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Artificial Intelligence (AI) in Music Market - Forecasts from 2024 to 2029

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    Report

  • 138 Pages
  • October 2024
  • Region: Global
  • Knowledge Sourcing Intelligence LLP
  • ID: 6014289
Artificial intelligence (AI) in music market is expected to grow at a CAGR of 16.28%, reaching a market size of US$3.201 billion in 2029 from US$1.489 billion in 2024.

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 listen 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.

Artificial Intelligence (AI) in Music Market Drivers:

  • Advancement in AI software and technology is 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.

Artificial Intelligence (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.

Reasons for buying this report::

  • Insightful Analysis: Gain detailed market insights covering major as well as emerging geographical regions, focusing on customer segments, government policies and socio-economic factors, consumer preferences, industry verticals, other sub- segments.
  • Competitive Landscape: Understand the strategic maneuvers employed by key players globally to understand possible market penetration with the correct strategy.
  • Market Drivers & Future Trends: Explore the dynamic factors and pivotal market trends and how they will shape up future market developments.
  • Actionable Recommendations: Utilize the insights to exercise strategic decision to uncover new business streams and revenues in a dynamic environment.
  • Caters to a Wide Audience: Beneficial and cost-effective for startups, research institutions, consultants, SMEs, and large enterprises.

What do businesses use our reports for?

Industry and Market Insights, Opportunity Assessment, Product Demand Forecasting, Market Entry Strategy, Geographical Expansion, Capital Investment Decisions, Regulatory Framework & Implications, New Product Development, Competitive Intelligence

Report Coverage:

  • Historical data & forecasts from 2022 to 2029
  • Growth Opportunities, Challenges, Supply Chain Outlook, Regulatory Framework, Customer Behaviour, and Trend Analysis
  • Competitive Positioning, Strategies, and Market Share Analysis
  • Revenue Growth and Forecast Assessment of segments and regions including countries
  • Company Profiling (Strategies, Products, Financial Information, and Key Developments among others)

The Artificial Intelligence (AI) in music market is segmented and analyzed as follows:

  • 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

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

Companies Mentioned

Some of the key companies profiled in this Artificial Intelligence (AI) in Music Market report include:
  • iZotope
  • Aiva Technologies
  • Amper Music (Shutterstock Inc)
  • BRAINFM Inc
  • LANDR
  • Boomy Corporation
  • Magenta (Google Inc)
  • SOUNDRAW Inc
  • Amadeus Code
  • Klangio GmbH

Methodology

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Table Information