# How Is AI Inventorship Reshaping Patent Strategy in 2024?

patentreviewpro.com · October 14, 2026

> USPTO Guidance on AI-Assisted Inventions In 2024, the USPTO’s revised inventorship guidance makes clear that AI cannot be named an inventor, but a...

## USPTO Guidance on AI-Assisted Inventions

In 2024, the USPTO’s revised inventorship guidance makes clear that AI cannot be named an inventor, but a human must make a significant contribution to conception. That shifts patent strategy from simply claiming AI-generated outputs to documenting human ingenuity: problem framing, prompt design, selection, and reduction to practice. Crowell & Moring notes this affects patent versus trade secret choices, while Holland & Knight stresses the human element and Morgan Lewis tracks the revised guidance. IPWatchdog warns that drafting must survive not just the current cycle but the next.

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Globally, Japan’s JPO and extraterritoriality debates add pressure to file consistently. At patentreviewpro.com, AI Patent Review advises inventors to record AI’s role, identify human inventors early, and tailor claims to actual human contributions. In 2024, winning strategies combine rigorous invention disclosures, freedom-to-operate reviews, and trade secret protection for outputs that cannot meet inventorship. Monitor guidance updates, because AI inventorship is reshaping not only patentability but also portfolio value, licensing, and litigation risk.

## Drafting AI Patents for Future Cycles

AI inventorship is forcing patent strategists to rethink foundational assumptions in 2024. The USPTO's revised inventorship guidance for AI-assisted inventions, issued in February, clarified that a natural person must make a significant contribution to each claimed invention, but left practitioners grappling with how to document human involvement convincingly. Firms like Crowell & Moring and Holland & Knight have emphasized that the guidance, while helpful, stops short of bright-line rules, meaning applicants must build robust inventorship records during prosecution rather than retrofitting them later. This is particularly acute in AI drug discovery, where machine learning models generate candidate compounds with limited human intervention, raising questions about whether contribution to the model's design or training suffices.

Forward-looking drafting has become the prevailing response. IPWatchdog commentary urges practitioners to draft AI patents that survive not just the current guidance cycle but successive revisions, favoring claims anchored in concrete technical applications and human-driven innovation narratives. Internationally, Japan's patent landscape is shifting as the JPO refines examination practice around AI and extraterritoriality, signaling that global harmonization remains elusive. Strategic portfolios increasingly pair patents with trade secret protection for training data and model architectures, hedging against disclosure requirements that could undermine protection for the underlying AI itself.

## Patent vs. Trade Secret Strategies

In 2024, USPTO and JPO guidance reinforced that AI cannot be a named inventor, yet AI-assisted inventions remain patentable when a human makes a significant contribution to the conception. This forces patent strategy to document human ingenuity, not merely AI outputs. Companies must capture prompts, iterations, and human selection/refinement as evidence. Drafting shifts toward claiming specific technical improvements, training methods, and hardware integrations that show human-designed architecture, reducing rejection risk under evolving subject matter eligibility and inventorship rules.

At the same time, trade secret strategy gains appeal for AI models, weights, and pipelines where human inventorship is hard to prove or disclosure would expose core assets. But patents still offer exclusion and licensing value for AI drug discovery, diagnostics, and industrial applications. The practical result is hybrid portfolios: patents for human-conceived, claimable advances; trade secrets for opaque model internals and data. Extraterritorial AI use and revised USPTO guidance make early inventorship audits, assignment hygiene, and jurisdiction-specific filing decisions central to 2024 strategy.

## Global Approaches: Japan and Beyond

In 2024, AI inventorship stopped being a theoretical debate and became a drafting constraint. The USPTO's revised guidance continues to require natural-person inventors who made a significant contribution, so patent strategies now document human conception, prompt engineering, and iterative selection with care. Teams are separating AI-assisted discovery from AI-devised output, using trade secrets for unexplained model insights, and reserving patent filings for inventions with clear human contribution. The Holland and Knight analysis and Morgan Lewis updates both underscore that inventorship errors can invalidate otherwise strong claims.

Globally, Japan and beyond add another layer. The JPO's refined examination practice and debates over extraterritoriality push applicants to localize inventorship records and claim language. Drafting must survive current guidance and future cycles, so AI patents increasingly focus on technical improvements, training methods, and system architectures rather than bare outputs. This reshapes patent review by demanding stronger inventor narratives and jurisdiction-specific filing plans alongside hybrid patent and trade secret portfolios.

## Patent Analytics in the AI Era

The USPTO's revised inventorship guidance has settled the core rule: AI systems cannot be named inventors, but humans who make significant contributions to an AI-assisted invention can. This clarity, reinforced through 2024 updates and Federal Circuit precedent, pushes strategy away from vague "AI-generated" claims toward documenting the human conception that patent law demands. Prosecutors now draft with an eye toward surviving the next guidance cycle, building specification narratives that show how a person reduced AI output to practice.

For drug discovery, where AI models increasingly generate candidate molecules, the stakes are highest. Companies must decide what to patent, what to hold as trade secrets, and how to prove human contribution without exposing proprietary model weights. Japan's JPO and other offices are refining parallel standards, so global portfolios need consistent inventorship records. The practical result: stronger internal invention-capture processes, earlier human-in-the-loop documentation, and claims drafted to withstand both § 101 eligibility challenges and inventorship scrutiny.

## AI Inventorship: Patent vs. Trade Secret

| Dimension | Patent Strategy in 2024 | Trade Secret Strategy in 2024 |
| --- | --- | --- |
| Inventorship | USPTO guidance requires natural-person significant contribution; AI cannot be named. | Avoids inventorship disputes by keeping AI-assisted methods confidential. |
| Disclosure | Must disclose enough to enable claims while surviving revised guidance cycles. | No enablement/disclosure duty, but leaks or reverse engineering risk. |
| AI Drug Discovery | Patent key compounds, models, workflows with human-conceived improvements. | Protect training data, model weights, assays, and negative results. |
| Global Filings | JPO and other offices refine AI examination; extraterritoriality complicates filings. | Coordinate secrecy laws and employee access across jurisdictions. |

For AI-assisted inventions, patenting remains viable only when humans significantly contribute to the inventive concept. Trade secrets better protect models, datasets, and iterative know-how that are hard to claim or detect. In 2024, strategists file narrow patents on tangible outputs while keeping core AI methods confidential. Review inventorship evidence, document human contributions, and align global filing choices with secrecy controls.

## Quick answers

### Can AI be named as an inventor on a patent?

No, current USPTO guidance requires that inventors be natural persons, though AI-assisted inventions can be patented if humans made significant contributions.

### What is the key challenge for AI-assisted inventions?

The main challenge is documenting and proving human contribution to the inventive concept to satisfy inventorship requirements.

### How does Japan handle AI inventorship?

Japan's JPO refines examination practice for AI-related inventions, focusing on extraterritoriality and human inventorship.

### Why use trade secrets for AI inventions?

Trade secrets can protect AI algorithms and data without disclosing them, avoiding inventorship complications.

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