I’m trying to understand how people are adapting to the new AI music landscape, especially around Spotify, Deezer, TikTok/SoundOn, DistroKid, and platform detection. A few things I keep seeing discussed: 1. AI music may be getting separated from human artists. Some platforms seem to be moving toward stronger AI tagging, reduced algorithmic support, or different credibility signals for real-world artists. 2. AI disclosure may become unavoidable. Distributors are already asking about AI-generated music, vocals, and lyrics. I’m wondering how people here are handling that honestly without hurting reach. 3. Raw Suno/Udio exports may be risky long-term. Are people still uploading raw exports, or are you now post-processing, stem-splitting, remixing, adding real vocals/instruments, or running tracks through a DAW first? 4. Upload behavior may matter as much as the audio. Bulk uploads, similar track lengths, repetitive metadata, and generic artist personas could potentially look spammy to platforms. 5. Artist positioning may need to change. Instead of pretending an AI project is a traditional band, is it better to position yourself as a producer, curator, composer, or creative director using AI tools? What I’m looking for is practical field advice: - Are you disclosing AI usage on DistroKid or other distributors? - Are you changing your mixing/mastering workflow before release? - Are you spacing out uploads differently? - Are you avoiding certain keywords or artist positioning? - Have you seen any real evidence of deranking, takedowns, reduced reach, or royalty issues? I’m not looking for theory or fearmongering. I want to know what is actually working right now from people releasing AI music in the real market. How are you adapting your workflow?