Scope and Participant Profile
Between March and July 2026, MESAM partnered with Pro Creative with support from the Ministry of Culture and Tourism to survey 1,170 music professionals. The study combined quantitative and qualitative methods to measure AI usage in creative production, expectations about copyright, economic effects, and policy needs. Most respondents were 45 or older with 15–20+ years of professional experience, which strengthens the practical relevance of the findings.
How Frequently Professionals Use AI
Fifty-five percent of respondents reported using AI tools regularly or intermittently, while 44.2% had not used them. Uses range from demo creation to arrangement, mixing, and mastering; demo production was the most common because AI significantly reduces time and cost. Concrete examples include independent artists producing multiple demos in a month that previously would have taken weeks and higher studio budgets.
Does AI Support or Threaten Creativity?
Forty-six-point-two percent of participants said AI can support creativity; 42.2% warned it poses risks. The difference depends on context and tool design. Supportive tools—harmony suggestions, beat programming, and arrangement assistants—act as catalysts, producing idea variations that musicians refine. End-to-end generative models that create complete compositions can erode perceptions of originality for some creators. Field evidence shows musicians typically keep final aesthetic and emotional choices, using AI for ideation rather than authorship.
Copyright Expectations and Policy Requests
Seventy-four-point-one percent of professionals mandatory demand labeling of AI-generated tracks; 84.6% want MESAM and similar societies to take an active policy role. Respondents argued platforms and AI companies should transparently report data sources and pay rights holders when trained on copyrighted works. At board level, representatives emphasized that AI usually synthesizes existing works and therefore should compensate original creators.
Legal Status Today and Anticipated Changes
Participants indicated that AI-generated works currently lack clear international copyright status. From MESAM’s standpoint, AI-only outputs do not qualify as “works” under existing Turkish frameworks; members can claim lyric rights when lyrics are theirs, but melody/composition rights remain unresolved until international norms settle. This legal uncertainty drives demand for extended responsible licensing and mandatory labeling practices.
Economic Effects: Costs, Revenue and Market Dynamics
AI reduces demo production costs markedly. Traditional demo production can exceed 30,000 TRY, while AI-assisted workflows cut those costs and timelines, enabling more creators to enter the market. That increased supply shifts revenue dynamics: more releases can dilute per-release income unless licensing, royalty distribution and professional service pricing adapt. Example scenario: an independent artist releases ten AI-assisted demos a year; without fair licensing mechanisms, rights holders could lose predictable income streams despite higher output.
Policy Recommendations and Practical Solutions
The study offers actionable proposals: mandatory AI-content labeling; responsible, extended licensing where AI providers document training data and compensate rights holders; active roles for collecting societies acting as mediators and license pool managers; and educational programs for rights holders on AI tools and copyright. Implementing these steps short-term reduces uncertainty; medium-term, they help build sustainable revenue flows.
Step-by-Step Roadmap for Rights Holders and AI Companies
1) Require transparent data declarations: AI developers must publish training-dataset provenance and licensing status. 2) Implement mandatory labeling: streaming and distribution platforms should add metadata flags indicating AI contribution. 3) Create licensing pools: societies like MESAM should design collective licensing schemes to collect and distribute royalties from AI-generated uses. 4) Establish standard fee templates for demo and post-demo services to protect professionals’ income. 5) Run joint trainings: producers and developers attend shared workshops on ethical AI use and copyright compliance.
International Comparisons and Turkey’s Position
Turkey occupies a middle ground: it adopts technology while expressing legal and ethical concerns. That position allows policymakers to adapt European and Latin American practices—such as mandatory labeling and provenance requirements—into localized models. Comparative examples suggest labeling plus licensing pools achieve both transparency and enforceable compensation across jurisdictions.
Outcomes, Risks, and Expected Developments
The central trends are increasing AI adoption, mixed creative impacts, strong demands for transparency, and the need for new licensing models. Short term, expect regulatory moves on mandatory labeling and reporting; medium term, anticipate extended licensing frameworks managed by collecting societies. Risks include erosion of professional income if licensing does not adapt and public confusion over authority without clear labeling.
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