Fender CEO Edward “Bud” Cole’s remarks on artificial intelligence and music, made during a May interview with T3 to commemorate the Telecaster’s 75th anniversary, have recently garnered significant attention. These comments are now intensifying an existing wave of negative public relations for the company, which previously drew widespread criticism from the guitar community after issuing cease-and-desist letters to independent builders, asserting copyright over the Stratocaster body shape.
The controversy has prompted several prominent guitar YouTubers to declare an end to their purchases of Fender equipment. Furthermore, Cole’s recently resurfaced statements, which liken learning cover songs and collaborating with bandmates to a form of “analog AI,” have further eroded the company’s reputation among its most vocal online admirers.
While T3 editor-in-chief Mat Gallagher’s feature primarily paraphrased Cole’s remarks, and Fender did not immediately provide a comment or clarification, the key excerpts from the interview are presented below:
Cole’s core philosophy suggests that AI’s presence in music is not a recent phenomenon. He stated, “I think AI has existed in music as long as there’s been recorded music.” He identifies the primary obstacle to playing guitar as the time commitment required for learning, but posits that AI plays a role in addressing the secondary challenge: songwriting.
Cole elaborated, “I actually believe cover music has been sort of analog AI for a long time.” He explained that aspiring musicians lacking the proficiency to compose original material can instead perform songs by their preferred artists. He personally recounted, “I listened a lot to REM, U2, The Smiths and The Cure, and at some point I got sick of just listening to them. I wanted to play it, so I learned to play guitar.”
For individuals embarking on their songwriting journey, Cole suggested a second “analog AI” in the form of bandmates. He described how an initial chorus or riff can be developed further by a drummer or bassist, leading to the creation of a complete song. He believes AI can similarly fulfill this function, stating, “I actually think that we are in the brink of freeing up people to move beyond the same old covers and to really get into working like they do with their bands.”
Cole’s comments aim to draw a parallel between a human learning a limited number of cover songs and an AI processing vast datasets of copyrighted musical works. His implication seems to be that the human process of mastering existing songs, internalizing their styles, and subsequently creating new material is fundamentally analogous to an AI’s operation. This perspective is widely considered misguided, suggesting either a lack of comprehension regarding AI technology or a disregard for artistic integrity.
A critical distinction lies in scale. No human could realistically learn the millions of songs reportedly used to train a typical generative AI model, such as Suno. Furthermore, this comparison overlooks the intrinsic human element embedded in the myriad of conscious and subconscious decisions an artist makes during songwriting. These artistic choices, whether motivated by emotional responses, serendipitous discoveries, or practical limitations, are inherently unique to the individual creator.
This process differs fundamentally from an AI model generating output based on a prompt and a network of data points. As Steve Onotera, known online as Samurai Guitarist, highlights, a musician’s unique physicality and the subtle imperfections inherent in human performance prevent an exact replication of another’s work. Such serendipitous elements cannot be reproduced by a large language model.
The argument extends to bandmates as well. Human collaborators, drawing upon their distinct “training data” of life experiences, physical abilities, and limitations, are not equivalent to a chatbot. An AI lacks the discerning taste or intuitive instincts of, for example, a bassist with a jazz composition background. To suggest a drummer is indistinguishable from an AI model would understandably be perceived as an insult.
Later in the interview, Cole expressed his conviction: “I believe that AI is actually going to help create a whole new world of guitar players that use it. To help connect with other musicians, to be more productive. And across the chasm into becoming a student of songwriting to a master of songwriting.”
Cole’s claim that AI will somehow enable individuals to “across the chasm” and become master songwriters is, quite frankly, met with skepticism. There is growing evidence suggesting that excessive reliance on AI tools can lead to deskilling. Utilizing AI for rhyme or metaphor suggestions for emotional expression is not equivalent to the deliberate practice and skill development essential for songwriting. An AI has no lived experience, such as personal heartbreak or the painstaking effort of perfecting a pre-chorus transition. Repetition is paramount; the common wisdom suggests writing hundreds, if not thousands, of less-than-perfect songs before achieving a truly good one. This iterative process is how artists transcend clichés and cultivate the discernment to recognize genuine creative breakthroughs.
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