[Keeping Tempo With Music Biz] — Why AI’s Most Critical Role in 2026 Will Be Rescue, Not Creation: Op-Ed from Noctil’s Jacob Varghese

Walk into any boardroom, or any room for that matter, in the music industry, and I bet that there will be at least one mention of Generative AI and how it will replace our artists. We spend hours debating deepfakes, voice cloning, and the dilution of human creativity.

While these are valid concerns, they are a strategic distraction. We are so focused on the robot in the recording booth that we are ignoring the fire in the accounting department.

The recent landmark ruling won by GEMA against OpenAI serves as a critical reality check. It confirms that AI operators must comply with copyright law and obtain licenses. This is a massive victory; it establishes the legal right to compensation, which is the bedrock of our industry.

However, viewing this legal victory as the finish line is a dangerous mistake. It is merely the starting gun.

The GEMA ruling effectively hands the industry a contract. But a contract does not process a payment. A court order does not clean a database. The true existential threat to the music business in 2026 isn’t that AI will write better songs than humans; it is that our legacy infrastructure cannot handle the logistics of the victory we just won.

The Disconnect Between Law and Logistics

We are moving from a crisis of legality to a crisis of logistics. The industry is currently celebrating the prospect of licensing deals with major AI models. But we must ask the uncomfortable question: If OpenAI or Google sent us a check tomorrow for the usage of 50 million fragmented training files, would we know who to pay?

Legacy rights management systems were built for a world of physical releases and manageable digital release schedules. They were not architected to handle the infinite supply of generative content or the microscopic granularity required by AI training sets.

If the metadata on the rightsholder’s side is incomplete, inconsistent, or siloed, that “new” revenue stream hits a dead end. It flows directly into the “Black Box.”

The Scale of the Data Debt

This is not a hypothetical problem. We are already sitting on an estimated $2.5 billion in globally unclaimed royalties. This money exists; the usage occurred. The failure was entirely data-driven.

This leakage is driven by “data debt,” decades of bad metadata and incorrect identifiers. When DSPs report 99,000 new tracks ingested daily, legacy matching algorithms, often relying on fuzzy logic or manual intervention, simply break.

The GEMA ruling creates a massive new influx of usage data. If we pour that high-volume data into our current broken pipes, we aren’t creating wealth for artists. We are just increasing the size of the Black Box.

The Pivot to “Rescue AI”

This is where the narrative must shift. For 2026, we need to stop looking at AI as only a Generator and start deploying it as a Validator.

The “killer application” for AI over the next three years won’t be a tool that generates a hit record. It will be the “rescue” architecture that saves our industry from drowning in its own data debt.

The most valuable AI tools for rightsholders will not be Large Language Models (LLMs) like GPT-4, which are designed to hallucinate creatively. They will be Specialized Large Models (SLMs) and Agentic workflows designed to be boringly, ruthlessly accurate.

We are seeing the emergence of “Janitorial AI,” which is a system trained specifically on rights databases, global copyright laws, and conflict resolution protocols.

How Rescue AI Secures the Licensing Revenue

To actually cash the checks that the GEMA ruling enables, we need automation that operates at machine speed:

• Entity Resolution: Instead of humans manually checking why “Beyoncé” and “Beyonce” are triggering a conflict, AI agents can resolve millions of these syntax errors in seconds.
  
• Audio Fingerprinting 2.0: Beyond just matching audio, AI can now analyze the composition within a cover song or a speed-up remix to attribute underlying publishing rights automatically. This is essential for tracking AI-generated derivatives.
  
• Dynamic Data Cleaning: AI can proactively “scrub” catalogs before they are delivered to DSPs or AI platforms, predicting where metadata will break in specific territories and fixing it pre-ingest.
  
  

Data Hygiene as Financial Security

For executives, this is a P&L issue. Every percentage point of data accuracy reclaimed from the Black Box is pure margin. It is revenue that was already earned but never collected.

Furthermore, as we move toward 2026, the valuation of a catalog will no longer be based solely on its historical streaming numbers. It will be weighted by its “Data Hygiene Score.”

A catalog with clean, reconciled, AI-verified metadata will trade at a premium because it guarantees yield. A catalog with “dirty” data will be viewed as a distressed asset, discounted for the cost of the legal and administrative cleanup required to monetize it.

The End of the “Growth at All Costs” Era

The streaming era was defined by user growth. The post-streaming era, which we are entering now, will be defined by operational efficiency. We cannot hire enough humans to manage the volume of content coming down the pipe. If we try to solve a 2026 volume problem with 2010 operational workflows, margins will vanish.

The winners of the next cycle won’t necessarily be the ones with the flashiest generative tools. They will be the labels, publishers and distributors who successfully pivot their tech stack to “Rescue Mode.” They will use AI to pay down their data debt, secure their assets, and ensure that when a song is played, human or machine, the check actually clears.

By Jacob Varghese, CEO & Founder, Noctil

You can read past “Keeping Tempo” articles via the portal linked here. And, stay tuned for more insightful discussions from our members and partners from across the industry!