The rise of generative artificial intelligence (AI)—from large language models (LLMs) to image, audio, and code generators—has sparked a fundamental shift in how innovation is created, protected, and monetized. For companies, inventors, and intellectual property (IP) professionals, the stakes are high: patents remain a cornerstone of competitive advantage, but the rules surrounding AI-generated inventions are still unsettled.
At GHB Intellect, we have explored how AI is reshaping IP strategy. Generative AI introduces unique questions about inventorship, patentability, and valuation that extend beyond traditional AI tools. This article examines these trends and offers practical strategies for businesses navigating this evolving landscape.
Who Owns AI-Generated Inventions?
One of the most debated questions in patent law today is: Who owns the rights to something created by AI?
Patent systems worldwide assume inventions stem from human ingenuity. Most patent offices—including the USPTO, EPO, and UKIPO—require a human inventor to be named. When researchers attempted to file patents naming an AI system (the “DABUS” cases), applications were rejected because only natural persons can be inventors.
This raises critical issues:
- If an AI substantially contributes to the conception of an invention but a human directs, interprets, or refines the output, where is inventorship drawn?
- Could multiple human contributors—engineers, data scientists, or operators—claim inventorship based on their roles in prompting or developing the AI?
- Will future laws treat AI as simply a tool, or as a creative partner with independent contributions?
For now, the safest approach is ensuring a human plays a clear, documented role in the inventive process. Companies should implement protocols for recording how AI outputs are generated, refined, and ultimately transformed into patent-eligible inventions.
Evaluating the Inventive Step in the Generative AI Era
Another challenge lies in assessing non-obviousness (inventive step), a key requirement for patentability.
Generative models can produce chemical compounds, product designs, or technical solutions that may seem novel but result from probabilistic pattern recognition. Patent examiners may question whether such outputs truly involve an inventive leap beyond prior art.
Examples include:
- Pharmaceutical R&D: AI can generate candidate molecules at a scale no human team could replicate. If one proves effective, is it non-obvious simply because a machine produced it?
- Engineering Design: AI can iterate thousands of prototypes for mechanical parts. When does one of these designs cross from computational optimization into true invention?
To strengthen patentability, applications should highlight human contributions—guiding the AI, selecting from outputs, and applying domain expertise to achieve practical results.
How IP Valuation Models Are Adapting to AI
IP valuation methods—income, cost, and market approaches—must now adapt to AI’s unique contributions. Generative AI impacts both the creation and competitive value of patents.
Key factors to consider include:
- Proliferation of Similar Inventions: If AI enables many companies to develop near-identical solutions, exclusivity and patent value may diminish more quickly.
- Data as a Strategic Asset: Proprietary training datasets often create more value than the AI tool itself, making data governance central to IP strategy.
- Algorithmic Contributions: Beyond outputs, valuation experts must assess whether the AI model itself represents protectable or licensable IP.
At GHB Intellect, we see a growing demand for holistic IP audits that review patents, trade secrets, software assets, and data rights to capture the full value of AI-driven businesses.
Strategic Recommendations for Innovators
Businesses adopting generative AI should take proactive steps to safeguard their intellectual property. Consider these best practices:
- Document Inventorship Thoroughly: Keep detailed records of human contributions to defend inventorship claims.
- Reevaluate Filing Strategies: Use a mix of patents, trade secrets, and copyrights to protect AI outputs effectively.
- Strengthen Data Governance: Proprietary training data may be the most valuable IP asset—secure and document it carefully.
- Integrate IP and Business Strategy: Align IP protection with commercial goals, whether licensing, litigation, or acquisitions.
- Monitor Legal Developments: Stay informed as laws and precedents evolve around AI-generated inventions.
Looking to the Future
Generative AI is more than just another innovation tool—it is a paradigm shift. It challenges assumptions about inventorship, novelty, and valuation while opening new opportunities for rapid discovery and commercialization.
Companies that harness generative AI effectively will gain speed and efficiency. But those that pair AI adoption with a strong patent and IP strategy will secure long-term competitive advantage.
At GHB Intellect, we specialize in guiding innovators through these challenges—offering patent portfolio development, valuation, and strategic consulting tailored to the AI era.
The innovators who thrive will be those who embrace generative AI not only as a creation engine but also as a catalyst for building strong, defensible intellectual property.