Inside SXSW 2026: Producers and Tech Leaders Debate the Future of AI in Music

At SXSW 2026, a standing room only crowd gathered for a panel that reflected one of the most urgent conversations shaping today’s music industry: how artificial intelligence is being built, used and monetized. The session, titled Ethical and Unethical AI in Music, brought together producer voices and tech leaders, including Kato On The Track, KXVI, BeatStars chief technology officer Michael "MJ" Jacob and Neutune chief industry and rights officer Virginie Berger.

Across the discussion, they moved between creative workflows and legal concerns, outlining how quickly the ground is shifting for producers. While AI tools continue to evolve, the panel returned repeatedly to a central issue around ownership, attribution and compensation. The conversation made clear that the technology is not arriving in the future, but is already reshaping how music is made and distributed.

Berger opened the session by reframing what ethical AI means in the current moment. She explained that the conversation has moved beyond theory into practical concerns tied to training data, licensing structures and financial distribution. According to Berger, the industry is still operating without a clear framework, even as AI generated music becomes more visible across streaming platforms. She pointed to recent platform level changes, including labeling systems and transparency tags, while noting that there is still no universal standard. As a result, artists and companies are navigating a system that is still being defined in real time. That uncertainty has created both opportunity and tension across the music ecosystem.

Kato On The Track approached the topic from a producer’s perspective, grounding the conversation in how music has always evolved through influence. He reflected on studying producers like Dr. Dre and J Dilla early in his career, explaining that imitation has historically been part of developing a sound. In that context, he said he does not focus on AI replication unless it becomes a direct copy. Kato emphasized that borrowing ideas is already embedded in music culture, making it difficult to draw a strict boundary. His perspective positioned AI as an extension of an existing creative pattern, while still acknowledging that the scale of replication has changed.

KXVI expanded on that distinction by focusing on process. He described how artists spend years refining their sound through repetition, experimentation and lived experience, while AI systems generate outputs based on data inputs without that same development. For him, the concern is not simply that AI can replicate a sound, but how that replication is used in the market.

If a track built from elements of his work performs commercially, he said there should be clear attribution and compensation. That focus on monetization framed much of the conversation that followed, especially as panelists began to examine how companies are building and deploying these tools.

Tools, Competition and Creative Control

As the panel shifted toward real world usage, both Kato and KXVI described how AI tools are already part of their workflows. Kato detailed his experience using platforms like Suno, explaining that he treats AI as a creative assistant rather than a replacement. He described inputting his own production and using AI to generate variations, then selecting elements that align with his intended sound. The process, he said, still relies on human decision making at every stage. For Kato, the tool becomes valuable when it is used with intention and taste, rather than as a shortcut.

KXVI described a similar workflow, noting that AI generated outputs often require additional refinement before they are usable in a professional setting. He explained that while the technology can produce ideas quickly, producers are still responsible for shaping those ideas into complete records. That level of curation remains a defining skill, separating experienced producers from casual users. He also pointed out that many AI generated tracks still carry subtle imperfections that signal how they were made. Those details reinforce the continued importance of human involvement in the production process.

Both producers also addressed the risks associated with overusing AI tools. KXVI shared that after experimenting with AI, he became cautious about relying on it too heavily. He explained that maintaining a distinct identity is essential, particularly for producers who have already built an audience. Kato added that while access to music creation tools has expanded, the value in the market has not disappeared. Instead, it has shifted toward creativity, collaboration and the ability to stand out. As more people gain access to production tools, differentiation becomes a more important factor than technical skill alone.

The panel also explored how listeners engage with music in an AI driven environment. KXVI noted that audiences still connect more deeply with human artists, even when AI can replicate a similar sound. He suggested that identity and storytelling will continue to play a major role in how music is consumed. That shift places additional importance on branding and presence, particularly for producers who are traditionally less visible. In this context, AI does not remove the need for artists, but changes how they position themselves within the industry.

Ownership, Ethics and Industry Response

Michael "MJ" Jacob provided insight into how companies like BeatStars and Lemonade AI are approaching these challenges. He described the current landscape as a moment where some companies are building AI systems using music without consent, then competing directly with the same artists whose work was used. In response, he said the goal is to create an ecosystem where artists are compensated and involved in the process. That includes working directly with producers to license their data and develop AI models tied to their individual sound.

Jacob emphasized that ethical AI begins with transparency. If a company does not know exactly what data was used to train a model, he said it becomes impossible to fairly attribute or compensate contributors. He compared the process to building a product from specific ingredients, where each element plays a role in the final result. By working directly with artists and using detailed source material, he argued that companies can produce higher quality outputs while maintaining accountability. This approach stands in contrast to platforms that rely on large scale data scraping without permission.

Kato responded by raising questions about whether ethical AI models can compete with existing tools that have already been trained on massive datasets. He acknowledged that some of those tools produce strong results, even if their methods are disputed. However, he noted that competition in the market will ultimately determine which approach becomes sustainable. If ethical platforms can match or exceed the quality of current tools while compensating artists, he said producers will have an incentive to support them.

The topic of consent remained central throughout the discussion. Both Kato and KXVI said they would consider allowing their music to be used for AI training under the right conditions. Those conditions include clear agreements, fair compensation and transparency around usage. Kato shared that Suno had previously approached him about a partnership, but he chose not to move forward after reviewing the terms. His decision highlighted the level of scrutiny producers are applying as these opportunities emerge.

Berger added a broader industry perspective, pointing to regulatory efforts aimed at requiring companies to disclose their training data. She noted that regions like Europe are beginning to introduce policies designed to increase transparency. However, she also acknowledged that regulation is still developing and often lags behind the pace of technology. In the absence of clear rules, artists are left to navigate these decisions independently.

Audience questions brought additional focus to attribution, with one attendee asking whether AI systems could identify specific source material within generated tracks. Jacob explained that while the technology may exist, companies have little financial incentive to implement it. If attribution becomes standard, it would require platforms to share revenue with original creators. That reality highlights the tension between maximizing profit and maintaining fairness within the system.

Throughout the session, one idea remained consistent across both producers and executives. AI is not being rejected outright, but its role in music depends on how it is developed and who benefits from it. For Kato and KXVI, the priority remains protecting creative identity while adapting to new tools. For companies like BeatStars and Lemonade AI, the focus is building systems that include artists rather than replace them. As AI continues to expand across the industry, those decisions are shaping how music will be created, credited and valued moving forward.