By Michael-Patrick Moroney

Every creative field is heading toward the same reckoning. Writers, filmmakers, designers, podcasters - anyone who works with words, images, or sound will soon face what musicians are confronting now: the moment when machines can churn out convincing work at scale. I focus on music because it’s my world. As a composer and producer, I’ve seen how quickly the ground shifts. By 2030, the change will be impossible to ignore.

Today, in 2025, the business looks strong. Recorded-music revenues have climbed above $29 billion, subscriptions to streaming services are past three-quarters of a billion, and growth is surging in Africa, Latin America, and the Middle East. Vinyl still spins in surprising numbers. Yet behind these statistics lies unease. Artificial intelligence is no longer a toy for hobbyists - it can already write melodies in seconds, clone a singer’s voice, or imitate a band’s sound. Paul McCartney put it plainly earlier this year: “AI is a great thing, but it shouldn’t rip creative people off … Make sure you protect the creative thinkers, the creative artists, or you’re not going to have them.”

Harvey Mason Jr., chief executive of the Recording Academy, has echoed the same concern from the industry side. “AI absolutely will play a part in the future of music and creativity,” he said, “but we want to make sure that human creativity is protected.” His institution drew a line when it ruled that Grammy awards remain for human creators, even if AI contributes. The message is clear: these tools are here, but without rules they risk hollowing out the very thing they claim to serve.

By 2030, the outlines of that new world are visible. Consider two musicians living it.

In Lagos, a twenty-seven-year-old named Amina Reyes writes and records from her laptop. Cloud-based studios let her collaborate with a cellist in Berlin and a beatmaker in Seoul as if they were in the same room. She leans on AI for sketches - harmonies, textures, even rough mixes - but she makes the choices, shaping what matters. Her career doesn’t depend on viral hits. Instead, she nurtures a smaller circle of superfans who pay her directly for annotated lyrics, early mixes, and virtual listening parties. Luminate’s research shows that about one in five U.S. listeners already qualify as superfans, and they spend far more on merch and tickets than casual listeners. Goldman Sachs predicted years ago that this group would become the growth engine of the industry. Amina’s career is the forecast in practice.

In Denver, thirty-two-year-old Ethan Kim has chosen another route. He never tours. He doesn’t build a fan club. Instead, he produces short musical cues - half a minute of suspense for a thriller, a playful loop for a cooking show, a gentle guitar line for a meditation app. His work is tagged, licensed, and distributed through marketplaces that thrive on speed and precision. He even rents out digital models of his guitar tone and voice, earning royalties each time another producer uses them. The income is steady, if modest, enough to sustain a middle-class life. Daniel Bedingfield once described this divide: “There will be two paths: there’ll be the neo-luddite path, and then there’ll be everyone else, most of the planet, who thinks the music’s really good and enjoys it.” Ethan embodies that second path, where music is as much service as art.

These two imagined careers - Amina’s built on meaning, Ethan’s on utility - capture both the promise and the peril of 2030. On one hand, creation has never been more open. A songwriter in Lagos can reach Berlin and New York without ever booking a flight. Local sounds spread faster than ever; fans can now support artists directly with memberships, virtual tickets, and collectible editions. Björn Ulvaeus of ABBA framed it well: “I see [AI] as a valuable co-creative partner that can inspire new ideas and help overcome creative blocks.” For artists like Amina, that is exactly how it works.

But the risks are evident, too. When music can be generated endlessly, much of it risks becoming wallpaper - functional, forgettable, and cheap. Without enforceable rights, young musicians may see their voices and styles folded into training sets they never consented to. A Vox analysis captured the contradiction: “AI-generated music can expand the potential of human creativity, but in doing so, it could choke off the livelihoods of the musicians who make it possible.” Ethan’s model shows one way forward, but it also points to a future where music is treated less as expression than as content to be slotted in.

What happens between now and 2030 will decide which story dominates. If regulation matures, if platforms reward real engagement instead of raw numbers, and if provenance is enforced, then the Amina scenario feels within reach: sustainable, global, and deeply human. If not, then the Ethan model may expand: steady for a few, constraining for many.

The question is no longer whether AI will shape music. It already has. The real question is whether we preserve the part that machines can’t touch - the spark that turns organized sound into something meaningful.