How professionals in law, publishing, consumer goods, and enforcement perceive AI’s risks and opportunities.

Artificial Intelligence & Intellectual Property Protection: A Dual-Edged Reality

by ChatGPT-4o

Introduction

Artificial Intelligence is rewriting the playbook of intellectual property (IP) and brand protection. The AI & IP Final Report by the A-CAPP Center and the IPR Coordination Center (2025) delivers one of the most comprehensive snapshots yet of how professionals in law, publishing, consumer goods, and enforcement perceive AI’s risks and opportunities. Its findings underscore an uncomfortable truth: while AI promises efficiency and detection power, organizational readiness and literacy remain alarmingly low, creating gaps ripe for exploitation by counterfeiters and IP thieves.

Surprising Statements

Several findings leap out as unexpectedly stark:

1. Organizational unreadiness:

   • 38% of participants admitted their organizations are “not equipped” to handle AI threats—and only 18% had developed any formal protocol. In a world where counterfeiters are already deploying AI, this level of inertia is surprising and dangerous.

2. Counterfeits outperform originals:

   • Professionals noted that AI-generated packaging sometimes “looks better than the original” products, making even manufacturers struggle to detect fakes. This flips the old assumption that counterfeits are obviously inferior.

3. Gray zones of copyright law:

   • One participant highlighted that “AI-generated versions of real works exist in a gray zone,” where LLM-generated summaries or paraphrases resemble originals but aren’t exact duplicates—raising doubts over what counts as infringement.

4. Unfamiliarity with threats:

   • Around 20–30% of professionals were unfamiliar with AI’s role in malicious activities like credential theft, campaign resilience, or stealth. The very people responsible for protecting IP were unable to even assess the threats.

Controversial Statements

The report also surfaces claims that stir debate in legal and policy circles:

1. Copyright void for AI works:

   • Multiple participants pointed to the USPTO’s position: AI-generated works are not copyrightable. This provoked concern that creators using AI tools could unintentionally forfeit rights, undermining the value chain in publishing and film.

2. Counterfeiters are better at marketing than brands:

   • Some argued counterfeiters use AI-driven targeting and ads more effectively than corporations, raising uncomfortable questions about whether legitimate businesses are being out-innovated.

3. Legal lag:

   • Practitioners expressed consensus that “laws haven’t caught up yet” to AI-enabled IP violations. Yet there was optimism that legislation would adapt—a debatable stance given the pace of tech vs. regulation.

4. Ethically sourced models:

   • The idea of training AI models only on licensed content was described as a “good compromise.” While pragmatic, it clashes with current lawsuits where AI firms defend scraping under “fair use,” showing an unresolved policy war.

Valuable Statements

The most constructive insights center on opportunities to align AI with protection rather than threat:

1. Detection and enforcement at scale:

   • AI tools can scan tens of thousands of listings in minutes, making enforcement against counterfeit sellers far more feasible than human review.

2. Pattern recognition against illicit networks:

   • AI can map counterfeit trade routes and seller networks, providing intelligence that law enforcement would otherwise miss.

3. AI literacy as leverage:

   • The study found higher AI literacy strongly correlates with confidence and willingness to deploy AI for IP protection. This makes training a strategic enabler, not just an HR box-tick.

4. Dual perceptions of AI:

   • Despite the threats, 63% of participants still agreed AI is beneficial for IP protection—signaling appetite for innovation if literacy and trust barriers are lowered.

Recommendations

For IP & Brand Protection Professionals

1. Develop tailored AI literacy programs: General awareness is not enough—training must focus on concrete malicious uses (credential theft, stealth, campaign resilience) and practical countermeasures.

2. Build organizational readiness: Every major brand owner should draft and test an AI-specific IP protocol, covering detection, takedown, and escalation procedures.

3. Strengthen cross-industry collaboration: Counterfeiters exploit global e-commerce; publishers, consumer goods, and law enforcement must pool intelligence and share AI-powered detection tools.

4. Advocate for clarity in law: Push policymakers to address gray zones (e.g., AI summaries, derivative works) and ensure fair licensing models that prevent the erosion of copyright.

5. Leverage external expertise: Until internal capacity matures, outsourcing to AI-driven vendors for monitoring and enforcement is pragmatic—but organizations must scrutinize vendor practices to avoid overreliance.

For AI Developers

1. Commit to ethical data sourcing: Adopt licensing-first approaches for training datasets, building models on authorized, high-quality corpora to avoid IP liability and misinformation risks.

2. Embed transparency: Develop explainable AI tools so brand protection professionals can trust model outputs in legal and enforcement contexts.

3. Design anti-counterfeiting applications: Expand AI systems that detect fakes (e.g., watermark recognition, image forensics) and integrate them into customs and law enforcement workflows.

4. Minimize bias in protection systems: Ensure AI doesn’t disproportionately protect large brands at the expense of smaller rights holders, democratizing enforcement capacity.

5. Collaborate with IP stakeholders: Proactively involve publishers, creators, and brand owners in system design to align detection tools with real-world infringement patterns.

Conclusion

The report paints AI as both a threat multiplier for counterfeiters and a force multiplier for defenders. The most surprising discovery is not the sophistication of AI-enabled fakes, but the organizational unreadiness to meet them. The fight for IP integrity will not hinge solely on legal reforms but on the ability of professionals to raise literacy, adopt tailored tools, and push developers toward ethical, transparent, and rights-respecting models. In this dual-edged environment, readiness is not optional—it’s survival.