Pilot Programs, Regulatory Engagement, and Success Metrics
Hypothetical Framework — Prepared by Adservio Innovation Lab Olivier Vitrac (former Research Director, Université Paris-Saclay) For internal discussion — November 2025
This memo synthesizes findings from Memos 1–4 into a strategic action plan for Vivendi. It includes discussion questions for the CTO meeting, concrete pilot program proposals, regulatory engagement strategies, and measurable success criteria. All recommendations are exploratory and assume validation through stakeholder consultation.
AI models act as transformative intermediaries that decouple content from rights, causing:
Acoustic fingerprints to fail (pitch/tempo/stem transformations)
Metadata to be stripped (no ISRC/ISWC propagation)
Attribution to become ambiguous (multi-source blending, generative synthesis)
Result: SACEM's detection rate degrades, leading to revenue leakage for Vivendi (UMG composition royalties, Canal+ video rights, etc.)
Given that traditional rights detection is increasingly ineffective, what organizational and technical measures should Vivendi prioritize to ensure IP remains monetizable and traceable in the AI era?
Validate problem scope: Does Vivendi observe declining detection rates or royalty discrepancies?
Assess appetite for pilots: Is Vivendi willing to invest €1–5M in next-gen traceability experiments?
Identify partners: Can Vivendi convene SACEM, platforms (YouTube, TikTok), and other majors (Sony, Warner)?
Align on regulatory strategy: Will Vivendi champion EU AI Act amendments or industry standards?
| Topic | Question | Why It Matters |
|---|---|---|
| Revenue impact | Has UMG/UMPG noticed declining royalty rates per stream over 2023–2025? | Quantifies urgency |
| Detection gaps | What % of SACEM-registered works are undetected on TikTok vs. Spotify? | Identifies highest-risk platforms |
| AI remix prevalence | How many copyright claims involve pitch-shifted or AI-remixed content? | Measures threat scale |
| Internal data | Does Vivendi have telemetry on Content ID match confidence for UMG catalog? | Enables data-driven pilot design |
| Topic | Question | Why It Matters |
|---|---|---|
| Current detection | Which fingerprinting vendors does UMG use (beyond YouTube Content ID)? | Identifies integration points |
| Watermarking readiness | Does UMG's mastering pipeline support embedding (e.g., via iZotope, Nugen)? | Determines watermark pilot feasibility |
| Blockchain experience | Has Vivendi explored distributed ledger for any IP use case (gaming, video)? | Assesses technical maturity |
| SACEM collaboration | Does Vivendi have influence over SACEM's technology roadmap? | Determines advocacy leverage |
| Topic | Question | Why It Matters |
|---|---|---|
| Investment appetite | Is Vivendi willing to fund pilot programs (~€1M) without immediate ROI? | Gates next steps |
| Competitive positioning | Would Vivendi lead industry consortium, or prefer to follow Sony/Warner? | Shapes governance model |
| Regulatory engagement | Does Vivendi have relationships with EU policymakers (DG CNECT, DG GROW)? | Enables AI Act advocacy |
| Cross-subsidiary coordination | Can UMG, Canal+, Vivendi Gaming align on shared traceability infrastructure? | Maximizes leverage, reduces cost |
| Topic | Question | Why It Matters |
|---|---|---|
| Platform relations | Would mandating watermark detection strain relationships with YouTube, TikTok? | Assesses political risk |
| Artist perception | How would artists/labels react to embedded watermarks (privacy concerns)? | Manages PR risk |
| Failure scenarios | If pilot shows watermarks are defeated by new AI tools, what's Plan B? | Ensures adaptive strategy |
Objective: Validate that embedded watermarks survive AI remixes and improve detection rates
Scope:
Catalog: 500 new releases from UMG (select high-streaming artists)
Technology: Spread-spectrum watermarking (e.g., Civolution, Digimarc, or proprietary)
Platform partners: YouTube (Content ID extension), TikTok (if willing)
Implementation Steps:
Q1 2026: Integrate watermarking into mastering workflow (3 pilot studios)
Q2 2026: Embed watermarks in 100 tracks; distribute to platforms
Q3 2026: Monitor detection rates (watermark vs. fingerprint-only)
Q4 2026: Analyze results; decide on full rollout
Success Metrics:
| Metric | Baseline (fingerprint-only) | Target (watermark + fingerprint) |
|---|---|---|
| Detection rate (original uploads) | 90% | 95% |
| Detection rate (pitch-shifted ±3 semitones) | 20% | 70% |
| Detection rate (AI remixes on TikTok) | 10% | 50% |
| False positive rate | <1% | <2% |
Budget:
Watermarking tech: €250k (licensing + integration)
Platform integration: €300k (engineering time)
Monitoring & analysis: €150k (3rd-party audit)
Total: €700k
Decision Point: If detection rate improves by <20%, abort; if >30%, scale to full catalog
Objective: Establish tamper-proof provenance for UMG's premium catalog
Scope:
Catalog: 10,000 top-streaming tracks (represents 80% of UMG streaming revenue)
Technology: Private consortium blockchain (Hyperledger Fabric or Polygon Edge)
Partners: SACEM, Sony Music, Warner Music (shared infrastructure)
Implementation Steps:
Q1 2026: Design data schema (hash structure, metadata) + governance model
Q2 2026: Deploy blockchain nodes (4 validators: Vivendi, Sony, Warner, SACEM)
Q3 2026: Anchor hashes for 10k tracks
Q4 2026: Pilot dispute resolution (retroactive proof-of-registration)
Success Metrics:
| Metric | Target |
|---|---|
| Transaction throughput | >1,000 registrations/hour |
| Hash verification latency | <500 ms |
| Dispute resolution time | <7 days (vs. 60 days traditional) |
| Cost per registration | <€0.001 |
Budget:
Blockchain infrastructure: €200k (nodes, setup)
Integration with SACEM: €300k (API development)
Legal/governance: €150k (consortium agreement)
Total: €650k
Governance Model:
Objective: Prove that generative AI models used UMG catalog without license; establish precedent for training royalties
Scope:
Target: 3 generative music platforms (e.g., Suno, Udio, Stable Audio)
Method: Adversarial testing (prompt models to generate UMG-like outputs, analyze for fingerprint matches)
Legal strategy: Negotiate licensing or pursue transparency mandate
Implementation Steps:
Q2 2026: Conduct adversarial audit (generate 10k samples, test for similarity to UMG catalog)
Q3 2026: Publish findings (e.g., "X% of outputs match UMG works")
Q4 2026: Engage AI companies for voluntary disclosure + licensing
Q1 2027: If unsuccessful, submit findings to EU policymakers (support AI Act amendment)
Success Metrics:
| Metric | Target |
|---|---|
| Similarity detection rate | >10% of outputs match UMG catalog (fingerprint or melody) |
| Licensing agreements secured | ≥1 major AI platform |
| Policy impact | AI Act amendment proposed by Q4 2027 |
Budget:
Adversarial testing: €100k (compute + analysis)
Legal engagement: €200k (negotiations)
Policy advocacy: €150k (EU lobbying)
Total: €450k
Regulatory Pathway:
| Regulation | Current State | Desired Outcome | Vivendi Role |
|---|---|---|---|
| EU AI Act | Music gen not high-risk | Classify as "high-risk to IP" → mandate dataset transparency | Lead industry coalition |
| EU Copyright Directive (Art. 17) | Requires "best efforts" detection | Define technical standards (watermarking, phase-domain) | Propose ISO/IEC standard |
| DSA (Digital Services Act) | Platform liability for illegal content | Extend to "unlicensed AI-generated content" | Submit policy brief |
| SACEM Mandate (French law) | Declarative + automated | Require platforms to integrate enhanced detection | Direct SACEM lobbying |
Proposed "AI Music Transparency Alliance":
Core members: Vivendi (UMG), Sony Music, Warner Music, SACEM
Supporting members: Independent labels (Beggars Group, Concord), artist unions (FIM, FIA)
Objectives:
Advocate for AI Act amendment (training data disclosure)
Develop industry technical standards (watermarking, blockchain)
Coordinate litigation against non-compliant AI platforms
Governance:
| Metric | Baseline | Target (2026) | Measurement Method |
|---|---|---|---|
| UMG detection rate (all platforms) | 85% | 90% | SACEM royalty reports + Content ID stats |
| TikTok-specific detection | 60% | 75% | Sample audit (1000 random UMG-tagged videos) |
| Watermark survival rate (pilot tracks) | N/A | 70% (pitch-shifted) | Lab testing + field monitoring |
| Blockchain registry throughput | N/A | 1000 reg/hour | Technical benchmark |
| Metric | Baseline | Target (2028) | Measurement Method |
|---|---|---|---|
| Revenue recovery (due to improved detection) | N/A | +€50M/year | SACEM payout analysis |
| AI platform licensing | 0 agreements | 3+ agreements | Signed contracts (training royalties) |
| Regulatory wins | 0 | AI Act amendment passed | Official EU legislation |
| Cross-subsidiary adoption | UMG only | UMG + Canal+ + Vivendi Gaming | Internal rollout tracker |
| Metric | Target | Impact |
|---|---|---|
| Industry standard adoption | ISO/IEC standard ratified | Vivendi technology becomes global norm |
| SACEM detection rate | 95% (despite AI growth) | Revenue leakage reduced to <5% |
| Vivendi IP leadership | Top 3 in industry innovation ranking | Enhanced brand value, artist relations |
| Risk | Probability | Impact | Mitigation | Contingency |
|---|---|---|---|---|
| Watermarks defeated by adversarial AI | Medium | High | Adaptive embedding (annual key rotation) | Pivot to phase-domain detection |
| Blockchain scalability fails | Low | Medium | Use Layer 2 (Polygon) | Fallback to centralized registry |
| Platforms refuse integration | High | Very High | EU regulatory pressure (Art. 17) | Litigation (breach of best efforts) |
| Risk | Probability | Impact | Mitigation | Contingency |
|---|---|---|---|---|
| Pilot costs exceed €5M | Medium | Medium | Phase funding (abort if P1 fails) | Seek co-funding (Sony, Warner) |
| No measurable ROI by 2028 | Low | High | Set conservative targets (20% improvement) | Reframe as "defensive investment" |
| AI music market collapses | Low | Low | Detection infrastructure useful for all transformations | N/A |
| Risk | Probability | Impact | Mitigation | Contingency |
|---|---|---|---|---|
| AI Act amendment blocked | Medium | High | Multi-pronged advocacy (EU + member states) | Pursue national regulations (France, Germany) |
| Smart contracts not legally recognized | Medium | Medium | Hybrid model (SACEM retains authority) | Manual settlement with on-chain audit |
| GDPR violations (blockchain data) | Low | High | Store only hashes (no PII) | Legal review before deployment |
| Capability | Current State (Hypothetical) | Gap | Action |
|---|---|---|---|
| Blockchain expertise | Low (scattered across subsidiaries) | Medium | Hire 2 blockchain engineers (Q1 2026) |
| Signal processing R&D | Medium (UMG has audio engineers) | Low | Partner with academic lab (e.g., IRCAM, Fraunhofer) |
| Policy/regulatory affairs | High (existing EU lobbying team) | None | Allocate 1 FTE to AI music policy |
| Cross-subsidiary coordination | Low (siloed operations) | High | Establish "Vivendi IP Defense Council" (monthly meetings) |
| Partner | Role | Engagement Model |
|---|---|---|
| SACEM | Co-develop blockchain registry; advocate for mandate | Joint steering committee |
| YouTube / TikTok | Integrate watermark detection | Technical partnership + MOU |
| Sony Music / Warner | Co-fund pilots; share infrastructure | Consortium (equal cost-share) |
| IRCAM / Fraunhofer | Phase-domain detection R&D | Research contract (€300k/year) |
| EU DG CNECT | AI Act amendment | Ongoing dialogue (policy briefs, hearings) |
Duration: 60 minutes Participants: Vivendi CTO, UMG CTO, SACEM rep (if available), Adservio (Olivier Vitrac)
| Time | Topic | Objective |
|---|---|---|
| 0:00–0:10 | Introduction & Context | Present problem hypothesis (Memos 1–2) |
| 0:10–0:25 | Technical Deep-Dive | Walk through detection failure modes (Memo 3) |
| 0:25–0:40 | Solution Overview | Present watermarking + blockchain + AI audits (Memo 4) |
| 0:40–0:50 | Pilot Proposals | Discuss Pilots A/B/C; gauge investment appetite |
| 0:50–0:55 | Regulatory Strategy | Align on EU AI Act advocacy approach |
| 0:55–1:00 | Next Steps | Agree on decision timeline and follow-up actions |
Required: This document (Memo 5) + Executive Summary (2 pages)
Optional: Memos 1–4 (for technical stakeholders)
Meeting notes with decisions and action items
Go/No-Go decision on each pilot (deadline: 2 weeks post-meeting)
Draft consortium agreement (if blockchain pilot approved)
CTO Response: "This is strategic priority. Fund all pilots, lead consortium, advocate at EU."
Vivendi Actions:
Allocate €5M over 2026–2027
Assign dedicated cross-subsidiary team (10 FTEs)
CTO presents at EU Parliament hearing (Q2 2026)
Expected Outcome: Vivendi becomes industry leader; watermarking becomes standard by 2028
CTO Response: "Interesting, but prove ROI first. Fund Pilot A (watermarking) only."
Vivendi Actions:
Allocate €700k for watermarking pilot (2026)
Reserve decision on blockchain/AI audits until results available (Q4 2026)
Participate in industry working groups (no leadership role)
Expected Outcome: Incremental improvement; Vivendi follows Sony/Warner's lead
CTO Response: "Technical solutions too uncertain. Focus on policy advocacy."
Vivendi Actions:
Allocate €500k for EU lobbying (2026–2027)
Support AI Music Transparency Alliance (observer status)
No technical pilots; wait for regulatory mandate before investing
Expected Outcome: Slow progress; dependent on EU timeline (2028+)
CTO Response: "Current systems are adequate. Monitor but don't invest."
Vivendi Actions:
No new funding
Continue relying on Content ID + SACEM
Revisit in 2027 if revenue decline accelerates
Expected Outcome: Revenue leakage continues; competitive disadvantage vs. proactive majors
Vivendi can either:
Pioneer next-generation IP protection (watermarking, blockchain, AI audits) → industry leadership
Participate cautiously (small pilots, follow majors) → risk mitigation
Advocate for regulation without tech investment → slow, uncertain
Maintain status quo → accept revenue leakage as cost of doing business
"Scenario A: Full Commitment" is optimal because:
Revenue risk is material (hypothetical €50–200M annually by 2028)
Technical solutions are mature enough for pilots (watermarking proven, blockchain low-risk)
Regulatory window is open (AI Act revision 2026–2027)
Competitive advantage: First-mover in AI-resilient IP infrastructure
Investment: €5M over 2 years is <0.5% of UMG's annual revenue (~€10B) → acceptable risk
| Action | Owner | Deadline |
|---|---|---|
| Circulate meeting notes + decision summary | Adservio | Meeting + 3 days |
| Go/No-Go on Pilot A (watermarking) | Vivendi CTO | Meeting + 2 weeks |
| Go/No-Go on Pilot B (blockchain) | Vivendi CTO | Meeting + 2 weeks |
| Go/No-Go on Pilot C (AI audits) | Vivendi CTO | Meeting + 2 weeks |
| Draft consortium agreement (if B approved) | Vivendi Legal + SACEM | Meeting + 1 month |
| Assign project leads for approved pilots | Vivendi COO | Meeting + 1 month |
| Schedule follow-up (Q2 2026 review) | All | Meeting + 6 months |
For Vivendi CTO: This is not a "technology problem" or a "legal problem" in isolation. It is a strategic business challenge at the intersection of:
Technical innovation (detection, traceability)
Economic modeling (royalty flows, training fees)
Regulatory influence (EU AI Act, Copyright Directive)
Industry leadership (standards, coalitions)
The companies that solve this will define the next era of media IP protection. Vivendi has the scale, catalog, and political leverage to lead. The question is whether it chooses to act now, or wait for others to set the rules.
End of Memo 5 End of Memo Series (1–5)
Prepared by Adservio Innovation Lab — Hypothetical Framework Contact: olivier.vitrac@adservio.fr
AI transformations (pitch shift, remixing, generative synthesis) evade acoustic fingerprints → SACEM cannot detect → UMG loses composition royalties (hypothetical €50–200M/year by 2028).
Current detection relies on:
Acoustic fingerprints (fragile to AI transformation)
Metadata (stripped during AI remixing)
Watermarking: Embed cryptographic signatures at creation (survives most AI transformations)
Blockchain: Registry for tamper-proof provenance (fast dispute resolution)
AI Training Audits: Prove models trained on UMG catalog → negotiate training royalties
Regulatory Advocacy: EU AI Act amendment (mandate dataset transparency)
| Pilot | Investment | Timeline | Success Metric |
|---|---|---|---|
| A: Watermarking (500 tracks) | €700k | Q1–Q4 2026 | +30% detection rate |
| B: Blockchain (10k tracks) | €650k | Q1–Q4 2026 | <7 days dispute resolution |
| C: AI Audits (3 platforms) | €450k | Q2 2026–Q1 2027 | 1+ licensing agreement |
| Total | €1.8M | 2026 | Proof of concept |
Go/No-Go on pilots? (Deadline: 2 weeks post-meeting)
Alternative: "Scenario B" (watermarking only, €700k) or "Scenario C" (regulatory advocacy only, €500k)
Recommendation: "Scenario A" (full commitment, €5M over 2 years) → position Vivendi as industry leader
One-page summary complete. All 5 memos ready for CTO meeting.