If you have built an AI model, app, SaaS product, or algorithm, you have probably wondered: "Can I patent this?"
The short answer: yes, you can patent software and AI-related inventions — but you cannot patent a bare idea, abstract algorithm, or generic "do it on a computer" concept. The way you frame your invention is everything.
Protecting code and algorithms: why it's complicated
Software and AI patents sit in one of the most complex parts of patent law. Unlike a simple mechanical device, your invention is largely intangible, built from code, models, and data, and often described at a high level ("this algorithm sorts faster," "this AI predicts X").
Patent offices like the USPTO are wary of granting monopolies on abstract ideas or basic math. So to be patentable, your AI or software invention usually needs to be concrete (not purely conceptual), technical (not just a business idea wrapped in code), and tied to a real-world application with measurable impact.
You generally cannot patent: "A new sorting algorithm." But you may be able to patent something like:
"A method for optimizing database query performance using a novel sorting algorithm, resulting in a measurable reduction in server load."
Notice the difference: it's a specific method (not an abstract idea), tied to a practical application (database queries), with a technical result (reduced server load). The more your invention looks like a technical solution to a technical problem, the better your chances.
What can be patentable in software and AI?
These types of inventions are often good candidates (when they're new and non-obvious):
New computer functionality
Software that makes a computer or system behave in a new way — a novel user interface that fundamentally changes how users interact with data, a new method of data compression or encryption, or a unique way of handling concurrent requests or resource allocation.
Improvements to performance or security
A process that reduces latency or server load in a measurable way, a new approach to protecting systems from cyberattacks, or an algorithm that improves memory usage or energy efficiency.
AI models used in a specific system
Patents rarely protect "just a neural network," but may protect a system for diagnosing medical conditions from images using a specific model architecture and training scheme that yields improved accuracy, or a method for detecting fraudulent transactions using a trained model with certain inputs and decision logic. Key idea: tie your AI to a real-world problem, and describe the system and method — not just the buzzwords.
Software controlling hardware
A control algorithm that optimizes motor control in an electric vehicle, a computer-implemented method that adjusts sensor thresholds in response to environmental conditions, or an AI model controlling robot behavior in a novel way. This hardware-and-software combination can be strong because it's clearly rooted in the physical world.
Every case differs, but these are often weak or non-patentable on their own:
- Pure abstract ideas, or matching people with products without technical detail.
- Business methods with no technical implementation, or generic "do it with a computer" versions of known practices.
- Raw source code — usually protected by copyright, not patent law.
- Data sets by themselves — a database isn't an invention, though how you generate or use it might be.
Why provisionals are especially helpful for AI/software
Tech moves fast, and being first to file can make a huge difference — you might not want to wait until every line of code is perfect. That's where a provisional patent application (PPA) shines. It locks in an early filing date while you're still building, lets you use "patent pending" with investors and early customers, and lets you describe the core technical idea, system architecture, data flow, and performance improvements.
Over the next 12 months you can improve your model, gather performance metrics (accuracy gains, latency reductions), and build out implementation detail. Then, when you file your non-provisional (utility) patent, you include those deeper technical details and measurements.
Practical steps if you're considering a software/AI patent
- Write down what your invention actually does. What problem does it solve, how is that problem solved today, and what's different about your approach?
- Describe the technical implementation. Architecture diagrams, data flow, key steps in the pipeline, and improvements in speed, accuracy, or resource usage.
- Focus on concrete examples. "The system receives X, processes it with steps A-B-C, and outputs Y, which improves Z by 30%."
- Consider a provisional. Use it to secure your date and "patent pending" while you keep building.
- Talk to a patent professional for complex cases. Especially in regulated areas like fintech or healthcare.
This is general information, not legal advice. Specific cases can differ.
Document your AI or software invention the right way
AutoInvent turns your description of a software or AI invention into structured, patent-style text — emphasizing the practical application, system architecture, and technical improvements — and generates figures of your system components and data flows. Then it guides you step-by-step through filing your provisional yourself with the USPTO: idea to filed provisional in under 10 minutes, for a couple hundred dollars plus the USPTO fee. You stay in control of your code and your IP strategy.