MANAGEMENT STRATEGIES FOR AI-BASED MUSIC STARTUPS
DOI:
https://doi.org/10.29121/shodhkosh.v6.i2s.2025.6693Keywords:
AI-Based Startup Music, Management, Music Technology, Generative Composition, Machine Learning, Management of Innovation, Creative Industries, IP, Ethical AI, Digital Entrepreneurship, Music AnalyticsAbstract [English]
The music industry, has been transformed by the introduction of new startups due to the advent of the Artificial Intelligence (AI) where machine learning, deep learning, and natural language processing are used to redefine the music creation, production, and distribution. The paper will discuss the management practices which may be utilized in the success of AI-based music startups such as the organizational models, innovation models and the mechanisms of sustainable growth. Applications of AI to music have touched various themes such as generative music composition, machine learning-based playlist optimization, machine mastering, machine-generated music and emotion-based playlists, and audience analytics. These startups are difficult to administer as they will require a mediating zone between the invention of technology and aesthetic arts and be necessitated by inter-disciplinary management, which will incorporate the engineering precision and aesthetic sense. The strategic aspects found to be agile development cycles, ethical data governance, intellectual property management and collaboration with artists and technologists. The paper is devoted to the dynamic business strategies, such as the so-called AI-as-a-Service (AIaaS) and subscription-based models which can be scaled and made to maintain the relationships with customers. Similarly, strategic cooperation with record labels, streaming applications as well as independent artists are crucial agents of market entry. Acquiring talent strategies should give priority to hybrid skills with data science, good engineering and music theory to be able to maintain product relevance and continuity of innovation. Issues like data bias, ambiguity in copyright and creative ownership are resolved by transparent algorithm design and management practices which are stakeholder-centric. The conclusion of the paper is that effective AI-driven music startups are built on a dynamic leadership, cross-domain partnership, and constant ethical review of AI work. With creative innovation and sustainability of business, these startups can transform the entire music ecosystem across the world, enabling a more personalized, intelligent, and inclusive future of music creation and consumption.
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Copyright (c) 2025 Mohit Malik, Dr. Vaishali Vivek Patil, Dr. Pallavi M, Lalit Khanna, Dr. Vandana Gupta, Sanjay Bhatnagar
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