The expansion of false images generated by artificial intelligence has driven the development of new tools designed to combat digital misinformation. Currently, the internet is saturated with manipulated photographs, videos, and memes, many of which are nearly indistinguishable from reality, fueling a growing wave of misinformation. In response to this phenomenon, various applications and platforms have emerged that can identify, with notable accuracy, images created or altered by AI. According to various reports, fraud related to AI-generated content caused losses exceeding $1.5 billion last year. Scams range from fake invoices and documents to justify business expenses, images of non-existent damage to property, to the dissemination of fictitious events on social media and news outlets, and even voice cloning to authorize bank transfers. In light of this situation, tools like IMGDetector.ai, RealReveal, Tenorshare Deepfake Detection, AI or Not, and Vericta have gained prominence. Many of them, available for free, allow users to detect synthetic images, analyze visual inconsistencies, and trace the digital footprints left by systems generating false images. Does an image still hold the same value as before? For Georgina Viaplana, co-founder and director of Vericta, the answer is yes, although she warns that the ease with which images are accepted without question has changed. "Precisely because an image holds so much power, it is tempting to manipulate it," she notes. Her company has developed technology capable of verifying in seconds whether an image or video is authentic or AI-generated. Viaplana emphasizes that trust in the authenticity of digital content is now a structural necessity for companies, especially when an image can imply direct costs. Examples of this can be found in the insurance sector, where claims are resolved based on images that may be manipulated, in e-commerce, or in the real estate sector. Labeling AI-generated images at the source could be a solution, although Viaplana warns that watermarks and metadata can be altered, and not all models follow the same standards. Hervé Lambert, head of Global Consumer Operations at Panda Security, agrees that these tools are useful and will continue to evolve, although he acknowledges that the battle between AI generators and detectors is ongoing. He highlights their value in professional fields such as media, justice, or law enforcement, but doubts their impact among the general public, especially in countries with low cybersecurity culture. "Most people do not verify news, let alone an image that reinforces their beliefs," says Lambert, who recalls that if 73% of Spaniards believe their phones do not need protection, it is unlikely they will verify the authenticity of an image. Lambert considers it desirable for all AI-generated images to be labeled, although he acknowledges that the lack of borders on the internet complicates the universal application of this measure.