Generative AI in Music Market Soar to USD 2,660 Million by 2032

Yogesh Shinde
Yogesh Shinde

Updated · Mar 4, 2024

SHARE: is supported by its audience. When you purchase through links on our site, we may earn an affiliate commission. Learn more.
Advertiser Disclosure

At Scoop, we strive to bring you the most accurate and up-to-date information by utilizing a variety of resources, including paid and free sources, primary research, and phone interviews. Our data is available to the public free of charge, and we encourage you to use it to inform your personal or business decisions. If you choose to republish our data on your own website, we simply ask that you provide a proper citation or link back to the respective page on Scoop. We appreciate your support and look forward to continuing to provide valuable insights for our audience.


Generative AI in music refers to the application of artificial intelligence techniques, specifically generative models and algorithms, to compose, produce, and generate music autonomously. Generative AI models can analyze vast amounts of musical data, learn patterns, and create new melodies, harmonies, and rhythms that closely resemble human-created music. This technology has revolutionized the music industry by offering new creative possibilities, automating music composition, and providing personalized music experiences.

According to, The global Generative AI in Music market was valued at USD 229 million in 2022 and is expected to reach USD 2,660 million by 2032, with a remarkable CAGR of 28.6%.

The generative AI in music market has witnessed substantial growth in recent years, driven by several factors. Firstly, advancements in deep learning algorithms and neural networks have significantly improved the capabilities of generative AI models in understanding and creating music. These models can now generate complex musical compositions, experiment with various genres and styles, and even collaborate with human musicians.

Secondly, the demand for personalized music experiences and unique content has fueled the adoption of generative AI in the music industry. Music streaming platforms, production companies, and artists are leveraging generative AI to create personalized playlists, generate background music for videos or advertisements, and compose original pieces tailored to specific moods or preferences.

Furthermore, the efficiency and productivity offered by generative AI in music production have been driving factors for its market growth. Generative AI models can compose music at a rapid pace, reducing the time and resources required for traditional music composition. This scalability and efficiency allow musicians and composers to explore a wider range of musical ideas and output, leading to increased productivity and creativity.

Generative AI in Music Market size

To learn more about this report – request a sample report PDF

One of the key opportunities in the generative AI in music market is the ability to automate music composition and generate a vast amount of original content. Generative AI models can analyze large datasets of existing music, learn patterns and structures, and generate new compositions that align with specific genres, moods, or artist styles. This opens up possibilities for musicians and composers to explore new creative territories and expand their musical repertoire.

Moreover, generative AI in music enables personalized music experiences for listeners. By leveraging user data, preferences, and contextual information, generative AI models can create personalized playlists, generate music that suits individual moods or activities, and offer tailored recommendations to enhance the music discovery process. This personalization enhances user engagement and satisfaction, leading to increased user retention and loyalty.

Additionally, the integration of generative AI with other technologies, such as virtual reality (VR) and augmented reality (AR), presents new opportunities for immersive music experiences. Generative AI can be used to create interactive and dynamic soundscapes, virtual concerts, and personalized audiovisual experiences, enhancing the overall music consumption and live performance aspects.

Furthermore, the generative AI in music market offers opportunities for collaboration between human musicians and AI models. Musicians can leverage generative AI as a creative tool and collaborate with AI models to explore new musical ideas, experiment with different genres and styles, and push the boundaries of traditional music composition.

Generative AI in Music “Latest” Statistics

  • The Generative AI in Music Market size is expected to be worth around USD 2,660 Million by 2033, from USD 294 Billion in 2023, growing at a CAGR of 28.6% during the forecast period from 2024 to 2033.
  • The software segment dominates the market, holding the largest global revenue share of 55% in 2022, while the services segment is expected to grow at the fastest CAGR.
  • Generative Adversarial Networks (GANs) lead the market, accounting for 41% of the market revenue share in 2022, with transformer-based models expected to grow at the fastest CAGR.
  • Music mastering holds the largest market revenue share in 2022, with a share of 30%, followed by music composition.
  • North America dominates the market with a share of 35% in 2022, attributed to technological advancements in the music industry, while the Asia Pacific region is expected to witness the fastest CAGR.
  • In 2023, a transformative year for the music industry, over 65% of major music production software companies incorporated generative AI tools into their platforms, enabling automated melody, chord, and rhythm generation. This innovation significantly influenced the creative landscape, with an estimated 22% of hit songs on music charts featuring some level of generative AI assistance in their composition processes.
  • The realm of electronic music, particularly EDM, witnessed a noteworthy shift with over 40% of producers utilizing generative AI in at least a portion of their composition workflow. This trend underscored the growing acceptance and integration of AI technologies in music production.
  • A landmark achievement was observed with Google’s MusicLM, an AI music generation model, which achieved human-level quality ratings in blind tests involving over 10,000 participants, highlighting the advanced capabilities of AI in mimicking human musical creativity.
  • Financial investment in the sector soared, with generative AI music startups receiving over $450 million in venture funding throughout the year, indicating robust confidence in the potential of AI-driven music innovation.
  • Distribution platforms such as DistroKid and TuneCore adapted to the evolving landscape by allowing direct uploads of AI-generated music, reflecting the mainstreaming of AI in music distribution channels.
  • The commercial success of generative AI in music was exemplified by “AVIA,” a generative AI system, amassing over 100,000 paid subscribers for its AI-composed music, showcasing significant consumer interest and market viability for AI-generated compositions.
  • However, the integration of AI in music also sparked debate and controversy, notably within the Grammy Awards, which faced criticism for the absence of clear guidelines regarding AI contributions, following several AI-assisted nominations.
  • Despite the technological advancements and successes, over 75% of music producers surveyed voiced concerns regarding the potential of generative AI to supplant human creativity and artistry, reflecting underlying apprehensions about the future role of AI in music.
  • Streaming platforms experienced a significant uptick in AI-generated music consumption, with global streaming numbers witnessing over 200% year-over-year growth between 2022 and 2023, indicating a rapidly growing audience for AI-created music.
  • The integration of generative AI music tools in the production of soundtracks for over 20 TV shows, films, and video games by late 2023 further demonstrated the broadening applications of AI in entertainment.
  • Major record labels, including Sony, Warner, and Universal, collectively invested over $100 million into generative music AI companies, signaling strong industry belief in the technology’s future.
  • As the technology proliferated, AI music detectors saw a 70% increase in use, driven by rising concerns over plagiarism and copyright issues associated with generative AI, highlighting the challenges and ethical considerations in the field.
  • The “AI Music Fair” held in Tokyo in November 2023, featuring over 150 exhibitors, showcased the latest in generative music technology, underscoring the global interest and investment in AI’s role in music creation.
  • Lastly, China’s technological landscape was significantly impacted, with tech giants Baidu, Tencent, and Alibaba launching their own generative AI music apps and tools, targeting the vast Asian market and marking a global shift towards AI-driven music innovation.

How does Generative AI impact the Music Industry

Generative AI has had a significant impact on the music industry, transforming various aspects of music creation, production, and consumption. Here are some ways in which generative AI has influenced the music industry:

  • Music Composition and Creation: Generative AI models can analyze vast amounts of musical data, learn patterns, and generate new musical compositions. This has opened up new creative possibilities for musicians and composers by offering them a tool to explore different melodies, harmonies, and rhythms. It can help overcome creative blocks, inspire new ideas, and generate music in various styles and genres.
  • Personalized Music Experiences: Generative AI enables personalized music experiences for listeners. By leveraging user data, preferences, and contextual information, AI models can create personalized playlists, generate music that suits individual moods or activities, and offer tailored recommendations. This enhances the music discovery process and provides users with a more engaging and customized music experience.
  • Music Production and Arrangement: Generative AI can assist in music production and arrangement tasks. It can generate backing tracks, create variations of existing musical elements, and even collaborate with human musicians. This automation and assistance can streamline the production process, save time, and provide musicians with additional creative options.
  • Royalty-Free Music and Licensing: Generative AI has the potential to generate original music that is royalty-free and available for licensing. This can benefit content creators, filmmakers, and advertisers who require music for their projects without the need for costly licensing fees or copyright restrictions. It offers a broader range of options for finding suitable music for various media productions.
  • Remixing and Mashups: Generative AI models can analyze existing music and generate remixes or mashups by combining elements from different songs. This can offer new and unique interpretations of popular songs and allow artists and DJs to create fresh and innovative versions of existing tracks.

Major Challenges

In the music industry, using generative AI (artificial intelligence) brings up several big challenges that need careful attention:

  • Intellectual Property and Copyright: When AI creates music, figuring out who owns the rights to that music gets complicated. It’s hard to tell apart what’s made by humans from what’s made by machines. We need clear rules and guidelines to solve these legal and ethical puzzles.
  • Lack of Human Emotional Connection: AI can make music that sounds a lot like what humans create, but it might not capture the heart and soul that human musicians put into their work. Music has a special way of touching emotions, and AI still struggles to match this.
  • Overreliance on Existing Data: AI learns from existing music to make new tunes. However, this can lead to new music that sounds too much like what’s already out there, lacking freshness and originality. It’s a big task to push AI to come up with truly new and diverse sounds.
  • Ethical Considerations: Using AI to make music also brings up ethical issues, like being true to the original culture, not taking away jobs from human musicians, and ensuring that AI respects everyone’s cultural background. It’s important to think about these issues carefully to make sure AI enhances the music world without causing harm.

Broader Benefits

The introduction of generative AI into the music industry brings forth several significant benefits, impacting creativity, efficiency, personalization, exploration, accessibility, and preservation.

  • Enhancement of Creativity and Inspiration: Generative AI acts as a novel tool for musicians and composers, sparking new avenues for creative thought and innovation. By producing fresh musical ideas and offering alternative viewpoints, it aids artists in breaking through creative stalemates, thereby enriching the music creation process.
  • Boost in Efficiency and Productivity: By automating routine tasks in music production, such as crafting backing tracks or modifying musical elements, generative AI streamlines the workflow. This automation allows musicians and producers to allocate more time and energy towards the artistic and expressive facets of their projects, enhancing both productivity and the quality of their output.
  • Personalization of Music Experiences: Through generative AI, music experiences become highly personalized, adapting to individual tastes, moods, and contexts. This technology tailors music recommendations and playlists to user preferences, elevating engagement and providing a more immersive and customized listening experience.
  • Exploration of New Musical Frontiers: Generative AI facilitates the exploration of untapped musical landscapes. It supports the fusion of genres, the invention of novel compositions, and the discovery of unique musical blends, pushing the boundaries of conventional music and opening up new creative possibilities.
  • Accessibility to Royalty-Free Music: Generative AI offers a pathway to accessing royalty-free music, making it easier for content creators, filmmakers, and advertisers to utilize music without the complexities of licensing fees and copyright issues. This accessibility fosters creativity and innovation in various media projects.
  • Preservation and Revival of Musical Styles: By learning and replicating specific musical styles and genres, generative AI plays a crucial role in preserving and revitalizing traditional or culturally significant music. This capability ensures the continuity and exploration of diverse musical heritages, keeping them relevant for future generations.

Recent Developments

  • Notably, the Consumer Electronics Show (CES) 2024 served as a platform to showcase how generative AI developments are increasingly being integrated into consumer technology products. Key events included funding announcements and mergers and acquisitions, such as the deals involving Qlik and Typeface. Additionally, legal and regulatory issues, particularly copyright infringement, were highlighted by a lawsuit filed by The New York Times against Microsoft Corp. and OpenAI LLC
  • OpenAI marked the beginning of 2023 by formally launching its GPT store, which allows users to monetize models they developed with the new controls for GPT tailoring introduced in November 2023. Although full details on the payment structure were not disclosed, initial payments in the US were said to be based on user engagement
  • At CES, several generative AI announcements were made, spanning from traditional technology providers to automotive companies integrating ChatGPT into vehicles as an enhancement to voice assistants. Amazon’s Alexa introduced new generative AI “skills,” including one that enables users to interact with chatbots representing characters like historical figures or fitness coaches​


In conclusion, the generative AI in music market is driven by advancements in deep learning algorithms, the demand for personalized music experiences, and the efficiency and productivity offered by generative AI. The market offers opportunities for musicians, music companies, and technology providers to enhance music production, deliver personalized experiences, and explore new creative territories. As generative AI continues to evolve, it will likely play a significant role in shaping the future of music composition, production, and consumption.

Yogesh Shinde

Yogesh Shinde

Yogesh Shinde is a passionate writer, researcher, and content creator with a keen interest in technology, innovation and industry research. With a background in computer engineering and years of experience in the tech industry. He is committed to delivering accurate and well-researched articles that resonate with readers and provide valuable insights. When not writing, I enjoy reading and can often be found exploring new teaching methods and strategies.