Artificial intelligence tools like Midjourney, DALL-E, and Stable Diffusion are now generating images so realistic that they're spreading across social media faster than fact-checkers can debunk them. From a Pope in designer fashion to fake explosions near the Pentagon, these viral AI creations are raising urgent questions about how we verify what we see online.

What Made the Pope Image So Convincing?

In 2026, an image of Pope Francis wearing a Balenciaga puffer jacket became one of the year's most viral AI-generated photos, viewed millions of times and liked hundreds of thousands of times. The creator, experimenting with Midjourney, simply wanted to make surreal art. "I just thought it was funny to see the Pope in a funny jacket," the artist explained.

What made this image remarkable wasn't just its absurdity; it was its technical quality. The AI image displayed a hyperreal aesthetic that fooled many observers, including celebrity Chrissy Teigen, who tweeted, "I thought the pope's puffer jacket was real and didnt give it a second thought. no way am I surviving the future of technology." Despite telltale signs of AI creation, such as smeared details, the image spread like wildfire across social media platforms.

How Are AI-Generated Images Spreading Misinformation?

The Pope's puffer jacket was just the beginning. Throughout 2026, several high-profile AI-generated images went viral and created real-world consequences. In March, journalist Eliot Higgins, founder of the Bellingcat platform, created a series of images showing former President Donald Trump being arrested. Made with Midjourney, these images were viewed 6.7 million times and were intended to demonstrate the power of AI image creation tools.

Perhaps most concerning was an image of an explosion near the Pentagon that circulated on Twitter in May. While the official creator never revealed themselves, the images were quickly shown to be fake. However, the image stirred panic and confusion, even causing ripples in the stock market, demonstrating the potential misuse of AI technology for creating convincing fakes that spread faster than they can be fact-checked.

In August, AI-generated images of Paris overwhelmed by trash went viral on TikTok with over 450,000 views. The context seemed believable because garbage disposal workers had actually gone on strike earlier in the year. However, fact-checking site AFP traced the images to an artist known as Nik Art, who confirmed they were made with Midjourney.

Why Are AI Models Becoming Influencers?

The viral spread of AI-generated images has normalized AI-created content in unexpected ways. Milla Sofia, a 24-year-old virtual girl living in Helsinki, openly identifies as an AI creation on her Instagram bio. All of her pictures across social media platforms are AI-generated, yet she became viral when she shared a TikTok clip dressed in summer clothes against a backdrop of a field of flowers. Other TikTok users heaped on compliments despite her public announcement that she's an AI model. Sofia is an example of how AI-generated images and people are becoming more widely accepted in today's society, with some AI models even securing sponsorships from brands.

How to Spot AI-Generated Images Before They Spread

Understanding the distinction between AI-generated images and real ones used to be straightforward; you'd look for telltale signs like blurry details or unusual renderings of hands and feet. However, AI is getting smarter, and these clues are becoming less obvious. To help identify AI-generated images, experts recommend applying the SIFT method, a framework designed to verify visual content before sharing it.

• Stop: Take a moment to pause and critically evaluate the image before accepting it as real, rather than immediately sharing or believing it.
• Investigate: Dig deeper into the image by examining its details, searching for any inconsistencies or unusual elements that might indicate AI generation.
• Find Better Coverage: Look for additional sources or related information that can provide more context about the image's origin and authenticity.
• Trace the Original Context: Trace the image back to its original source to verify its legitimacy and prevent the spread of misinformation.

This method helps sort the real from the fake and keeps you clear of fake news. However, as AI tools become more sophisticated, staying vigilant is becoming increasingly difficult.

What Does This Mean for Art and Authenticity?

The rise of convincing AI-generated images has sparked significant debate about authenticity in visual arts. Boris Eldagsen's submission titled "Pseudomnesia: The Electrician" won the Sony World Photography Award in 2026, but Eldagsen turned down the award after revealing the winning piece was generated by AI. In subsequent interviews, he shared that he wanted to initiate a dialogue about the role of AI in the future of visual arts. Eldagsen's image, a haunting black-and-white portrayal, achieved viral status, demonstrating AI's ability to mimic reality convincingly. This incident has amplified discussions about AI's place in art, with many calling for clear differentiation between AI-generated and human-crafted works in competitions.

The challenge of distinguishing AI-generated content from authentic work extends beyond photography competitions. In January 2026, Instagram user Jos Avery confessed to Ars Technica that the images he posted were "AI-generated, human-finished." His growing base of followers had been amazed by what they believed was his technical skill and mastery of his craft. However, Avery couldn't bring himself to confess that AI did some heavy lifting in the artistic process. The question remains: if he hadn't revealed his behind-the-scenes process, would anyone have ever known the truth ?

As AI image generation tools become more accessible and powerful, the line between human creativity and machine-generated content continues to blur. The viral success of these images shows that the public is increasingly exposed to AI-generated visuals, whether they realize it or not. The challenge ahead lies not just in developing better detection methods, but in establishing clearer norms around disclosure and authenticity in an era where photorealistic AI images are becoming the norm rather than the exception.