Adoption of AI Technology in the Music Mixing Workflow: An Investigation
It addresses the problem of designing effective AI tools for different user groups in the music industry, but it is incremental as it focuses on adoption strategies rather than novel technical solutions.
This study investigated the adoption of AI technology in music mixing workflows, finding that AI tools simplify processes for amateurs but pro-ams and professionals require more control and customization.
The integration of artificial intelligence (AI) technology in the music industry is driving a significant change in the way music is being composed, produced and mixed. This study investigates the current state of AI in the mixing workflows and its adoption by different user groups. Through semi-structured interviews, a questionnaire-based study, and analyzing web forums, the study confirms three user groups comprising amateurs, pro-ams, and professionals. Our findings show that while AI mixing tools can simplify the process and provide decent results for amateurs, pro-ams seek precise control and customization options, while professionals desire control and customization options in addition to assistive and collaborative technologies. The study provides strategies for designing effective AI mixing tools for different user groups and outlines future directions.