Brändli/I. Oehri, page 659. ↵

M. Rehbinder/L. Haas/K. Uhlig, URG 10 margin note 10. ↵

S. Krempl. ↵

E. Mühlemann/N. Ritter. ↵

R. M. Hilty, page 181. ↵

S. Marmy-Brändli/I. Oehri, page 659. ↵

R. M. Hilty, page 183. ↵

R. M. Hilty, page 185. ↵

R. M. Hilty, page 186. ↵

S. Marmy-Brändli/I. Oehri, page 660. ↵

Pfortmüller, Stämpflis Handkommentar zum Urheberrechtsgesetz, URG 10 margin note 5; Das neue Urheberrecht-Barrelet/Egloff, URG 10 margin note 16. ↵

F. Thouvenin, White Paper: Urheberrecht, page 4. ↵

R. M. Hilty, page 191. ↵

S. Marmy-Brändli/I. Oehri, page 660. ↵

C. Semmelmann, page 640. ↵

S. Marmy-Brändli/I. Oehri, page 660. ↵

E. Mühlemann/N. Ritter. ↵

S. Marmy-Brändli/I. Oehri, page 662. ↵

Botschaft, page 38. ↵

S. Marmy-Brändli/I. Oehri, page 663. ↵

F. Thouvenin/P. Picht, page 517. ↵

S. Marmy-Brändli/I. Oehri, page 662. ↵

M. Rehbinder/L. Haas/K. Uhlig, URG 43 margin note 3. ↵

R. M. Hilty, page 319. ↵

F. Thouvenin, White Paper: Urheberrecht, page 4. ↵

R. M. Hilty, page 319. ↵

R. M. Hilty, page 320. ↵

BAKOM, page 4. ↵

SBFI, page 1 perge perge. ↵

BAKOM, page 4. ↵

Bundesrat, page 1 perge perge. ↵

Bundesrat: Leitlinien «Künstliche Intelligenz» für die Bundesverwaltung verabschiedet, 25.11.2020, available for download under: https://www.news.admin.ch/de/nsb?id=81319 (accessed September 11, 2025). ↵

BAKOM, page 4. ↵

V. Practical Challenges

Although there are no public proceedings or cases in Switzerland to date, the practical challenge can be illustrated with an example from Germany.

The collecting society GEMA, which represents music makers, is suing the US provider of AI research and deployment OpenAI before the Munich Regional Court. The allegation is that OpenAI has unlawfully used the lyrics owned by GEMA members for the training of its large language model ChatGPT. The ongoing court proceedings  illustrate the complexity of the situation. In order to be successful, GEMA must first prove that OpenAI was active in Germany. If successful, it would also have to prove that the provision of ChatGPT in Germany led to a copyright infringement.[1]

The “Black Box”

The term “Black Box” is often used in the context of AI and machine learning to describe models whose internal workings are difficult for users or developers to understand or perceive. The term originally comes from engineering and refers to a system whose internal processes are unknown or inaccessible, but whose inputs and outputs can be observed.[2]

In AI, the “Black Box” refers to models whose decision-making processes are not easy to understand, even for their developers.[3] Unlike traditional machine learning models, where the link between input and output is clear, complex algorithms such as deep neural networks process data on multiple levels, making it difficult to understand how decisions are made.[4]

This lack of transparency is the essence of the “Black Box”.

For instance, if a plaintiff wants to file a complaint because they believe their work has been used in AI training without their permission, they need to be able to prove that this is the case. However, the “Black Box” nature of these models makes this almost impossible. This lack of transparency is not entirely impenetrable, as the legal framework provides for certain procedural duties that are designed to mitigate informational asymmetries, at least to some extent. The Swiss Code of Civil Procedure establishes obligations of cooperation for the parties, most notably the duty to testify and the duty of production under Article 160. On the basis of the duty of production, both parties to the proceedings as well as third parties not directly involved may be required to disclose relevant documents. This obligation also extends to records and documentation concerning the operation of AI systems. Although certain limitations apply, the mechanism often constitutes an effective means of obtaining the information necessary for the enforcement of claims arising in connection with the use of AI.[5]

However, these obligations come into effect only once legal proceedings have been initiated. As a result, the claimant must assume the risk of bearing litigation costs in order to benefit from the disclosure duties imposed on the AI companies concerned. And since it is almost unfeasible to enforce copyright, knowledge work and creative work will, as a result, be degraded in the future because their rights cannot be protected.[6]

Territorial Borders

Not only is the question of whether a work has been used challenging, but the question of where it has been used presents practical difficulties for plaintiffs. Unlike property, which is conceived as a single, universally recognized right over an object that can only be transferred as a whole, the right to a work consists of a bundle of territorially limited exclusive rights,[7] which can be transferred both collectively and individually. The enforcement of rights on the Internet, on the World Wide Web, faces significant challenges. The central reason for this is that national legal systems are bound by territorial boundaries, while actions on the web transcend these limits.[8]

There is currently no overarching legislation or case law specifically on AI in Switzerland and therefore no direct solution to the practical challenges mentioned above. However, AI technology has developed rapidly in recent years and there has also been considerable movement in the area of regulation at international level, particularly in the European Union. These developments will be examined more closely in the next chapter.

F. Steiner. ↵

B. Kohn, page 365. ↵

P. Dany, page 50. ↵

A. Boos/N. M. Pompe, page 244. ↵

F. Thouvenin, White Paper: Transparenz, page 8. ↵

L. Waltle. ↵

C. Semmelmann, page 643. ↵

P. Thouvenin, page 702. ↵

VI. Excursus on the Regulations in the European Union

In 2024, important legal frameworks in the field of artificial intelligence were established within the European Union. On the one hand, the Council of Europe has adopted a convention on the regulation of AI; on the other hand, the AI Act entered into force.[1] This chapter provides a detailed overview of both legal instruments and examines their relevance for Switzerland.

The AI Act

On July 12, 2024, the European AI Regulation came into force, putting the European Union ahead of Switzerland in this regard.

With few exceptions (Article 113 of the AI Act), it will apply from August 2, 2026, and, according to Article 2 II of the AI Act, is directly applicable to the European Union, its institutions, member states, citizens, and businesses. According to Article 2 I letter a of the AI Act, it also applies to AI providers and users outside the EU if their results are used within the Union, thus preventing circumvention through geographical agreements. The regulation is based on decades of various legislative proposals and has been adjusted with numerous technical innovations and national approaches.[2]

The AI Act covers the development, placing on the market, putting into service, and use of AI systems within the EU. Its purpose is to ensure that AI systems placed on the EU market are safe throughout their entire life cycle and comply with applicable EU standards, particularly in relation to product safety. Furthermore, the AI Act aims to facilitate the free cross-border movement of AI-enabled goods and services and to prevent market fragmentation. In doing so, it seeks to harmonize the EU internal market in the field of artificial intelligence.[3]

The AI Act indirectly aims to protect the fundamental rights of affected individuals but contains relatively few provisions granting individual rights. It applies equally to public and private actors.[4]

For Swiss stakeholders, the initial placing on the market and the first putting into service of AI systems in the EU internal market are particularly relevant. In addition, operators are required to establish a post-market monitoring plan to assess the ongoing compliance of AI systems with the requirements set out in the AI Act.[5]

It is worth noting that under Article 53 I letter c of the AI Act, a machine-readable reservation of rights by rightsholders results in the use being once again exclusive and as such prohibited without a license. Such opt-out declarations are currently installed by collecting societies or producers in the cultural sector. This declaration has the effect of a stop sign for operators of generative AI models and systems, prohibiting the use of the identified works for training purposes.[6] In this way, the use for training purposes is either generally prohibited or, increasingly, it serves as preparation for the acquisition of licenses.

According to Article 53 I letter d of the AI Act, providers of AI models with general applications are obliged to summarize the content used for training in such detail that copyright claims can be enforced and asserted. This summary must follow a template provided by the European Union’s AI Office, even though it is not directly related to specific works.[7] This provision aims to address the “Black Box” problem by enhancing transparency regarding the data used to train generative AI models.

With the European AI Regulation, the European Union has taken a significant step toward regulating artificial intelligence. The protection of intellectual property is a key focus. Particularly through the opt-out mechanism and disclosure requirements the EU’s AI Regulation appears to offer promising solutions, at least in theory.[8] However, only time will tell whether these measures can be effectively implemented. Whether Switzerland will adopt similar regulations or pursue its own approach will be discussed in the next chapter.

The AI Convention

On May 17, 2024, the Committee of Ministers of the Council of Europe adopted the “Council of Europe Framework Convention on Artificial Intelligence and Human Rights, Democracy and the Rule of Law”. It is the world’s first legally binding international treaty on AI and is not limited to European member states but takes a global approach. Under the chairmanship of Switzerland, 57 countries from nearly all regions of the world participated in the negotiations, including all G7 nations.[9]

When the Convention was opened for signature on 5 September 2024, it had already been signed by the European Union (on behalf of all 27 Member States), as well as by Andorra, Georgia, Iceland, Israel, Moldova, Norway, San Marino, the United Kingdom, and the United States of America.[10]

The convention aims to ensure that the use of artificial intelligence is in line with existing international standards on human rights, democracy, and the rule of law. To this end, it establishes a general obligation for the contracting states to safeguard human rights, the integrity of democratic processes, and respect for the rule of law throughout the entire life cycle of AI systems.

It sets out a series of fundamental principles that states must observe in their handling of AI and calls for access to effective legal remedies and the assurance of procedural safeguards. In Articles 8, 9, and 14, the convention specifically addresses the issue of the so-called “black box.” It requires measures to ensure that relevant information about AI systems and their use is documented, made accessible to the competent authorities, and disclosed to affected individuals.[11]

The contracting parties are granted broad discretion in implementing the Convention. They are free to determine which legislative, administrative or other appropriate measures to adopt in order to fulfill their obligations under the Convention. In doing so, they may tailor the implementation to their respective national legal, political  and institutional contexts, provided that the objectives and principles of the Convention are upheld.

Ratification of the AI Convention

On March 27, 2025, Federal Councillor Albert Rösti signed the AI Convention on behalf of Switzerland in Strasbourg. With this act, Switzerland reaffirms its commitment to the responsible and human rights-compliant use of AI technologies. Following the signature, Switzerland must now prepare the necessary legislative amendments. The Federal Department of Justice and Police (FDJP), in cooperation with the Federal Department of the Environment, Transport, Energy and Communications (DETEC) and the Federal Department of Foreign Affairs (FDFA), has been tasked with drafting a consultation proposal, which is expected to be available by the end of 2026. DETEC has also been mandated to develop an implementation plan for non-legally binding measures under the Convention, also by the end of 2026.[12]

In February 2025, as part of the comprehensive review of AI regulation, a report was submitted to the Federal Council. This report already examined the legislative changes Switzerland would need to undertake in the event of ratification of the AI Convention.[13]

For certain provisions of the Convention, Swiss law appears to offer a sufficiently high level of protection, making legal amendments unnecessary. This is the case, for example, with respect to the integrity of democratic processes and the rule of law (Article 5), as well as the requirement for public consultation on significant AI-related issues (Article 19).[14]

However, in other areas, existing Swiss legislation does not yet go far enough to meet the Convention’s requirements, making adjustments necessary. Key areas in this regard include transparency and oversight (Article 8), safe innovation (Article 13), legal remedies (Article 14), and procedural safeguards (Article 15). Switzerland is now obliged to address the so-called “black box” problem.[15]

In addition, Swiss law currently lacks specific provisions for some obligations set out in the Convention. This is particularly true for the framework required under Article 16 for risk and impact assessments of AI systems, as well as for the effective oversight mechanisms envisioned in Article 26 to ensure compliance with the Convention. In these areas, new legal foundations will need to be created, as the current Swiss legal framework only addresses such issues in a fragmented manner.[16]

As far as copyright is concerned, the AI Convention does not require any specific substantive provisions. As such, the Convention alone will not lead to amendments in this area. However, it does contribute to greater accountability of AI systems, which in turn is expected to facilitate the enforceability of existing substantive copyright law.

BAKOM, page 4. ↵

R. Köchli, page 367. ↵

BAKOM, page 9. ↵

BAKOM, page 9. ↵

BAKOM, page 9. ↵

C. Semmelmann, page 641. ↵

C. Semmelmann, page 642. ↵

S. Marmy-Brändli/I. Oehri, page 665. ↵

BAKOM, page 7. ↵

BAKOM, page 7. ↵

BAKOM, page 7. ↵

Generalsekretariat UVEK: Schweiz unterzeichnet Europaratskonvention zu KI, 2.03.2025, available for download under: https://www.news.admin.ch/de/nsb?id=104646 (accessed September 4, 2025). ↵

BAKOM, page 1 perge perge. ↵

BAKOM, page 8. ↵

BAKOM, page 8. ↵

BAKOM, page 8. ↵

VII. Outlook

In recent years, the development of artificial intelligence (AI) has progressed at a rapid pace and is gaining increasing significance within society. This dynamic evolution presents new challenges for the state, society at large, and particularly the legal system. At the international level, initial regulatory frameworks have already been established, including the Council of Europe’s AI Convention, ratified by Switzerland , as well as the European Union’s AI Act. It remains to be seen to what extent Switzerland will follow the EU’s lead. What is clear, however, is that the implementation of the AI Convention will necessitate certain legislative amendments. Copyright law itself, however, remains unaffected for the time being. The following chapter explores the prospect of a dedicated AI Act for Switzerland and subsequently examines the “Gössi Motion” in the context of these developments.

The Gössi Motion

Artificial intelligence (AI) is now widely used, and many are familiar with it through the provider OpenAI, which operates the chatbot ChatGPT. Nearly 70 percent of individuals under the age of 20 report using AI applications at least occasionally.[1] However, OpenAI’s chatbot operates in a legally ambiguous area with regard to copyright. In December 2023, the New York Times filed a lawsuit against the company, alleging that ChatGPT made extensive use of copyrighted content.[2]

Misses Petra Gössi, representing the Free Democratic Party (FDP) in the Council of States of the canton of Schwyz, was among the first Swiss politicians to draw attention to the potential infringement of intellectual property rights by AI technologies. In collaboration with the Neue Zürcher Zeitung, she conducted a practical test in September 2024 by asking the AI system about the public debate concerning the administrative and security complex in Kaltbach, which will house around 500 jobs for cantonal administrations and the cantonal police forces of Schwyz and Zug. The question of whether the canton of Schwyz should invest nearly 140 million Swiss francs in the new building had received little attention outside the region. Apart from a few local and regional media outlets, the issue had not been broadly reported.

Nonetheless, the AI application provided a detailed summary of the main arguments for and against the project within minutes. The primary source was clearly the Einsiedler Anzeiger, a regional newspaper whose online content is strictly protected by a paywall and intended exclusively for paying subscribers. Despite this, almost the entire content of the article appeared in the AI-generated response. Misses Gössi subsequently raised the critical question of why anyone would still pay for a newspaper subscription if it were possible to access such content worldwide and free of charge via AI. In June 2024, she had already brought attention to this issue in the Council of States. At that time, the Federal Council responded cautiously, stating that it was aware of the challenges, was monitoring developments closely, and would take legislative action if necessary.[3]

On December 20, 2024, the “Gössi Motion” was submitted to the Council of States by  Ms. Petra Gössi. The motion calls on the Federal Council to establish the necessary legal framework to ensure that journalistic content and other works and performances protected by copyright receive comprehensive protection when used by AI providers. Specifically, it should be clarified in the Swiss Copyright Act (CopA) that the consent of copyright holders is required whenever journalistic content and other original creative works are extracted, processed, or reused in any form for generative AI services. This either applies under the usage rights provided for in Article 10 II CopA, or under the general clause of Article 10 I. Furthermore, the motion demands that the limitations and exceptions set out in the Act, particularly in Article 19 III, and where applicable, in Articles 24a, 24d, and 28, should explicitly state that public AI services and offerings cannot invoke copyright exceptions or limitations to justify such uses. Lastly, it should be made clear that Swiss law applies and Swiss courts have jurisdiction when such content is made accessible in Switzerland. The Federal Council has recommended that the motion be adopted.[4] Petra Gössi not only succeeded in convincing the Federal Council, but the Council of States also adopted the motion and referred it to the National Council for further deliberation.

In essence, the legal regulation of artificial intelligence is expected to be articulated in clear and explicit terms. In the absence of statutory provisions and relevant case law, a considerable degree of legal uncertainty currently prevails in this area. The aim is to establish a definitive legal rule stating that AI training shall, under no circumstances, fall within the scope of existing copyright limitations and exceptions. As a result, the express consent of the copyright holder must always be obtained before using protected intellectual property for AI training purposes.

Unlike the approach taken in the EU’s AI Act, this model would not require rights holders to take active steps in order to protect their intellectual property. Ms. Gössi concludes by emphasizing that the effective protection of intellectual property is essential to safeguarding Switzerland’s capacity for innovation.[5]

The Emerging Challenges for AI Providers

The motion in question addresses Swiss copyright law and thus affects all AI providers based in Switzerland or offering their services within Swiss jurisdiction. While the Gössi motion aims to protect intellectual property rights, it does so in a manner that imposes significant constraints on AI providers. These providers face the daunting challenge of obtaining consent from every individual copyright holder in order to continue training their AI systems. Unless a feasible solution is found, AI providers relying on copyright-protected data for training might be forced to cease operations in Switzerland.

Although the Gössi motion has garnered considerable support, Federal Councillor Mister Albert Rösti recognizes the necessity of promoting AI development in Switzerland to avoid falling behind in the global AI race. Such a setback would be reminiscent of past developments: Europe was the birthplace of the Internet, yet today, the major US tech companies dominate the market. This dominance is largely attributable to the enactment of laws such as Section 230 of the Communications Decency Act (1996), a federal US law which shield internet companies from liability for user-generated content and thereby fostered the sector’s growth.[6]

To prevent Switzerland from lagging behind, the regulatory framework must be adapted to better support innovation. In this context, Federal Councillor Mister Rösti has proposed convening a national AI conference.[7] Effective AI training requires access to substantial datasets. For example, Japan permits the use of copyright-protected works for AI training, thereby securing a strategic advantage over Europe.[8] In contrast, the Gössi motion may hinder Switzerland’s capacity for innovation in the AI sector. Protecting copyright holders’ rights while simultaneously fostering the development of AI in Switzerland requires that copyright law not be tightened without offering AI providers viable solutions. If Switzerland fails to do so, it will run the risk of quickly becoming a laggard in the field of artificial intelligence.

Possible Implementation of an AI Act in Switzerland

The question is, if Switzerland will also enact its own “AI Act”. Although such practical problems also exist in Switzerland, there is still no legislation in this country dealing with copyright in AI training courses. As part of a project carried out by the Center for Information Technology, Society, and Law (ITSL) at the University of Zurich and the Research Forum on electronic Public Institutions and Administrations (e-PIAF) at the University of Basel, possible approaches were examined.[9] When asked about solutions, the Federal Department of Justice and Police (FDJP) now points to the findings of this project.

The Complete Exemption

One approach that would arguably be the simplest to implement is the complete exemption, which allows copyrighted works to be used for the training of artificial intelligence models without the payment of remuneration. This model is currently applied in Japan in order to promote the development of artificial intelligence as comprehensively as possible. However, this approach considers neither the legitimate interests of rights holders nor the economic value associated with the use of their works.[10]

The Content Flat Rate

Instead of permitting unrestricted use, a statutory limitation in the form of a license could be introduced; this would allow the use of copyrighted works for the training of artificial intelligence models while also being subject to a compensation requirement. Such a provision would make it possible to legally regulate the currently largely uncontrolled mass use of protected content from the Internet. Until now, the concept of a statutory license has primarily been associated with the reproduction, distribution, or public accessibility of works in non-commercial contexts.[11] For applications in the field of artificial intelligence, however, this model would need to be fundamentally reconsidered and adapted to commercial use scenarios. In return for the legally permitted use, rights holders would receive appropriate remuneration, since companies developing AI systems would be required to pay a flat fee for access to the relevant works within this legal framework.

The introduction of such a statutory license could provide legal certainty and significantly reduce transaction costs. Moreover, this limitation could be seamlessly integrated into the existing system of copyright exceptions under the Copyright Act. The specific design of the compensation, both in terms of its calculation basis and its amount, would need to be governed by a joint tariff established by the collecting societies, which could be adjusted as needed to reflect technological developments.[12]

Despite these advantages, certain disadvantages must also be considered. In particular, given that the training of current large-scale AI models involves processing vast quantities of works from an almost unmanageable number of different rights holders, this approach appears only partially effective. In practice, the financial benefit for most rights holders would be minimal. Furthermore, the introduction of a statutory license would mean that holders of large collections of works, such as media companies, publishers, or image agencies, could no longer license and monetize their high-quality content through contractual agreements. This could lead to a situation where a functioning licensing market either does not develop at all or is jeopardized in its current form.[13]

Exemption with Opting-Out

A potential legislative amendment could consist of introducing an exemption regulation based on an opting-out mechanism. This way, copyright-protected works may, in principle, be used for the training of artificial intelligence, unless the author has expressly objected to such use. Such a reservation of use would have to be declared by the rights holders in an appropriate format, particularly in a machine-readable form, either for individual works, for several specific works, or for a clearly defined set of works. From the perspective of legal doctrine, this would amount to the creation of a new statutory limitation on copyright.[14]

Although this approach offers various advantages, it also presents certain challenges. Its practical effectiveness depends in particular on how many rights holders exercise their right to opt out and which works are affected. Should this occur especially in the case of large datasets, it could initiate negotiations and lead to the conclusion of licensing agreements for usage. In most cases, however, such a reservation would simply result in certain works being excluded from AI training, as it is hardly practicable to negotiate licensing agreements with a large number of individual rights holders. These rights holders would ultimately be in a position to either prohibit the use of their works altogether or to silently tolerate it.[15]

The possibility of permitting the use of works in exchange for remuneration would be difficult to implement in practice due to the disproportionately high transaction costs involved. Furthermore, rights holders who have declared an opting-out must be able to verify whether their works have indeed been excluded from the training of an AI model. To this end, a corresponding right to information would be required, enabling them to obtain data from the providers of such models regarding whether their work was used in training.[16]

In addition, technical mechanisms could be developed to enable logging and documentation of usage, indicating whether certain content was accessed despite an opting-out declaration. Such a system could contribute to legal certainty, facilitate innovation, and promote a fair balance of interests among all parties involved.[17]

Moreover, this approach would represent an alignment with the provisions of the European AI Act. The Act also provides that copyright-protected works may, in principle, be used for AI training unless rights holders actively object to such use. However, this requirement for proactive action is untypical under Swiss law, since the exclusive right, as set out in Articles 6 and 8 of the Swiss Copyright Act, is automatically vested in the author. It therefore remains to be seen whether Switzerland will adopt a similar approach. Should there be a political will to further align national legislation with the AI Act, this would result in extensive new obligations for the affected parties.[18]

The Hybrid Model

A conceivable solution is a hybrid approach combining elements of the second and third models. Under this framework, legislation would stipulate that the use of protected works for training AI models is generally permitted, but subject to a remuneration obligation. Authors would retain the option to exclude their works from such use through an opting-out procedure. They could subsequently grant specific AI providers permission to use their works under individually negotiated licensing agreements. While this model would entail a certain degree of administrative effort, it could offer a balanced reconciliation of the interests of rights holders and developers of generative AI.[19]

C. Neuhaus/B. Skinner. ↵

McKool Smith, AI Infringement Case Updates: May 5, 2025: available for download under: https://www.mckoolsmith.com/newsroom-ailitigation-21 (accessed September 5, 2025). ↵

C. Neuhaus. ↵

Motion 24.4596 from Gössi Petra, Besserer Schutz des geistigen Eigentums vor KI-Missbrauch, 20.12.2024, available for download under: https://wmww.parlament.ch/de/ratsbetrieb/suche-curia-vista/geschaeft?AffairId=20244596 (accessed September 4, 2025). ↵

C. Neuhaus. ↵

L. Finger. ↵

B. Balzli. ↵

L. Finger. ↵

F. Thouvenin, White Paper: Urheberrecht, page 4. ↵

F. Thouvenin, White Paper: Urheberrecht, page 4. ↵

M. Wullschleger, page 203 perge perge. ↵

F. Thouvenin, White Paper: Urheberrecht, page 5. ↵

F. Thouvenin, White Paper: Urheberrecht, page 5. ↵

F. Thouvenin, White Paper: Urheberrecht, page 5. ↵

F. Thouvenin, White Paper: Urheberrecht, page 5. ↵

F. Thouvenin, White Paper: Urheberrecht, page 5. ↵

F. Thouvenin, White Paper: Urheberrecht, page 5. ↵

BAKOM, page 10; F. Thouvenin, White Paper: Urheberrecht, page 5. ↵

F. Thouvenin, White Paper: Urheberrecht, page 5. ↵

VIII. Conclusion

The legal qualification of the use of copyright-protected works in the training of generative AI models constitutes one of the most pressing and complex challenges facing contemporary copyright law. Under the current Swiss legal regime, such use is permissible only under narrowly defined conditions, notably through statutory limitations or extended collective licensing mechanisms. This state of affairs underscores the limited capacity of existing instruments to effectively address the multifaceted demands of AI innovation.

Any prospective legislative reform, whether prompted by the Gössi motion – as outlined in Chapter VII. A. – or pursued independently, would necessitate a meticulous balancing of interests among AI developers and copyright holders. As demonstrated, the pursuit of parity between these competing interests is fraught with difficulty: enhancing the position of one stakeholder invariably constrains the other. A stark choice – either the pace and scope of AI advancement are significantly impeded, or the legitimate rights of authors are impermissibly diminished.

Furthermore, such reform could entail a profound departure from the foundational principles of Swiss copyright law, particularly the doctrine of automatic protection for creative works. If this trajectory were nonetheless adopted, a hybrid model could provide a pragmatic and equitable compromise. Under this framework, the use of protected works for AI training would be broadly permissible but subject to a remuneration obligation, coupled with an opting-out provision enabling rights holders to exclude their works from such use. Subsequently, they could selectively license their works to certain AI providers under individually negotiated agreements. While this construct entails a degree of administrative complexity, it offers the potential for a nuanced equilibrium, safeguarding intellectual property rights while sustaining the momentum of technological innovation.

The analysis further reveals that the challenges are not solely normative but also deeply technical and regulatory, particularly with respect to the opacity of training datasets. The “black box” phenomenon demands timely and practicable solutions if future obligations for AI developers are to be meaningfully enforced. Ensuring verifiable transparency as to which works have been incorporated into training processes is indispensable. Should the European AI Office prove capable of executing its mandate effectively, Switzerland would be well-advised to consider alignment with this model as a matter of strategic foresight.

In the final analysis, Switzerland’s enduring challenge will lie in establishing a coherent and adaptive regulatory framework, one that affords legal certainty to practitioners while actively engaging with the dynamics of technological transformation. Only by achieving this balance can Switzerland preserve its dual identity as an innovative and globally competitive hub, firmly anchored in the rule of law.