Next: Factor 7 - Patentability Potential and Layered Strategies
Previous: Factor 5 - Commercial Longevity
This article forms one part of a broader decision framework for evaluating whether patent or trade secret protection is appropriate for AI innovation.
The framework is designed to help decision-makers (e.g., innovators, in house, CTOs) align patent and IP strategy with underlying business realities and moving beyond purely "legal" considerations.
Defensive blocking considers whether a patent can prevent others from patenting or controlling adjacent technical or commercial space.
Defensive blocking matters for two main reasons: (i) to stop competitors from obtaining AI patents that could later restrict your ability to operate, and (ii) to provide leverage for counter-assertion if a competitor brings a patent claim against you.
This consideration also extends to the risk that competitors may gain access to the technology through your former employees with detailed knowledge of your systems (i.e., despite the internal function of the system not being reproducible).
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Examples: Competitor Defensive Positioning
- Patents (High Defensive Value): AI-Based Documentation Classification and Compliance
An AI-based document classification or compliance analysis system deployed in a highly competitive market, where multiple vendors are developing similar solutions using overlapping techniques. Patents in this space can block competitors from patenting incremental variations and provide leverage in negotiations or disputes involving overlapping rights.
- Trade Secrets (Low Defensive Value): Company-Specific Maintenance Operations
An AI system used internally to optimize maintenance scheduling for a company’s proprietary equipment based on custom sensor configurations and operational constraints. The use case is highly specific to the company’s internal processes and custom hardware, with few external competitors and little incentive for others to develop or patent similar solutions. This results in low defensive value for patent protection and making trade secret protection more appropriate.
- Hybrid Approach (Patents/Trade Secrets): AI for Controlling Hydrogen Production with Client-Specific Adaptations
A company offers a licensable AI-based control platform for hydrogen production processes. The AI platform can manage electrolysis or reforming operations using standard process data including temperature, pressure and gas composition.
The platform is offered broadly in a competitive market with multiple vendors providing similar AI-driven solutions. Patent protection is used to cover the system-level application of AI for monitoring and controlling hydrogen production. This provides defensive value against competing platforms.
For individual customers, the platform is optionally further adapted to account for site-specific equipment configurations, or operating conditions, unique to a given hydrogen facility. These customer-specific AI adaptations are novel but are tightly coupled to the client’s processes and provide little value outside that context. Because non-client competitors have little incentive to replicate them, these adaptations offer low defensive value and are better protected as trade secrets.
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Applying the Decision Tool: Patents or Trade Secrets
For a further discussion of the decision framework and remaining decision factors in the framework, please see the following:
Framework: Patents or Trade Secrets
Factor 1: Nature of AI Innovation
Factor 2: Enforceable Scope of Patent Protection
Factor 3: Reproducibility of AI Innovation
Factor 4: Business Delivery Model
Factor 5: Commercial Longevity
Factor 7: Patentability Potential and Layered Strategies
If your organization needs assistance evaluating which aspects of its AI innovation are better suited to patent protection versus trade secret protection, our team can help. Our team can also support patent filing and the development of a broader IP strategy.
