AI in – Misryoum examines how AI is reshaping music economics, ownership, and live-work value, and why rules for consent and payment matter now.
AI can write a song in minutes, but the bigger question for the music economy is whether it can help build careers.
In Misryoum’s view. the focus keyphrase is “AI in music. ” and the real disruption isn’t the ability to generate melodies.. It is the pressure it puts on an industry already running on thin margins. where streaming payouts are small and algorithms strongly influence what audiences see.. As machine-made content becomes easier to produce and spread. the systems that determine visibility. credit. and revenue face a tougher test than ever.
This matters because music is not just content; it is a business model built on relationships, rights, and measurable performance. When those signals get distorted, creators can lose leverage even if new music keeps flowing.
Meanwhile. Misryoum highlights a potential upside: for early-career artists. AI tools can lower startup costs and reduce the friction of doing the basics. from marketing materials to early production ideas.. In practice, that can make the entry point less dependent on large teams or label infrastructure.. But the promise of easier creation only holds if the rules around ownership, consent, and compensation keep pace.
The risk is that automation could move faster than accountability.. If AI platforms and distributors cannot reliably distinguish human-made from machine-generated work. it becomes harder to apply existing royalty logic or to understand what “credit” really means.. Misryoum also notes concerns about training data and output rights. since questions around who provided the inputs and who receives payment can become more difficult as models scale.
Insight: Even small shifts in attribution and payment can ripple through signing, booking, and funding decisions, which are already tightly connected to stream-based metrics.
Beyond recording and publishing, the music business depends on far more than the final track.. Misryoum points to the broader ecosystem of work around live events and production. where roles such as engineers. stage and venue staff. and tour operations translate creative output into real-world experiences.. AI may speed up certain creative steps. but it cannot replace the operational and human intensity of live music. including the logistics and teamwork required to deliver shows.
In this context. Misryoum argues that audiences appear to keep valuing what digital tools cannot fully replicate: connection. atmosphere. and community built over time.. As AI-generated music becomes more polished. the market signal may be that people are still willing to pay for the unpredictability and shared energy of a performance.
Insight: The next competitive advantage may belong to whoever strengthens the “human systems” around music, not just whoever produces the most content.
Misryoum concludes that the industry’s response should be about governance and guardrails, not reaction.. That includes clear rules around authorship and consent. workforce development for roles that could be disrupted. and tools designed to empower creators rather than extract from them.. The goal. as Misryoum frames it. is not to block AI from music. but to ensure it expands opportunities for artists instead of weakening the economic foundations that make long-term careers possible.