The end of copyright? How AI is changing intellectual property

If you work in marketing, software development, or lead a creative team, you've probably found yourself asking the following question: "If I created this text, image, or code using artificial intelligence, who owns the intellectual property?" This question, which once seemed like science fiction, is now at the center of one of the biggest legal and corporate battles of our time. We are entering an economy where the most valuable asset of companies is no longer physical; the real value now resides in data, digital reputation, governance capacity, and intellectual property.

To understand in depth how Artificial Intelligence is redefining copyright laws and transforming corporate governance, we spoke on the Elas em Tech with two leading figures in the Brazilian legal and technological ecosystem: Tania Liberman (a specialist in data and IP protection qualified in Brazil and New York) and Julia Pazos (a leading figure in the strategy for protecting and monetizing intangible assets and female leadership in blockchain).

Make yourself a coffee and follow along with this detailed analysis of the impact of AI on the intellectual property ecosystem.

The great legal paradox: can a machine be an author?

Traditional copyright law, both in Brazil and in most of the world, has a very clear basis: for copyright protection to exist, there must be a human creation. And that's exactly where the terrain becomes thorny.

When you enter a prompt into ChatGPT, Midjourney, or Copilot and the tool generates a result, who is the author? Currently, the global landscape is divided into two main currents:

1. The public domain stream

It argues that the result generated by generative AI automatically enters the public domain, meaning it lacks legal protection and can be used by any competitor. While this is the most literal interpretation of current law, it creates a dangerous scenario for capital markets and innovation agencies, limiting the monetization of assets.

2. The current level of human intervention (prompt engineering)

She argues that authorship should be evaluated based on the level of human interaction and creativity in the process. As Julia Pazos explained, the professional creative process with AI is not limited to a single click:

The lesson for companies is clear: the more generic their use of AI, the more similar their brand will be to the competition and the less legal protection they will have. Originality remains the greatest competitive differentiator.

The invisible risk: training data and the leakage of trade secrets

The discussion about AI and intellectual property is not limited to what the tool produces (output), but also encompasses what it consumes (input). There are two critical bottlenecks that your IT team and legal department need to monitor under strict governance guidelines:

The use of protected data without authorization

databases copyrighted. If your company uses AI that violated third-party copyrights during training, the final product delivered to your client may carry a hidden legal flaw.

Leaking confidential information via prompts

A very common and dangerous mistake: employees entering contracts, customer data, proprietary code, or marketing plans into open (public) AI tools for them to create summaries or reviews.

Many of these tools use user interactions to train their external models. If the AI ​​is not certified and the contract is not reviewed to ensure complete privacy, your confidential information may be leaked or suggested to a competitor performing a similar search.

Data governance as a competitive advantage and valuation

There was a time when privacy programs (such as compliance with the LGPD) were seen merely as a bureaucratic "to-do list" or a shield against regulatory fines. Today, governance has changed: it has become a monetization asset and a way to differentiate itself in the market.

Tânia Liberman highlighted that, in investment rounds and Mergers and Acquisitions (M&A) processes, technology and data auditing is often the determining factor for the success or failure of the operation:

“When we audit a company for acquisition, we look at whether it has suffered any incidents and how its data is handled. An organization with an adequate governance program is sold more easily and has a much higher valuation.”

Furthermore, companies with structured and clean data can identify market patterns, personalize the customer experience ethically, and create new scalable products with complete legal security.

Blockchain as the "digital registry" of intellectual property

If Artificial Intelligence has shattered the barriers to content creation, how do you prove the authenticity of an asset? The answer lies at the intersection with another disruptive technology: Blockchain.

Going far beyond the cryptocurrency market, blockchain functions as an immutable and decentralized database. In intellectual property, it acts as a powerful record of chronological prior art (timestamp).

• Copyright: In Brazil, copyright does not require mandatory registration to exist. However, in case of litigation, you need to prove that you created the work before a third party. Registering the digital file on a blockchain network generates proof of authenticity with an unequivocal date recognized by the courts.
• Trade secrets: If your company possesses a valuable asset that cannot be patented (because patents expire in 20 years and fall into the public domain, such as the Coca-Cola formula), the strategy is to protect it as a trade secret. Blockchain allows you to register the existence and ownership of this secret without exposing its content to the public, serving as a safeguard against corporate espionage or unfair competition.

The future in 2026: digital literacy and technological sovereignty

As we move forward, the market demands an urgent behavioral shift. It is estimated that in a few years, much of the content circulating on social media will be synthetic (generated by AI). The key differentiator for brands and professionals will be their ability to generate credibility and genuine connections.

The first practical step for any organization that wants to innovate without risking its reputation is digital literacy. Implementing visual AI usage manuals, best practice workshops, and data ethics committees is no longer optional—it's the foundation for protecting the future of your business.

Would you like to hear the full debate?

This article highlights only the key points of a nearly hour-long conversation filled with strategic insights, real-world case studies on international regulation (such as AI Act ), and valuable advice on female leadership in the technology ecosystem.

Don't miss any detail of this lesson on innovation, data, and digital law.

👉 Click here to listen to the full episode on Spotify!

Written by Skyone