Opinion
The hidden risks of using AI in the invention process
AI can accelerate brainstorming, research and patent drafting, but unless inventors stay in control of the process and protect confidential information, the same technology can jeopardize novelty, patentability, and commercial value.
Rapid developments in artificial intelligence (AI) have changed how ideas move from concept to protectable assets. AI now shows up at nearly every stage of the invention process – brainstorming variations on a concept, accelerated R&D and prototyping, and eventually helping structure and describe the invention into something that can be the basis for the patent application of that invention. Used properly, AI can streamline processes that used to take weeks of iteration. But this speed makes cutting corners enticing, creating real risks that can undermine an invention’s confidentiality, patentability, and commercial value.
AI models are highly effective at generating plausible, well-structured outputs, whether that is code, technical variations, or written descriptions. What they struggle with is understanding, contextually, what actually makes an invention novel. An AI tool does not know how to discern what constitutes a breakthrough (or an improvement) and what is merely standard. Because AI tools are now often used at nearly every stage of the invention process, each output must be reviewed, corrected, and re-explained to ensure accuracy - an inherently counterproductive back-and-forth when AI's appeal is its promise of greater efficiency. AI should enhance your thinking, not do your thinking for you.
That concern is particularly significant when applied to invention disclosures, a necessary step for obtaining intellectual property protection. These depend on clear descriptions of, at a minimum, the problem the invention solves, how it works, and its unique advantages over existing solutions.
Although hallucinations are becoming less likely, AI tools that lack sufficient context or clear direction as to what the inventor regards as the invention can still produce inaccuracies or inconsistencies that may give rise to legal and technical risks in an invention disclosure.
Inventors should control what information the AI can access, including whether the tool relies solely on the data materials provided to it or also draws data from external public sources. Those boundaries matter. If not clearly defined, they can blur the line between what the inventor actually conceived and what the model surfaced independently.
Effective use of AI in the inventive process is rarely accomplished through a single prompt. Producing meaningful outputs often requires an iterative exchange in which the inventor continually supplies additional context, technical details, design constraints, and feedback to guide the model toward a useful result. This creates a paradox: AI performs best when it is given a detailed understanding of the invention, yet every additional prompt may disclose further aspects of the inventive concept and increase the model’s influence over the resulting output. Models’ inability to understand and evaluate novelty means that relying too heavily on AI-generated suggestions may blur the distinction between the inventor’s own contribution and the model’s assistance. Unless these interactions occur within a secure environment governed by clear confidentiality, no-retention, and no-training commitments usually found exclusively within enterprise or private tier-tools, inventors risk exposing the very information they are seeking to protect.
It's important for AI users to realize that consumer-grade (free models and even some paid models) AI tools store, log, or use your inputs to train future models. Feeding invention details into a non-secure chatbot like ChatGPT, Gemini, or Claude, can inadvertently qualify as a public disclosure, which can negate novelty and inventiveness. As a rule, treat any free consumer AI product as inherently non-confidential.
AI’s rapid development has been remarkable, and as these tools continue to evolve, they will only become more integrated into how inventors brainstorm, refine, and document their ideas. Used thoughtfully, AI can significantly streamline the path from invention to disclosure. But its value depends on how it is used. Inventors should treat AI as a tool for efficiency, not as a replacement for human judgement. It is important to stay in control of the process, carefully protect confidential information, verify every output, and ensure that the invention is defined in the inventor’s own words before AI is brought in to refine or organize it.
Yoav Alkalay is Chair of the IL STEM Practice Group at Pearl Cohen, and Justin Halprin is an intern at the firm.
