X vs music publishers: lessons for AI licensing tools

A single missing licence can wipe out a whole product strategy.

That’s the uncomfortable subtext behind X (formerly Twitter) suing 18 major music publishers and the National Music Publishers’ Association (NMPA) in the US, alleging an antitrust conspiracy to force inflated licensing terms. According to the Reuters report carried by CNA, X claims publishers representing “more than 90%” of US copyrighted music refused to negotiate individual deals and instead coordinated through the trade association.

If you’re building or marketing an AI-driven platform in Singapore—especially anything that touches user-generated content, media, or data—this case isn’t “US-only drama.” It’s a clear reminder that licensing and rights frameworks are product features now. They affect growth, trust, distribution, and revenue.

This post is part of our Singapore Startup Marketing series, and the angle is practical: how founders and growth teams can avoid a licensing mess becoming a brand crisis, and how AI business tools (workflow automation, rights tracking, contract intelligence) can turn compliance from a drag into a moat.

What X is alleging—and why it matters to platforms

X’s lawsuit argues the publishers and NMPA coordinated to deny X competitive, publisher-by-publisher terms, pressuring X into industrywide licensing terms. X also says the publishers used takedown notices targeting thousands of posts weekly as leverage, and that X removed thousands of posts and suspended more than 50,000 users, harming user experience and advertising revenue.

The publishers’ side, via NMPA’s CEO David Israelite, is blunt: X is the only major social platform that doesn’t license songs on its platform. They frame X’s lawsuit as a distraction from alleged long-running copyright infringement.

Here’s why this hits home for AI platforms and startups:

• Rights issues scale faster than teams do. When you’re growing, content volume and edge cases multiply. Manual processes collapse.
• Takedowns are a growth tax. Every takedown creates user frustration, churn risk, and support overhead—plus it can spook advertisers.
• Negotiation power is asymmetric. Platforms want modular, flexible terms; rights-holders often want standardised, enforceable terms.

Snippet-worthy truth: If your product enables creation, sharing, remixing, or training on content, licensing isn’t “legal’s problem”—it’s your retention curve.

The real issue: licensing isn’t built for internet speed

Music licensing is a classic example of a system that evolved for a different era:

• Many stakeholders (publishers, songwriters, collecting societies, platforms)
• Multiple rights layers (composition vs sound recording)
• Territory-by-territory rules
• Enforcement that’s often automated, but negotiation that’s still deeply manual

AI platforms run into the same mismatch with data rights:

• Training data rights (who owns what, what permissions exist)
• Output rights (who can use generated assets commercially)
• Model and dataset provenance (can you prove what went in?)
• Reuse rights for customer inputs (especially in B2B tools)

In other words, the X lawsuit is a high-profile version of what smaller companies experience quietly: you can ship product in weeks, but you can’t fix rights architecture in a weekend.

A marketing lens: why “compliance-first” wins trust in APAC

In Singapore and across APAC, B2B buyers often ask:

• “Can you show an audit trail?”
• “What’s your IP and data governance approach?”
• “What happens if a rights claim comes in?”

Growth teams sometimes treat these as procurement hurdles to overcome.

I think that’s a mistake. If you position governance as a feature—clear policies, transparent usage rights, fast dispute handling—you build a brand that’s safer to champion internally. That’s a competitive advantage in enterprise deals.

What Singapore startups can learn from X’s dispute

X is arguing about music publishing, but the startup lessons are universal.

1) Don’t build your GTM on “we’ll sort the rights later”

If your growth strategy depends on users uploading or remixing third-party content, you’re effectively betting that enforcement will be weak or inconsistent.

That bet becomes fragile the moment:

• you become visible (press + virality)
• you become lucrative (ads + subscriptions)
• you enter regulated partnerships (banks, telcos, media companies)

A safer stance is: design for permissioning early, even if it’s imperfect at launch.

2) Treat takedowns like a product KPI

X claims weekly takedown notices targeting thousands of posts and says it suspended 50,000+ users due to copyright issues.

Even if your numbers are smaller, the pattern is the same. Track:

• takedown rate (% of uploads flagged)
• time-to-resolution
• repeat offender patterns (often unintentional)
• revenue impact (lost creators, lost inventory, support cost)

Make it visible to product and marketing. If you’re only hearing about takedowns from angry users, you’re already behind.

3) “Industrywide terms” vs “individual terms” is a strategic fork

X says it was denied the ability to negotiate individual licences on competitive terms.

For startups, the equivalent fork shows up as:

• signing a broad, standard agreement quickly to ship
• negotiating modular terms that match your business model

My bias: default to modularity where possible. It’s harder upfront, but it prevents you from paying for rights you don’t use, or being blocked from features you’ll need later (regional expansion, new formats, AI remix, enterprise tiers).

Where AI actually helps: smarter licensing and royalties

AI isn’t a magic wand for rights problems, but it does three useful things well: classification, matching, and auditability.

Automated rights intake: contract intelligence that doesn’t miss clauses

If you’re negotiating licences or ingesting third-party content, AI contract tools can:

• extract key terms (territory, duration, permitted uses)
• flag risky clauses (broad indemnities, ambiguous sublicensing)
• build a searchable “rights library” for your team

The marketing benefit: faster deal cycles and fewer “we can’t launch that feature” surprises.

Content identification: match uploads to known works at scale

Platforms need a practical way to detect and route content:

• audio fingerprinting / similarity detection
• metadata matching (with error tolerance)
• confidence scoring and human review queues

This isn’t only about enforcement. It enables:

• pre-clearance flows (“this track requires a licence; here are options”)
• creator education (“why your post is limited”)
• monetisation splits (where agreements exist)

Royalty workflows: less spreadsheet hell, more transparent payouts

If you ever pay creators, partners, or rights-holders, you know the pain:

• inconsistent IDs
• duplicate claims
• territory rules
• reconciliation delays

AI-assisted workflow automation can:

• detect anomalies (duplicate claims, suspicious spikes)
• reconcile against usage logs
• produce explainable payout statements

Transparency reduces disputes. Disputes reduce churn. That’s not a legal argument—it’s a growth argument.

Smart contracts: useful, but only if you fix the plumbing first

People love the phrase “smart contracts” for licensing. Sometimes it’s warranted, but most teams skip the hard prerequisite: clean rights data.

A realistic approach (especially for Singapore startups) is:

1. Standardise identifiers (works, recordings, rightsholders)
2. Create a rights registry inside your product (even if internal)
3. Implement policy-as-code checks before publishing/monetising
4. Only then explore smart-contract execution for:
   • automated splits
   • time-bound licences
   • usage-triggered payments

If you don’t have step 1–3, a blockchain doesn’t save you. It just makes messy data permanent.

Practical checklist for founders and growth teams (Singapore + APAC)

This is the part I’d paste into a Notion doc.

Build a “rights-first” launch plan

• Define your content categories: user-created, licensed, public domain, AI-generated, brand-owned
• Map what’s allowed in each category: upload, remix, monetise, advertise against, export
• Decide your enforcement posture: block, mute, demonetise, or geo-restrict

Make rights legible to users (it’s a marketing asset)

• Use plain language notices (“This audio is restricted in the US”)
• Offer alternatives (licensed library, royalty-free options, replace-audio tool)
• Publish a simple escalation process with response time targets

Prepare for disputes before they happen

• Maintain an audit trail: what was uploaded, when, by whom, and what matched it
• Keep a “litigation-ready” log format (timestamps, hashes, decision reasons)
• Train support staff on rights scenarios; don’t leave them guessing

For regional expansion: don’t assume “one licence covers APAC”

For Singapore startups expanding into Indonesia, Malaysia, Thailand, or Australia, rights regimes and collecting society practices differ.

Treat licensing like localisation. Budget time for it.

What this means for Singapore Startup Marketing in 2026

Most startups think marketing is channels and creative. It’s also risk management that protects growth.

The X vs music publishers fight is a public case study in what happens when:

• a platform’s content model outpaces its licensing model
• enforcement actions hit high-profile accounts
• user trust and advertiser confidence take collateral damage

If you’re marketing an AI product in Singapore—especially a tool that touches content, data, or automation—make governance part of your positioning. Not as fearmongering, but as proof you’re serious.

For teams building AI-driven licensing, royalties, or content compliance tools, the opportunity is clear: customers want faster, clearer rights workflows that don’t kill momentum.

Where do you sit on that spectrum: shipping features first and fixing rights later, or treating licensing architecture as part of your growth engine?

Source article (landing page): https://www.channelnewsasia.com/business/musks-x-sues-music-publishers-over-alleged-licensing-conspiracy-5849586