When you’re building something in software or AI, your code isn’t the only thing worth protecting. The logic behind it, the way it processes data, the unique way it solves a problem — these are all parts of your invention. If you don’t lock them down, someone else can copy them, tweak them slightly, and take your market.
Understanding the Role of a Software Claim
A patent claim is the line in the sand. It tells the world exactly what’s yours and where your territory ends.
Everything else in your patent — the diagrams, the background, the detailed description — exists to support that line.
For software and AI inventions, this is even more critical because competitors can often rebuild your product with small changes in code, architecture, or algorithms.
If your claim is too narrow, they’ll step right over it. If it’s too broad without enough support, the patent office will reject it.
Why software and AI claims feel tricky
Unlike a physical machine, software and AI systems are invisible. You can’t point to a gear or a lever and say “this is my invention.”
The real magic often happens in how the system processes data, learns from inputs, or integrates different components.
That’s why many first-time inventors struggle: they focus on describing what their code looks like now, instead of protecting the deeper logic or approach that makes it unique.
A strong software claim focuses on the function and interaction of the system rather than specific lines of code.
For AI, this might mean claiming the way data is processed, transformed, or analyzed to reach a result — not just the exact algorithm you wrote.
That way, if you later improve the algorithm, or if someone else uses a different algorithm to do the same thing, your patent can still cover it.
Start from the core, not the code
One of the most common mistakes is starting from the wrong place — the codebase. Code changes. Features get added.
Bugs get fixed. But the reason your invention exists usually stays the same.
Your claim should be anchored to that reason. Ask yourself: what problem am I solving, and what is my unique way of solving it?
Write that in plain words. Strip away the buzzwords and ask yourself if a non-technical person could picture it. That statement becomes the seed for your claim.
For example, if you’ve built an AI that detects defects in manufacturing, your code might use a specific convolutional neural network with certain layers.
But the core might be “automatically analyzing images from multiple camera angles to detect and classify manufacturing defects in real time.”
This is broader, and it allows room for your technology to evolve.
The fine balance between broad and narrow
There’s a constant tug-of-war when drafting software claims. Too narrow, and competitors can tweak their product to get around it.
Too broad, and you risk rejection for not being supported by enough detail in the application.
The sweet spot is to claim the invention broadly enough to cover future variations but grounded enough in your description that it feels real and defensible.
Think of it like fencing off a property. If you put the fence too close to your house, you leave a lot of open land for others to use.
If you try to fence off half the state, the authorities will tell you you don’t own it. Your job is to fence off as much as you can realistically defend.
Why the “how” matters as much as the “what”
Many software and AI founders focus too much on “what” their invention does — the outcome — and forget the “how” — the method that achieves it.
Patent law rewards those who can explain the specific mechanism or approach that achieves a result.
Even in the most cutting-edge AI, the patent examiner will want to know the steps, data flows, and interactions that make your system different.
For instance, if your AI produces better predictions than existing models, it’s not enough to say “the AI predicts more accurately.”
You need to explain how it gets there — perhaps through a unique way of preprocessing input data, combining multiple models, or applying a novel training schedule.
That “how” will become a backbone for your claims and make it harder for others to copy without infringing.
Preparing for the long game
When you draft software claims, you’re not writing for today only. You’re writing for the next 10 to 20 years.
Technology will change, and so will your product. Your claims should be forward-looking.
This doesn’t mean guessing future tech, but rather crafting them so they still apply when your invention naturally evolves.
One way to think about this is to imagine your product three versions from now. Will your claim still describe the heart of what it does? If not, you might be writing too narrowly.
And here’s the real kicker: courts and patent examiners read your claims word for word, literally.
One misplaced phrase can narrow your protection in ways you never intended. That’s why the language in a claim isn’t just legal — it’s strategic. It’s the blueprint of your protection.
Structuring a Strong Software or AI Claim
The structure of a claim is like the skeleton of your patent. It holds everything in place and determines how strong it will be under pressure.
When it comes to software and AI, your claim needs to be precise enough to make sense legally, but flexible enough to protect against future variations.
Thinking like an architect, not a coder
Writing claims is less about coding detail and more about system architecture. Think about the major components of your invention and how they interact.
For AI, this might include how data enters the system, how it’s processed, how the model operates, and what outputs are generated.
For non-AI software, it could be about the data structures, user interface flow, or backend processing.
You don’t have to explain every single function, but you need to map out the important steps in a way that someone could understand without seeing your source code.
The claim is a high-level map, not the blueprint of every single screw.
The anatomy of a software claim
A typical software or AI claim follows a simple logical flow:
First, it identifies the type of invention — for example, a method, a system, or a computer-readable medium.
Second, it introduces the main purpose or operation of the invention — for example, “for processing data to detect fraudulent transactions.”
Third, it breaks down the essential steps or components that achieve the purpose — such as receiving input data, transforming the data, applying a model, generating an output, and using the output for a specific purpose.
Even though this seems obvious, the order matters. The claim should lead the reader from start to finish in a way that’s clear and inevitable.
If a step is missing or vague, it creates gaps for competitors to exploit.
Methods vs. systems vs. computer-readable media
One of the strategic choices in drafting is deciding the form of the claim.
A method claim focuses on the steps performed to achieve the result. It’s useful for covering the actual process, regardless of the hardware used.
A system claim focuses on the components — such as servers, processors, and storage — that are configured to carry out the steps.
A computer-readable medium claim focuses on the software stored in a format that a computer can read and execute.
The smart move for many software patents is to use more than one type.
This way, you protect the process, the setup, and the software itself. If one type is harder to enforce, the others might still cover the infringement.
The importance of connections
In software claims, the strength often lies in how the elements are connected. Simply listing components is weak.
The claim should show how they interact to create the unique function of your invention.
For example, don’t just say “a data processing module” and “a prediction module.”
Explain that the data processing module transforms raw data into a structured format, and the prediction module applies a trained model to that structured data to generate an output.
The connection — that one module prepares data for another — makes it harder for others to design around your claim.
Avoiding accidental limitations
A common trap is adding unnecessary detail that limits the claim without realizing it.
For instance, if you claim “an AI system using a convolutional neural network,” then you’ve limited your protection to CNNs only.
If someone uses a transformer model to achieve the same result, you might not be able to stop them.
Instead, you might say “an AI system applying a trained machine learning model” in the claim, while describing CNNs as an example in the description.
This gives you room to cover different model architectures in the future.
Building in flexibility
The way to future-proof a claim is to focus on functions, relationships, and outcomes rather than specific implementations.
This doesn’t mean being vague — you still need concrete steps and components — but you describe them in a way that allows for variation.
For example, instead of saying “a mobile app that displays recommendations on an iPhone screen,” you could claim “a client application that displays recommendations on a user device interface.”
This small shift opens the door for your claim to apply to tablets, AR headsets, or devices that don’t exist yet.
Why claim language feels unnatural
One of the first things inventors notice is that patent claims don’t read like normal sentences.
That’s because they are written in a single sentence, often with a lot of commas and clauses.
This isn’t bad writing — it’s deliberate. The goal is to make the claim self-contained, so you don’t need to reference other parts of the patent to understand what’s covered.
Even though the format is formal, the choices you make inside that structure — which elements you include, the order you present them, and how you connect them — are where your strategic thinking comes into play.
Finding the Core of Your Software or AI Invention
If you strip away all the code, the features, and the technical buzzwords, what’s left should be the beating heart of your invention — the part that makes it new and valuable.
This is your “core inventive concept.” Finding it isn’t just a step in drafting your claims. It’s the foundation for the whole patent.
Why the core matters
Patent law rewards novelty. That means your claim must target something that’s not already out there.
For software and AI, the novelty often isn’t in the programming language, the cloud service, or the model architecture.
It’s in the unique way you combine elements, process data, or solve a problem.
If you miss this, you risk writing claims that either get rejected for being too similar to existing work or are so narrow they can be sidestepped.
The core is what gives your claims staying power. If you claim the right concept, your patent can cover different technical versions of your invention over time.
If you get it wrong, your claim might only protect today’s implementation — and be obsolete in a year.
The “what’s really new here?” question
A useful way to uncover your core is to keep asking one simple question: “What’s really new here?”
Don’t settle for your first answer. Push past surface features and dig into the deeper idea.
If your first answer is “it uses AI to recommend products,” ask again. Lots of systems do that.
Maybe your real novelty is “combining real-time inventory data with behavioral analytics to tailor recommendations.”
If your answer is “a tool for predicting mechanical failures,” ask again.
Maybe the real novelty is “detecting subtle vibration patterns in sensor data and mapping them to specific failure modes before they occur.”
The trick is to move from a general category into a specific, unique twist that you own.
Separating the core from the clutter
In most products, there are dozens of features, and it’s tempting to try to claim them all at once.
But not every feature is worth claiming. Many are just supporting acts for your main invention.
Trying to put them all in your primary claim makes it messy, harder to defend, and easier for competitors to design around.
Instead, think of your patent strategy like building a house. Your core inventive concept is the foundation.
You can always add more claims later to cover extra features — those are the rooms, the deck, the garage.
But your main claim should sit firmly on the foundation.
Looking for the hidden engine
Sometimes the true novelty of a software or AI invention isn’t visible to the end user at all.
The real breakthrough might be in a preprocessing step, a way of structuring data, or an internal feedback loop in the system.
For example, in an AI that recognizes objects in images, the novelty might be in a new way of labeling training data that cuts annotation time in half.
The user never sees this, but it’s what makes your invention possible.
If you miss this hidden engine when drafting, you leave a door open for others to copy the key part of your invention without infringing your claim.
Thinking in terms of relationships, not just parts
Software and AI inventions rarely hinge on one single component. They’re usually about how components work together.
Sometimes the novelty is in a relationship — data flowing from one module to another in a certain way, or a loop that feeds results back into an earlier stage for improvement.
If you can identify these unique relationships, you can write claims that are much harder to work around.
A competitor might swap out a component, but if the relationship is still the same, they could still infringe.
Testing your concept for strength
Once you think you’ve found your core inventive concept, stress-test it. Ask yourself:
If someone changes the hardware, does my claim still apply?
If someone swaps one algorithm for another, does my claim still apply?
If the invention is adapted to a different industry, does my claim still apply?
If the answer to all three is yes, you’ve probably got a strong core. If not, you might be focusing too much on a specific technical detail instead of the broader inventive idea.
Writing it in plain words first
Before you even think about legal claim language, try writing your core inventive concept in the simplest words possible, as if explaining it to a smart high school student.
If you can’t do that, you probably don’t fully understand your own invention’s core yet.
Plain language forces you to strip away unnecessary jargon.
Once you have this simple sentence, you can start layering in the technical and legal detail to turn it into a strong claim.
Turning the Core Into a Strong, Enforceable Claim
Once you know the beating heart of your invention, the next step is to wrap it in legal armor.
This is where the skill comes in — translating your inventive concept into precise claim language that’s broad enough to block competitors but solid enough to survive the patent examiner’s review.
Start with the legal category
Every claim starts by picking its type — method, system, or computer-readable medium.
The same inventive concept can be framed in all three categories to give you a layered defense.
For software and AI, method claims are common because they focus on the process rather than specific hardware.
System claims are useful when you want to protect a setup that ties hardware and software together.
Computer-readable medium claims cover the software stored in a tangible form.
Using multiple types of claims means you don’t put all your eggs in one basket. If your method claim gets challenged, your system claim might still hold.
Anchor it in concrete steps
Your claim should walk the reader through the invention in a logical order. Think about the input, the processing, and the output.
Each step should connect to the next. Even if you describe it broadly, the examiner needs to see a real, functional flow.
For example, instead of writing “receiving data, processing data, generating output,” you might say: “receiving sensor data from a plurality of sources, transforming the sensor data into a unified format, applying a trained predictive model to the transformed data, and outputting a classification indicating a predicted system state.”
The second version tells the examiner exactly how the invention moves from start to finish without locking you into unnecessary specifics.
Choose flexible but precise language
One of the hardest balancing acts in software claims is being precise without being restrictive. Words that seem harmless can narrow your protection dramatically.
For example, “transmitting over a wireless network” means you don’t cover wired systems. “Displaying on a touchscreen” excludes other types of displays.
If you want to keep it open, you can say “transmitting over a network” or “displaying on a user interface.”
This keeps the door open to future variations without making the claim vague.
Avoid “example trap” wording
When describing your invention in the claim, don’t fall into the trap of locking yourself into one embodiment by mistake.
Words like “wherein the system uses a convolutional neural network” mean you’ve limited the claim to CNNs.
A competitor could use a transformer model and escape infringement.
If your novelty isn’t tied to the type of model, you might write “applying a trained machine learning model,” and then in the description, you can give CNNs, transformers, and other architectures as examples.
That way, the claim stays broad, but you still have the technical support needed to satisfy patent rules.
Make relationships clear
The power of a software claim often comes from how elements interact, not just what they are.
If your modules or steps pass data in a unique way, make that relationship explicit in the claim.
For example, “transforming the data to a normalized format before applying the predictive model” is stronger than simply saying “transforming the data” and “applying the predictive model” as separate steps.
The relationship — that the transformation feeds the prediction — becomes part of the protection.
Guard against design-arounds
When you write a claim, think like a competitor trying to get around it.
If you can imagine an easy workaround that avoids one of your steps, you need to adjust your wording.
For example, if you claim “receiving data from a mobile app,” a competitor could use a web app and avoid infringement.
If you claim “receiving data from a client application,” they’re covered either way.
The goal is to close as many obvious loopholes as possible while still being honest about what your invention actually does.
Back it up in the description
Even the best-drafted claim can fail if your description doesn’t support it.
Patent law requires that you “enable” the invention — meaning your description must teach someone skilled in the field how to make and use it without undue effort.
For software and AI, that doesn’t mean giving away every line of code, but it does mean giving enough detail about the architecture, the data flow, and the steps so that your claim isn’t seen as empty words.
If you claim “applying a trained predictive model,” your description should explain what kinds of models could be used, how they might be trained, and what type of data they process.
Keep an eye on patent eligibility
For software and AI, especially in the US, you also need to be aware of the “abstract idea” issue.
Patent examiners often reject software claims if they seem to cover nothing more than a generic computer performing a known task.
To avoid this, your claim should show a technical improvement — something that changes how the system itself works, processes data, or interacts with hardware.
For example, “applying a model to recommend products” might be seen as an abstract business idea.
But “applying a model that dynamically adjusts its feature weights based on real-time inventory data received from distributed sensors” is more technical and harder to dismiss.
Wrapping It Up
Drafting claims for software and AI inventions isn’t about filling in a form. It’s about strategy, foresight, and precision. The claims are where your idea turns into enforceable rights. They define your territory in a competitive landscape where code can be rewritten overnight and competitors can pivot in a week.
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