How to Tell If an Image Is AI-Generated: AI Detectors & SynthID

How to Tell If an Image Was Made by AI: A Practical Guide to AI Image Detectors and SynthID

A few years ago, seeing a photo online usually meant one of two things: someone had taken it with a camera, or a designer had edited it using software such as Photoshop. That assumption is becoming harder to make.

AI image generators have improved dramatically. Today, a detailed image can be created within seconds and look surprisingly realistic. It could be a portrait of a person who does not exist, a realistic-looking news scene, or even a beautiful location that was never photographed in the real world.

Once an image is shared on Facebook, Instagram, X, or a website, identifying its origin becomes even more difficult. Cropping, resizing, compression, filters, and screenshots can remove some of the information that originally existed in the file.

The good news is that you do have ways to investigate. Several AI image detectors can analyze an image for signs of synthetic generation, while technologies such as Google's SynthID can provide a different kind of clue by looking for an invisible watermark associated with supported Google AI content.

None of these methods should be treated as an infallible answer. The most useful approach is to combine several signals rather than trusting a single result.

What Is an AI Image Detector?

An AI image detector is a tool designed to estimate whether an image was likely generated or manipulated using artificial intelligence.

Different detectors use different approaches. Some analyze pixel-level patterns, textures, image statistics, and other visual characteristics. Others are trained to recognize patterns associated with particular image-generation systems. Some verification systems take a completely different approach by looking for embedded watermarks or content-provenance information.

This is why two detectors can sometimes disagree. One may report that an image is probably AI-generated, while another may return an uncertain result. That does not automatically mean one of them is broken. They may simply be analyzing different characteristics or have been trained on different datasets and models.

AI image generation is also moving quickly, which makes detection an ongoing challenge.

1. AI or Not

AI or Not is one of the easier options for checking whether an image may have been generated by AI.

You upload an image and the service analyzes it before returning a detection result. It can also be useful when checking other forms of synthetic media.

If you are investigating a suspicious image for the first time, it can serve as a useful starting point. However, its result should be considered a detection signal rather than a final verdict.

Best use: A quick first check when you want an initial indication of whether an image may be AI-generated.

2. Sightengine

Sightengine takes another approach to AI-generated image detection. Its AI-generated image detection technology analyzes the visual content of an image rather than simply depending on metadata.

That distinction matters because metadata can disappear. An image may lose its original EXIF information after being edited, exported, uploaded to a social network, or converted into another format.

Sightengine can therefore be useful as a second opinion when another detector has already raised a suspicion.

Best use: Cross-checking a suspicious image with a detector that focuses on the visual content itself.

3. Illuminarty

Illuminarty is another option for analyzing images for signs of AI generation.

The main advantage of using a separate detector is comparison. If one service flags an image but another gives a completely different result, you should be cautious about drawing a conclusion.

On the other hand, if several independent systems point in the same direction, that agreement gives you more reason to investigate the image further.

It is still important to remember that agreement between detectors is not the same thing as absolute proof.

4. WasItAI

WasItAI is an AI image detector designed to help determine whether an image was likely created by artificial intelligence or captured by a camera.

You can upload an image or paste an image URL, and the service analyzes it for patterns associated with AI-generated content. It can also provide a confidence level and, when the evidence is strong enough, an indication of the likely AI generator behind the image.

One useful feature is that WasItAI works directly in a web browser, including on mobile devices, without requiring an account for its free checks. The service says it currently covers more than 29 AI image generators.

However, its result should still be treated as evidence rather than absolute proof. Screenshots, heavy compression, cropping, and extensive editing can make AI detection more difficult.

Best use: A quick and convenient second opinion when you want to check whether a suspicious image may have been AI-generated.

Google SynthID: A Different Way to Check an Image

AI image detectors are not the only way to investigate an image. Google's SynthID takes a fundamentally different approach.

Developed by Google DeepMind, SynthID is a technology designed to add an invisible digital watermark to content generated by supported Google AI systems.

Unlike a traditional watermark that appears as a visible logo or piece of text in the corner of an image, a SynthID watermark is designed to be imperceptible to the human eye.

This means you normally cannot look at a picture and simply see the SynthID watermark. Specialized systems need to check for it.

This is an important distinction. A conventional AI detector may estimate whether an image looks AI-generated. SynthID can provide a different type of evidence by checking for a watermark associated with supported Google AI content.

How to Check an Image for SynthID Using Gemini

One of the most useful things for everyday users is that you can ask Gemini to check an uploaded image for SynthID.

If you have an image and suspect that it may have been generated or edited using Google's AI tools, upload the image to Gemini and ask it to check for SynthID.

You can use a prompt such as:

Check this image for SynthID.

For a more specific request, you can write:

Was this image generated or edited by Google AI? Please check whether it contains a SynthID watermark.

Gemini can attempt to determine whether a SynthID watermark is present and, when detected, provide information indicating that the content may have been generated or edited using supported Google AI systems.

This makes Gemini particularly useful when your main question is not simply, “Does this picture look like AI?” but rather, “Could this particular image have come from Google's AI tools?”

How Does SynthID Work?

The basic idea is relatively straightforward, although the underlying technology is much more sophisticated.

When supported Google AI systems generate content, SynthID can embed an invisible watermark into the content. In the case of images, the watermark is incorporated into the image information in a way that is not normally visible to people.

Google DeepMind says SynthID is designed to remain detectable through a number of common modifications, including certain crops, filters, color adjustments, and compression.

That does not mean every possible edit will leave the watermark perfectly detectable. Severe or unusual manipulation can still make verification more difficult.

The important point is that SynthID is designed to provide provenance information without putting a visible label across the image.

Does Finding SynthID Prove an Image Is 100% AI-Generated?

Finding a SynthID watermark can be a strong indication that an image is associated with supported Google AI generation or editing. But it is important not to misunderstand what the result means.

SynthID does not tell you the complete history of an image. It is not a universal detector for every AI model available on the internet.

For example, an image generated with Midjourney, Stable Diffusion, or another company's AI system would not normally contain Google's SynthID watermark simply because it is AI-generated.

The reverse is also important.

No SynthID detected does not mean the image is definitely real.

It may simply mean that no Google SynthID watermark was found. The image could have been generated using another AI system, or the watermark may no longer be reliably detectable after significant manipulation.

Remember: “No SynthID found” should be understood as “no detectable Google SynthID watermark was found,” not as proof that an image is authentic.

Google AI Images and SynthID

Google has incorporated SynthID into supported AI-generated content, including its Gemini image-generation ecosystem.

This is particularly useful because it gives users a way to investigate images that may have originated from Google's own AI tools rather than relying entirely on general-purpose AI detection models.

If you receive an image and believe it may have been created with Gemini or another supported Google AI system, checking for SynthID is therefore a sensible step.

Google's SynthID Detector

Google has also introduced a dedicated SynthID Detector for checking AI-generated content for SynthID watermarks.

Google DeepMind has described the detector as a way to identify SynthID watermarks in supported image, video, and audio content. Google has also been working with journalists and media professionals around this technology.

For many ordinary users, however, asking Gemini to check an uploaded image can be the simpler option.

Don't Depend on a Single AI Detector

Imagine that you find a highly realistic image on Facebook and something about it feels suspicious.

Uploading it to one website and accepting the result immediately may not be the best approach. A better method is to compare several different kinds of evidence.

1. Start with a general AI detector. Use a service such as AI or Not to get an initial indication.
2. Get a second opinion. Try another service such as Sightengine or another independent detector.
3. Check SynthID when Google AI may be involved. Upload the image to Gemini and ask it to check for SynthID.
4. Look at metadata and content credentials. These may provide useful information about how a file was created, although they can be removed or changed.
5. Investigate the original source. Find out where the image first appeared, who published it, and whether there is an earlier trustworthy context for it.

That final step is often overlooked. In many real-world situations, finding the original source can tell you more than a detector score.

Can You Spot AI Images Just by Looking at Them?

Sometimes, yes. But it is becoming much harder.

Older AI image generators often produced obvious mistakes. Hands could have the wrong number of fingers, text in the background could look like meaningless symbols, and reflections sometimes failed to match the objects they were supposed to represent.

Modern image-generation models have improved significantly, so those clues are no longer dependable on their own.

Still, it can be worth checking small details when something looks suspicious.

• Look closely at hands and fingers.
• Check small text, signs, and labels in the background.
• Compare reflections with the objects producing them.
• Look for unusual shadows or inconsistent lighting.
• Examine faces, teeth, eyes, and small physical details.
• Pay attention to objects that appear strangely repeated or distorted.

These clues should be treated as hints rather than proof. A real photograph can contain strange-looking details because of perspective, compression, motion blur, or editing, while a modern AI image can sometimes look almost flawless.

What About Metadata and Content Credentials?

Metadata can sometimes provide useful information about an image's origin. Depending on how a file was created, it may contain information about the camera, software, creation process, or other technical details.

Content Credentials and C2PA-based provenance systems can provide another layer of information about the history of digital content.

There is one major limitation, though: metadata is fragile. Editing an image, taking a screenshot, converting the file, or uploading it through certain platforms can remove or alter metadata.

That is one reason invisible watermarking technologies such as SynthID are interesting. They provide a signal that is separate from ordinary file metadata.

Why AI Image Detectors Can Get Things Wrong

AI detection is not a simple “real or fake” test.

A detector is making an assessment based on the information available to it and the technology behind the detection model. As image generators improve, some of the visual patterns that detectors previously relied on can become harder to distinguish.

Image editing can make the problem even more complicated. Resizing, cropping, heavy compression, filters, screenshots, and other transformations may affect detection performance.

The same limitation applies to watermark-based systems. SynthID is designed to withstand a range of common modifications, but extreme manipulation can still affect detection reliability.

So if one detector says “AI-generated,” it is better to interpret that as evidence worth investigating rather than an unquestionable verdict.

The Most Reliable Way to Check an AI Image

There is no single tool that can reliably answer every AI-image question.

A practical verification process looks something like this:

Visual Check → AI Detector → Second Opinion → SynthID → Provenance → Original Source

Start by looking at the image yourself. Then use a general AI detector. If the result matters, cross-check it with another service.

If there is a possibility that Google AI was involved, check the image for SynthID through Gemini. After that, examine any available metadata or content credentials and, most importantly, investigate the image's original source.

Combining these methods gives you a much stronger basis for making a judgment than relying on a single percentage score.

Final Thoughts

AI has changed not only the way images are created, but also the way we need to evaluate what we see online.

A realistic-looking image is no longer enough to prove that something actually happened. At the same time, an unusual-looking image is not automatically AI-generated. Modern AI models can produce highly realistic images, while real photographs can also contain strange details because of lighting, perspective, compression, or editing.

If you want to check a suspicious image, I recommend starting with AI or Not because it is simple to use and provides a quick initial assessment. You can then compare the result with another AI image detector such as Sightengine, Illuminarty, or WasItAI. Using more than one detector can give you a better overall picture than relying on a single score.

From my own experience testing AI-generated and edited images, detector results should be treated as clues rather than absolute proof. The same image can sometimes receive different results from different detection services, particularly after it has been resized, compressed, cropped, filtered, or shared through social media. This is why I would not recommend declaring an image “fake” based on one detector result alone.

If you suspect that an image may have been created or edited using Google's AI systems, checking for SynthID is another useful step. You can upload the image to Gemini and ask it to check for a SynthID watermark. A detected SynthID watermark can provide useful evidence that the image is associated with supported Google AI content, although the absence of a SynthID watermark does not prove that an image is authentic.

For important situations, I recommend using a combination of methods:

Visual inspection → AI or Not → Second detector → SynthID → Metadata/Content Credentials → Original source

This approach is especially important when an image is connected to breaking news, politics, accidents, someone's identity, financial claims, or other information that could cause real-world harm if it is misleading.

The goal of AI-image verification is not simply to label every image as “AI” or “real.” The more useful question is: Where did this image come from, what evidence supports its origin, and can the claim surrounding it actually be trusted?

So, if you come across a suspicious image online, don't immediately trust it—and don't immediately call it fake either. Check it first, compare the evidence, and verify the original source before sharing it.

What About the Future of AI Image Detection?

One question is becoming increasingly important: Will we still be able to tell whether an image was created by AI in the future?

The honest answer is that identifying AI-generated images may become much harder.

As image-generation models continue to improve, the obvious visual mistakes that people traditionally looked for—such as unnatural hands, strange text, inconsistent shadows, or unusual facial details—may become less useful. Future AI-generated images could become nearly impossible to distinguish from real photographs simply by looking at them.

However, that does not necessarily mean AI-generated images will become impossible to identify.

The future of image verification is likely to depend less on simply asking, “Does this image look like AI?”, and more on asking, “Can we verify where this image came from?”

Technologies such as invisible watermarks, Content Credentials, C2PA-based provenance, and other authentication systems could become increasingly important. Instead of relying entirely on visual clues, these technologies can provide information about how content was created, modified, or published.

At the same time, AI detection systems will continue to evolve alongside image-generation models. This means the tools we use today may not always work equally well in the future, but new verification methods are likely to emerge as the technology develops.

So, I don't think the future will necessarily be a world where AI images are impossible to identify. It may simply become a world where identifying them requires more than looking at the image itself.

That is why learning about provenance, watermarking, Content Credentials, and reliable verification tools is becoming just as important as learning how to spot visual AI artifacts.

In the future, the most reliable question may not be “Does this image look real?” but rather “Can its origin be verified?”