Organized by the Berklee Emerging Artistic Technology Lab (BEATL), the inaugural AI Music Summit (AIMS) at Berklee College of Music ran June 3-5 in Boston, drawing hundreds of engineers, educators, executives, lawyers, researchers, producers, and musicians. Outside the venue, a rotating group of students protested peacefully, highlighting the tension between technological advancement and creator rights.
Student Protest Outside the Venue
Throughout the three-day event, students stationed themselves outside the Richard Ortner Studio Building, playing music, distributing brochures, and engaging attendees in conversation. The peaceful demonstration was part of a broader backlash against the college’s approach to AI.
“There are a lot of people here who are at the top level of the AI music industry, and they’re deciding it for the rest of us,” said Theo Wheeler, a Berklee student majoring in contemporary writing and production.
AI as an Umbrella Term
Music lawyer Elizabeth Moody opened her presentation, “The Future of Music & AI: Deals, Data, and Creator Value,” by asking whether the industry has a branding problem. She noted that discussions often conflate music production tools, generative songwriting software, and voice cloning technology.
Summit sessions highlighted that AI encompasses assistive, generative, and agentic applications across production, songwriting, remixing, recommendation systems, marketing, and royalty calculations. A panel featuring the CEOs of Audioshake, AutoTune, Image-Line, LANDR, and Universal Audio stressed that AI should solve specific problems rather than be deployed for its own sake.
Even within generative AI, approaches differ sharply. Companies like Suno train models on unlicensed music, while ElevenLabs says it uses only recordings with permission. Suno’s “open studio” model allows users to download and distribute AI-generated tracks, whereas upcoming platforms such as Udio‘s Starstruck app and Spotify‘s AI remix tool propose a “walled garden” where user-generated content cannot be exported.
Generative AI: Continuity or Rupture?
Speakers frequently compared generative AI to past disruptions: the player piano, phonograph, MIDI, sampling, peer-to-peer file sharing, and streaming. Each sparked industry revolt, legal battles, and fears over livelihoods before becoming normalized.
However, presenters cautioned that framing generative AI as just another technological shift risks overlooking its unprecedented scale. A recent study by Deezer found that nearly 75,000 fully AI-generated tracks are uploaded to the platform daily, accounting for 1-3% of overall streams, many of which are detected as fraudulent. Other streaming services, including Spotify, are similarly contending with a flood of AI-generated content.
The Need for Precision
Several speakers argued that collapsing all AI tools into a single category weakens both criticism and advocacy. Lumping a noise-removal plugin for a digital audio workstation (DAW) with fully AI-generated music dilutes arguments and distracts from underlying issues, they said.
Legal and Policy Gaps
Technology often moves faster than the legal, policy, and business infrastructure, as evident from lengthy lawsuits and ongoing concerns about Name, Image, and Likeness (NIL) protections. The summit underscored that regulatory frameworks are still catching up to the rapid deployment of generative AI in music.
