Report Overview
The Global Artificial Intelligence (AI) in Music market is forecast to grow at a CAGR of 18.7%, reaching USD 4.0 billion in 2031 from USD 1.7 billion in 2026.
Highlights:
- 1Rapid Market ExpansionAI in music market grows due to advanced algorithms enhancing composition and personalization.
- 2Smartphone-Driven AccessibilityIncreasing smartphone use enables easy access to AI music apps, boosting creation.
- 3Streaming Personalization SurgeAI recommendation engines drive user retention via tailored music experiences on streaming platforms.
- 4Ethical Challenges PersistCopyright issues and a lack of human emotional nuance in AI-generated music hinder growth.
In music, AI implies that artificial intelligence software applications have been integrated with music to facilitate the process of composing, mixing, and personalizing tracks. The application of AI software in music production processes has enabled music producers and artists to create new sounds and tunes.
Some of the major players in the AI music market include Landr, Amper Music, Izotope, and Brain.fm, Shazam, Splash, and Aiva Technologies. As a result, many musicians are adopting AI software to change their music composition style and individual listening playlists on streaming services where they produce or perform their songs. In this way, numerous music software applications have been developed to increase international music market consumption and the range of products offered by musicians.
The use of state-of-the-art music production tools and smart streaming services powered by artificial intelligence is driving the rapid expansion of the musical business into a new frontier. Organizations are investing in AI so that they can develop advanced algorithms capable of creating new songs, creating personalized soundtracks, or aiding music education. Additionally, another factor that adds to this growth is the expanded use of AI technology in gadgets like smart speakers and mobile phones, allowing many people to easily access AI-infused music apps.
AI In Music Market Growth Drivers:
Advancement in AI software and technology are anticipated to increase the demand
Properties of AI software are widely used in many industries, including the music industry, due to continuous evolution and development. These developments have opened new avenues for music composition in the context of AI software. One such technique is "riffusion," which is creating music using AI computer vision rather than voice and sound recognition software. Riffusion is a technique that allows soundtracks to be created by utilizing the visual cues connected to different notes used in various musical genres. The expansion of AI in the music market is expected to be driven by major factors over the forecast period. These factors include increased research and development related to AI applications, leading to new music production methods, as well as the widespread increase in the consumption of music streaming services.
Increasing use of smartphones is anticipated to drive market growth
The development of generative AI in the music industry is propelled by increasing smartphone usage for the foreseeable future. This is because smartphones merge the functions of a mobile phone and a computer into one device, thus allowing users to receive personal emails, use their data storage, and access the internet. Their popularity can be attributed to various factors such as connectivity, flexibility, socio-cultural factors, affordable cost, and availability. As smartphones continue becoming ubiquitous globally, millions more generate music from Generative AI-enabled platforms and applications due to their commonplace nature. These applications enable people to write songs, remix, and produce music on their phones, eliminating the need to purchase expensive studio instruments or specialized software.
Increasing demand for music streaming recommendations is augmenting the market growth
AI has taken the lead in the music industry for streaming recommendations as it can keep up with consumers' growing demand for personalized music experiences. In an era where digitized music platforms are skyrocketing, the overwhelming volume of songs, albums, and playlists can be daunting for users trying to discover their preferred music. AI giants have established recommendation engines that utilize user-related data to create personalized music for listeners to tackle this issue.
Thus, these systems can grow user retention levels through novel content that best suits their choices, all based on the information they have collected about them before. Furthermore, with the commitment received from users, including feedback on what should be played next or who else to follow, there will always be an improvement in these algorithms’ accuracy and relevance.
AI In Music Market Restraints:
The probability of ethical risks is anticipated to impede market growth
The applications of AI software and machine learning models in music composition and customization processes require a pre-recorded dataset for the application to understand the music composition procedures and produce new music. However, copyright and ethical issues are associated with using music tracks and records for such purposes. In addition, there is also a possibility of partial and mixed plagiarism in applying AI-powered tools in music production. These limitations could be mitigated by further research and development of better-performing AI music applications and software.
Moreover, AI technology can produce technically complex and precise music, but it often lacks the human touch and emotional nuance found in music composed and performed by humans. The crux of this issue lies in the difficulty of emulating the intricate expressions, subtle nuances, and quirks that give music its significance and authenticity.
AI In Music Market Geographical Outlook:
Asia Pacific is witnessing exponential growth during the forecast period
Asia Pacific is experiencing significant growth in their media and entertainment industry and is witnessing high levels of music consumption across consumers and other media platforms. This has driven the demand for more efficient and effective AI solutions for the music industry. This, in turn, has spurred investment in various AI applications that can be employed across various activities in the music industry. For instance, an AI-assisted music technology software, Beatoven.ai, is provided in India, which helps generate original music scores for various YouTube channels, wedding videography firms, and marketing agencies. In addition to this, the music industries of South Korea, Japan, China, and India are expanding rapidly.
AI In Music Market Key Developments:
June 2026: Modulate launched its AI Music Detection API on June 24, 2026, enabling streaming platforms, distributors, and rights holders to identify AI-generated vocals and instrumentals for improved content transparency and rights management.
March 2026: BandM8 debuted its music-to-music AI creative platform at NVIDIA GTC 2026 on March 18, 2026, allowing musicians to transform performances into fully editable AI-generated musical arrangements using ethically sourced training data.
January 2026: Deezer announced on January 29, 2026 that it commercialized its AI music detection technology after identifying over 13.4 million AI-generated tracks in 2025, strengthening transparency and fraud prevention across music streaming.
List of Top AI In Music Companies:
iZotope
Aiva Technologies
Amper Music (Shutterstock Inc)
BRAINFM Inc
LANDR
Artificial Intelligence (AI) In Music Market Scope
| Report Metric | Details |
|---|---|
| Total Market Size in 2026 | USD 1.7 billion |
| Total Market Size in 2031 | USD 4.0 billion |
| Forecast Unit | Billion |
| Growth Rate | 18.7% |
| Study Period | 2021 to 2031 |
| Historical Data | 2021 to 2024 |
| Base Year | 2025 |
| Forecast Period | 2026 – 2031 |
| Segmentation | Application, Geography |
| Geographical Segmentation | North America, South America, Europe, Middle East and Africa, Asia Pacific |
| Companies |
|
Market Segmentation
By Application
- Personalization
- Music Composition
- Audio Mixing
By Geography
- North America
- USA
- Canada
- Mexico
- South America
- Brazil
- Argentina
- Others
- Europe
- United Kingdom
- Germany
- France
- Italy
- Spain
- Others
- Middle East and Africa
- Saudi Arabia
- UAE
- Others
- Asia Pacific
- China
- Japan
- India
- South Korea
- Australia
- Singapore
- Indonesia
- Others
Geographical Segmentation
North America, South America, Europe, Middle East and Africa, Asia Pacific
Table of Contents
1. INTRODUCTION
1.1. Market Overview
1.2. Market Definition
1.3. Scope of the Study
1.4. Market Segmentation
1.5. Currency
1.6. Assumptions
1.7. Base and Forecast Years Timeline
1.8. Key Benefits to the Stakeholder
2. RESEARCH METHODOLOGY
2.1. Research Design
2.2. Research Processes
3. EXECUTIVE SUMMARY
3.1. Key Findings
3.2. CXO Perspective
4. MARKET DYNAMICS
4.1. Market Drivers
4.2. Market Restraints
4.3. Porter’s Five Forces Analysis
4.3.1. Bargaining Power of Suppliers
4.3.2. Bargaining Power of Buyers
4.3.3. Threat of New Entrants
4.3.4. Threat of Substitutes
4.3.5. Competitive Rivalry in the Industry
4.4. Industry Value Chain Analysis
4.5. Analyst View
5. ARTIFICIAL INTELLIGENCE (AI) IN MUSIC MARKET BY APPLICATION
5.1. Introduction
5.2. Personalization
5.3. Music Composition
5.4. Audio Mixing
6. ARTIFICIAL INTELLIGENCE (AI) IN MUSIC MARKET BY GEOGRAPHY
6.1. Introduction
6.2. North America
6.2.1. By Application
6.2.2. By Country
6.2.2.1. USA
6.2.2.2. Canada
6.2.2.3. Mexico
6.3. South America
6.3.1. By Application
6.3.2. By Country
6.3.2.1. Brazil
6.3.2.2. Argentina
6.3.2.3. Others
6.4. Europe
6.4.1. By Application
6.4.2. By Country
6.4.2.1. United Kingdom
6.4.2.2. Germany
6.4.2.3. France
6.4.2.4. Italy
6.4.2.5. Spain
6.4.2.6. Others
6.5. Middle East and Africa
6.5.1. By Application
6.5.2. By Country
6.5.2.1. Saudi Arabia
6.5.2.2. UAE
6.5.2.3. Others
6.6. Asia Pacific
6.6.1. By Application
6.6.2. By Country
6.6.2.1. China
6.6.2.2. Japan
6.6.2.3. India
6.6.2.4. South Korea
6.6.2.5. Australia
6.6.2.6. Singapore
6.6.2.7. Indonesia
6.6.2.8. Others
7. COMPETITIVE ENVIRONMENT AND ANALYSIS
7.1. Major Players and Strategy Analysis
7.2. Market Share Analysis
7.3. Mergers, Acquisitions, Agreements, and Collaborations
7.4. Competitive Dashboard
8. COMPANY PROFILES
8.1. iZotope
8.2. Aiva Technologies
8.3. Amper Music (Shutterstock Inc)
8.4. BRAINFM Inc
8.5. LANDR
8.6. Boomy Corporation
8.7. Magenta (Google Inc)
8.8. SOUNDRAW Inc
8.9. Amadeus Code
8.10. Klangio GmbH
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