“I often say that artificial intelligence is the new electricity.” - Andrew Ng, AI pioneer
AI turns vintage tracks into fresh revenue streams
Music labels are now using AI to bring new life into old sound recordings. By isolating vocals and instruments, AI allows labels to refresh classics without re-recording artists, opening fresh commercial avenues on platforms like YouTube, Meta, and others. This is a new application and has a promising future ahead.AI-driven revival
Major labels such as Saregama and Times Music are deploying AI to create new content from decades-old songs, especially devotional and nostalgia-driven categories. These tracks lacked videos when first released, but AI now enables visual storytelling that resonates with today’s audiences. The labels are happy to have discovered a new revenue stream!
AI-powered production
AI is allowing companies to cut production costs by up to 70 percent and slash turnaround times by nearly 80 percent. With tools that isolate audio stems accurately, labels can remix and repackage hits for a new generation without harming the original recordings.
Expanding reach without rights
A key advantage is staying within permitted audio-only rights. Many catalogues do not include video rights, leading to massive annual losses. By pairing licensed audio with AI-generated visuals, labels can reach wider audiences without infringing copyrights, while protecting artist contributions and integrity.
Future-ready
With most of branded content using unlicensed music being lost revenue for the industry, AI-supported catalogue reboot offers a sustainable solution. The goal is to improve discoverability, revive fan interest in older songs, and make classic music matter again on modern digital platforms.
Summary
AI is helping music labels revive legacy tracks, cut video production costs, avoid copyright hurdles, and reach new listeners worldwide. By refreshing vast archives through legally compliant AI visuals and audio stem separation, old hits are finding profitable new lives online.
Food for thought
As AI recreates the appeal of classics, will future generations feel nostalgic for music they never heard in its original era?
AI concept to learn: Stem Separation
Stem separation is an AI technique that isolates different elements of a song such as vocals or instruments from a single audio track. It helps remixers and music producers reuse parts of old recordings without altering the original. It plays a key role in modern music restoration and innovation.
[The Billion Hopes Research Team shares the latest AI updates for learning and awareness. Various sources are used. All copyrights acknowledged. This is not a professional, financial, personal or medical advice. Please consult domain experts before making decisions. Feedback welcome!]
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