Generative AI In Music Market By Component(Software, Services), By Type(GANs, AR-CNNs, Transformer-based Models), By Application(Music Mastering, Composition of Music, Streaming Music, Making of New Sounds, Other Applications), By Region And Companies - Industry Segment Outlook, Market Assessment, Competition Scenario, Trends, And Forecast 2024-2033

Report Overview

The Generative AI In Music Market was valued at USD 294.5 Million in 2023. It is expected to reach USD 3,421.3 Million by 2033, with a CAGR of 28.6% during the forecast period from 2024 to 2033.

The surge in demand for new advanced technologies, original music composition, and emergence in the entertainment industry are some of the main key driving factors for the generative AI in music market. Generative AI is a part of artificial intelligence that helps to generate unique and new data that are quite similar to textbooks, videos, audio, and images. In music industry, GenAI helps music composers to produce new chimes, measures, warbles, and even whole songs. This technology can transform how music is developed, with some musicians and artists already implementing GenAI to generate new and unique compositions.

There are two chief ways of utilizing GenAI in music composition. One way is to train an algorithm on a huge number of music datasets. The algorithms understand and learn the pattern as well as structure of the music, by using this technique to produce innovative music that is quite similar to the training data. Another method is using GenAI to generate unique and original music ideas that are not stranded in music. By using GenAI to persuade random sequences of notes or by utilizing GenAI to discover the space of probable musical combinations.

Generative AI model in music composition generally include advanced ML algorithms such as RNNs, and variational autoencoders. These algorithms are the base of this model. The model observes and develops music based on the information that the model has understood and learned. Several music composers and creators hold on to the ML substructure such as PyTorch and TensorFlow to develop and train. Testing with numerous network architectures, training methods, and high parameters to optimize the standards and innovation of the developed music.

According to IFPI’s global music report in March 2023, highlights that the global recorded music market surged by 9.0% which was driven by the upsurge in paid subscription streaming, as per IFPI, the company that epitomizes the recorded music industry globally. The overall trade revenue for 2022 was USD 26.2 billion. Moreover, subscription of audio streaming revenue was augmented by 10.3% to USD 12.7 billion and there were 589 million users who had paid subscription accounts at the end of 2022.

The overall streaming which includes paid subscription and advertising-supported boosts by 11.5% to reach USD 17.5 billion or 67% of the overall worldwide recorded music revenues. There was also growth in different areas with physical revenues remaining strong at 4.0%, the performance rights revenue augmented by 8.6% and the return of post-Covid-19 pandemic levels and synchronization revenue reached 22.3%.

There are several benefits of implementing GenAI in music such as it creates innovative variations and combinations of music. It also helps in saving time and maintaining efficacy, helps to discover new musical styles and genres, and helps in overcoming innovative and creative blocks. Using this technology, the customer can also tailor music according to his/her preference and taste. The demand for GenAI in music will rapidly increase due to its high requirement in the music industry and changes in customers’ music preferences that will help in market expansion in the coming years.

Key Takeaways

• Market Growth: The Generative AI In Music Market was valued at USD 294.5 Million in 2023. It is expected to reach USD 3,421.3 Million by 2033, with a CAGR of 28.6% during the forecast period from 2024 to 2033.
• By Component: Software dominated due to advanced functionality and high demand for integrated solutions.
• By Type: Generative Adversarial Networks (GANs) dominated with innovative applications in image and video synthesis.
• By Application: Music mastering is dominated, driven by AI's ability to enhance sound quality efficiently.
• Regional Dominance: In 2023, North America holds a 32% share of the global generative AI music market.
• Growth Opportunity: In 2023, AI-powered music tools are revolutionizing production and composition, enhancing efficiency and quality across composition, mastering, and streaming, promising significant growth in the global generative AI music market.

Driving factors

Enhanced Personalization Drives Consumer Engagement

The increased demand for personalized music experiences and unique content is a significant driver in the generative AI music market. Consumers' growing preference for tailored content that reflects their tastes and moods has catalyzed the adoption of AI technologies capable of creating highly personalized music experiences.

This trend is not only altering how consumers interact with music but also how they perceive its value, leading to increased market engagement and growth. Personalization capabilities provided by generative AI enable the production of unique content at scale, which can be leveraged by streaming platforms and music producers to enhance user satisfaction and retention.

Boosting Efficiency and Productivity in Music Production

Generative AI significantly enhances efficiency and productivity in music production. By automating time-consuming processes such as sound selection, mixing, and mastering, AI allows music producers and artists to focus on creative aspects. This efficiency not only reduces production costs but also speeds up the creation process, enabling artists and studios to produce more content faster.

This aspect is particularly valuable in an industry where the speed of content creation can be as critical as the content itself. Integrating AI technology into music production studios has proven a crucial asset, supporting both its expansion and evolution within the music industry.

Automation and Innovation in Composition

The automation of music composition through generative AI plays a pivotal role in the industry by enabling the generation of new compositions without human input. This capability is revolutionary, as it opens up possibilities for creating vast amounts of music quickly, which is especially beneficial for background scores in games, films, and online content.

Furthermore, AI's ability to generate innovative musical pieces by learning from a diverse array of data introduces a new era of creativity that transcends traditional boundaries. This not only expands the creative landscape but also stimulates market growth by attracting new creators and audiences eager to explore novel musical expressions.

Restraining Factors

Data Privacy and Security Challenges

Data privacy and security concerns are substantial restraining factors in the growth of the generative AI in music market. The integration of AI in music production involves the processing and analysis of vast datasets, which often include sensitive information such as user preferences, listening habits, and personal data.

This raises significant privacy concerns, as the misuse or breach of such data could lead to severe repercussions for both users and providers. The apprehension about data security can deter consumers and music companies from adopting AI-based solutions, thereby slowing market growth. Ensuring robust security measures and transparent data handling practices are critical to alleviating these concerns and fostering trust in AI applications within the music industry.

Impact of Lack of Standardization

A lack of industry-wide standards for the implementation and operation of generative AI in music presents a formidable barrier to its growth and adoption. Without standardized protocols, there can be inconsistencies in AI performance, interoperability issues between different systems, and difficulties in assessing the quality and fairness of AI-generated music.

This lack of standardization can lead to a fragmented market where consumers and professionals are unsure of the reliability and credibility of AI-generated content. Establishing common standards would facilitate smoother integration of AI technologies, promote uniform quality across products, and enhance user confidence, ultimately supporting broader adoption and growth in the market.

By Component Analysis

By Component, the dominance of Software is marked by innovative platforms enhancing user interfaces and analytics capabilities.

Software was the clear market leader in 2023 in terms of market penetration and revenue generation in Generative AI Music Market's "By Component" segment, outpacing Services both in terms of market share and revenue generation. This could be attributed to the increasing adoption of AI-powered tools for music composition, editing, and production processes; more advanced algorithms capable of creating complex musical pieces while adapting to various styles and learning from user input greatly augment artists and producers' creative capabilities thereby further propelling this segment's growth.

The market demand for such software is driven by its ability to reduce the time and cost associated with traditional music production. By automating part of the creative process, software solutions not only expedite the production cycle but also enable customization at scale, which appeals to both individual artists and large production key companies. The scalability of these solutions has facilitated a broader acceptance across different segments of the music industry, from independent artists seeking affordable production means to large studios aiming to innovate and improve productivity.

Moreover, the integration of cloud-based platforms has further elevated the accessibility and functionality of generative AI software, allowing for seamless collaboration and data management. This technological enhancement is anticipated to propel the growth trajectory of the software segment even further. The ease of integration with existing digital audio workstations (DAWs) and other music production software has also played a crucial role in its widespread adoption.

Investment in research and development activities continues to refine these software solutions, ensuring they remain at the forefront of the generative AI in music market. Future advancements are expected to focus on increasing the emotional intelligence of AI compositions and enhancing user interfaces to accommodate a wider range of creative expressions.

By Type Analysis

By Type, Generative Adversarial Networks (GANs) lead, driven by advancements in deep learning and artificial intelligence technologies.

In 2023, Generative Adversarial Networks (GANs) held a dominant market position in the "By Type" segment of the Generative AI in Music Market, outperforming AR-CNNs and Transformer-based models. This leadership can be attributed to the unique architecture of GANs, which effectively enables the creation of highly original and diverse musical content. GANs operate by using two neural networks that contest with each other to generate new data instances that are indistinguishable from real data, providing a powerful tool for creating complex musical compositions that resonate with human emotions and preferences.

The strength of GANs in the music industry lies in their ability to continuously learn and improve, thereby generating outputs that are increasingly sophisticated and appealing. This capability has made them particularly popular among music producers and artists seeking innovative ways to develop unique sounds and compositions without the constraints of traditional music production techniques.

Additionally, the adaptability of GANs to various musical genres and their capacity to handle different aspects of music sector creation, from melody generation to rhythm and harmony, contribute to their widespread adoption. The robustness of GANs in processing and producing high-quality audio has further solidified their position as a market leader.

Despite the strong position of GANs segment, AR-CNNs, and Transformer-based models also play significant roles in the market, with each offering specific advantages in speed and efficiency of learning patterns. However, for the year 2023, GANs have been the primary choice for professionals seeking cutting-edge tools to push the boundaries of musical creativity. Future developments are expected to enhance their efficiency and user-friendliness, potentially increasing their market share even further.

By Application Analysis

By Application, Music Mastering emerges as the predominant use, benefiting from automated precision and advanced sound engineering tools.

Music Mastering held the highest market position among Generative AI Music Market applications by Application in 2023, surpassing Composition of Music, Streaming Music, Making New Sounds, and Other Applications. This success can be attributed to its essential role in music production processes where mastering enhances sound quality while maintaining consistency across playback systems. Generative AI technologies revolutionized this segment allowing unprecedented precision and efficiency for mastering.

Generative AI in music mastering provides artists and producers with sophisticated tools that automate and refine the mastering process, which traditionally requires highly specialized skills. These AI-driven solutions can analyze and optimize sound dynamics and spectral balance, catering to the nuanced demands of different music genres and production styles. The ability to rapidly process tracks with consistent high-quality results has made AI-powered mastering increasingly popular among music professionals.

This technology not only speeds up the production timeline but also significantly reduces costs, making high-quality mastering accessible to a wider array of artists and smaller studios. With independent music production becoming more widespread and the democratization of creation tools driving its adoption, AI in music mastering is in high demand.

Music Mastering remains at the forefront of AI use in the music sector; however, other applications like Composing Music and Generating New Sounds also reap benefits from generative AI applications, creating a vibrant ecosystem in AI for music production. As technology develops further, AI integration should deepen further, further expanding creativity and productivity within this sector of industry.

Key Market Segments

By Component

• Software
• Services

By Type

• GANs
• AR-CNNs
• Transformer-based Models

By Application

• Music Mastering
• Composition of Music
• Streaming Music
• Making of New Sounds
• Other Applications

Growth Opportunity

Development of AI-Powered Music Composition Instruments for Automated Music Generation

In 2023, the development of AI-powered music composition instruments signifies a pivotal growth opportunity within the global generative AI in music market. These technological advancements are revolutionizing the industry by enabling the automation of complex musical compositions that can cater to diverse genres and styles. Such innovations not only streamline the creative process but also democratize music production, allowing both novice and experienced musicians to generate high-quality music with minimal effort.

This segment of the market is expected to see substantial growth, driven by continuous improvements in AI algorithms that enhance the quality and authenticity of generated music. As AI tools become more sophisticated and user-friendly, wider adoption is anticipated, particularly among independent artists and smaller music studios seeking cost-effective solutions to music production.

Increasing Applications in Music Composition, Mastering, Streaming, and Sound Generation

The expansion of generative AI applications across various domains of the music industry, including composition, mastering, streaming, and sound generation, presents significant growth prospects for 2023. AI technologies are being integrated into music streaming services to personalize user experiences and optimize music delivery, thereby attracting and retaining subscribers. Additionally, AI's role in mastering and sound generation is transforming traditional workflows, enabling faster production times and enhanced sound quality.

The capability of AI to adapt and learn from data also promises continuous improvement in these applications, which is likely to foster further innovation. Market growth in this area is expected to be fueled by the ongoing demand for more innovative and efficient music production technologies, which not only enhance artistic expression but also increase operational efficiencies for producers and artists alike.

Latest Trends

Growth of AI-generated music Streaming Playlists

In 2023, the generative AI music market is witnessing a significant trend towards the growth of AI-generated music streaming playlists. These playlists, curated by algorithms, are tailored to individual listener preferences, optimizing user engagement and satisfaction. This personalization is powered by AI's ability to analyze vast amounts of data on listening habits, enhancing the streaming experience.

As streaming services strive to differentiate themselves in a competitive market, AI-generated playlists are becoming a key feature. This trend not only attracts new subscribers but also retains existing ones by continuously adapting to their changing musical tastes. The integration of generative AI into streaming services is expected to drive substantial market growth as it aligns with the increasing demand for personalized content.

AI-Generated Background Music for Various Applications

Another emerging trend in the generative AI music market is the use of AI to create background music for various applications, such as video games, virtual reality environments, and public spaces. This application of AI in music production addresses the growing demand for immersive and customized audio experiences.

AI's capability to generate music that adapts to the dynamics of a game or an environment enhances the overall user experience. Furthermore, businesses are leveraging AI-generated music to enhance their brand identity and customer experience in commercial spaces. This trend is expanding the market reach of generative AI music beyond traditional music listening, presenting new opportunities for growth in diverse sectors.

Regional Analysis

In 2023, North America holds a 32% share of the global generative AI in music market.

The global Generative AI in Music Market is segmented into several key regions: North America, Europe, Asia Pacific, Middle East & Africa, and Latin America, each exhibiting distinct growth dynamics.

North America, dominating the market with a 32% share, is at the forefront due to its advanced technological infrastructure and the presence of major tech firms investing heavily in AI. The region's robust music industry, combined with high consumer readiness for AI-driven music platforms, fuels its leading position.

Europe follows closely, driven by strong governmental support for AI technologies and a vibrant cultural landscape that is increasingly embracing AI in music production. The region benefits from numerous startups and collaborations between tech music companies and music studios, aiming to innovate the user experience in music consumption and production.

The Asia Pacific region is witnessing rapid growth, attributed to the expanding digitalization and increasing adoption of streaming services among its large, tech-savvy youth population. Countries like China, Japan, and South Korea are leading in AI music technology, leveraging their strong positions in both technology and entertainment sectors.

Middle East & Africa, though smaller in comparison, is experiencing growth due to the digital transformation initiatives and the increasing penetration of internet and smartphone usage. This region shows potential for significant growth as local companies begin to explore generative AI applications in music.

Latin America, while still nascent, is seeing a rise in AI music adoption, driven by its growing tech startup ecosystem and cultural richness that embraces technological advancements in music.

Key Regions and Countries

North America

• The US
• Canada
• Rest of North America

Europe

• Germany
• France
• The UK
• Spain
• Netherlands
• Russia
• Italy
• Rest of Europe

Asia-Pacific

• China
• Japan
• Singapore
• Thailand
• South Korea
• Vietnam
• India
• New Zealand
• Rest of Asia Pacific

Latin America

• Mexico
• Brazil
• Rest of Latin America

Middle East & Africa

• Saudi Arabia
• South Africa
• UAE
• Rest of Middle East & Africa

Key Players Analysis

In 2023, the global Generative AI in Music Market will feature a dynamic landscape with several key players making significant contributions. Among these, Shutterstock Inc., primarily known for its vast repository of stock images and videos, has strategically extended its offerings to include AI-generated music, capitalizing on its existing digital asset management infrastructure to serve a broader range of creative needs.

Aiva Technologies SARL stands out for its AI-driven platform that composes emotional soundtrack music, which is particularly appealing to game developers and filmmakers looking to enhance the auditory experience of their productions without the extensive cost typically associated with original compositions.

Soundful, another significant player, focuses on providing AI-powered tools for music creation that cater to content creators across social media platforms, thereby addressing the rising demand for quick and cost-effective production of music tracks tailored to short-form video content.

Ecrett Music has carved a niche by offering AI-generated music specifically designed for videos, enabling users with minimal musical knowledge to create high-quality background scores that elevate their video content's professional appeal.

Boomy Corporation emphasizes user-friendly music creation, allowing individuals to generate and publish songs rapidly, thereby democratizing music production and distribution for amateur musicians and enthusiasts alike.

OpenAI, through its advanced AI research and development, has been pivotal in pushing the boundaries of what AI can achieve in creative domains, including music, setting high standards for innovation and quality in AI-generated music.

Amadeus Code is noted for its AI software that assists songwriters by offering melodic inspiration, thereby enhancing creativity through technology.

Market Key Players

• Shutterstock Inc.
• Aiva Technologies SARL.
• Soundful
• Ecrett music
• Boomy Corporation
• OpenAI
• Amadeus Code
• Other Key Players

Recent Development

• In March 2024, Universal Music Group pioneers artist-centric AI use and secures double royalties with Deezer. Challenges TikTok on fair compensation. Partners with Ntwrk for artist-fan experiences.
• In February 2024, The Indiana University Jacobs School of Music will host the "AlgoRhythms: The World of Music and AI" summit, exploring AI's impact on music creation and ownership.
• In January 2024, The Recording Industry Association of America (RIAA) advocates for responsible AI policies, emphasizing consent and compensation for creators. Transparency and authenticity are essential for AI development.

Report Scope