The International Confederation of Societies of Authors and Composers (CISAC) commissioned the consulting firm PMP Strategy to conduct a comprehensive study aimed at projecting the impact of audiovisual and musical content generated by Artificial Intelligence (AI) systems over a five-year horizon. This analysis seeks to answer three fundamental questions:
- What will be the market size of AI-generated content in 2028?
- What will be the associated revenue losses creators will face in 2028?
- What will be the revenue generated by generative AI tools and service providers in 2028?
Key Findings in the Music Sector
The study identified several areas within the music industry where AI adoption has a significant impact. These areas include:
- Content curation and consumption on streaming platforms, where AI intervenes in the selection and personalization of playlists.
- Background music in public spaces and audiovisual works, where automatically generated compositions are used.
- Commercial distribution of music on streaming platforms, with the incorporation of music generated by AI.
- Incidental or diegetic music in audiovisual productions, where AI is used to generate specific compositions for particular scenes.
Projections indicate that, by 2028, music generated by AI will represent a market valued of €16 billion, with a cumulative value of €40 billion over the five-year period. It is expected that 20% of the revenue generated by streaming platforms will come from music created by AI, while this technology will account for 60% of the revenue from music libraries.
Regarding projected losses for creator, the study estimates that, by 2028, music creators could face a revenue loss of €4 billion, equivalent to a 24% reduction. This decline is projected to accumulate to €10 billion over the next five years.
Also, Gen AI services’ revenue is expected to reach €4billion in 2028, with a cumulative toral of €8 billion over the next 5 years.
Key Findings in the Audiovisual Sector
In the audiovisual sector, AI is being integrated into various creative and operational processes, including:
- Generation of complete audiovisual works, with the creation of videos and visual sequences using AI.
- Automatic dubbing and subtitling, facilitating the localization of content for international audiences.
- Assistance in production direction, where AI supports creative decision-making.
- Automatic script generation, streamlining the pre-production phase of audiovisual works.
It is projected that the market for AI-generated audiovisual content will reach a value of €48 billion by 2028. However, it is also estimated that creators in this sector could face a revenue loss of €4.5 billion (-21%), with a cumulative loss of €12 billion over five years.
The study also examines the revenue to be generated by generative AI tools and service providers. By 2028, this revenue is expected to reach €5 billion, with a cumulative total of €13 billion over the following five years.
Recommendations and the Need for a Regulatory Framework
In light of these results, CISAC has emphasized the need to establish an appropriate regulatory framework to protect the rights of creators. In particular, it highlights the importance of ensuring that authors and copyright holders receive fair remuneration for the use of their works in the training of generative AI systems. This framework must recognize the value of human creative contributions and promote the sustainability of the creative industry amid the growing automation of content production processes.
Our thoughts:
The development of a regulatory framework to address the challenges posed by artificial intelligence in the creative industry should focus on creating a system that allows companies that own generative AI systems or service providers to pay a license fee for the use of copyrighted works to train their models and generate content. However, this proposal raises numerous questions regarding the implementation of such a system.
Initially, the creation of a collective management society could be considered, with the specific objective of managing rights related to the use of protected works for AI training. Nevertheless, the main challenge lies in defining the criteria for the distribution of the collected revenue. The distribution methods currently used by collective management societies do not seem applicable, as identifying the authors who should receive compensation is extremely complex.
Additionally, other challenges must be addressed, such as defining the admission criteria for members of the management entity, determining the percentages for the distribution of collected revenue, and adopting efficient and transparent methods for the traceability of the works used in AI training systems.
