Child sextortion in Maine: cases multiply twelvefold in a year as generative AI accelerates the abuse

By WGME · September 28, 2026.

In Bath, Maine, police chief Andrew Booth is more than familiar with what he himself describes as "a constant battle": sextortion cases, a form of sexual blackmail in which a criminal poses as someone else (catfishing) to get a minor to send sexually explicit images or videos and then extorts them, demanding money in exchange for not spreading the material. According to Booth, paying rarely closes the case: "Once you give a scammer money, they're only going to ask for more."

State data obtained by WGME's investigative team put the scale of the problem in perspective: sextortion reports in Maine rose from 109 in 2024 to 1,345 in 2025, an increase of more than 1,000% in a single year. The tipline of the National Center for Missing & Exploited Children (NCMEC), the leading U.S. organization fighting child exploitation, has already identified more than 150,000 images and videos as AI-generated child sexual abuse material, according to figures handled by the organization.

Maine responded in April 2026 with a law making it a crime to create, share and possess AI-generated child sexual abuse material. But Booth admits the law lags behind the technology: "AI is one of those new areas where police are on the defensive. We don't know enough and there aren't enough safeguards." Jamie Dorr, director and founder of the Midcoast Youth Center —a nonprofit in Bath offering after-school services for young people and support for homeless people— goes further: for her, not even the best parental controls are enough, because "these scammers are going to get around them", and she is calling for a federal-level response.

Our reading: this is exactly the kind of short-term harm that cannot be downplayed. Generative AI has broken the premise that underpinned classic sextortion —that a real compromising image of the minor was needed—; now an ordinary social media photo is enough to manufacture a convincing sexualized version, which multiplies the number of potential victims and helps explain a twelvefold jump in a single year, which the source attributes only in part to AI. It is a clear-cut example of dual use: the same ability to generate photorealistic images that drives creativity and productivity also makes abuse cheaper on an industrial scale.

There is also a paradox worth flagging. As industry context, quantifying hundreds of thousands of pieces of illegal material —like the more than 150,000 the NCMEC reports— is only feasible with automatic classification tools, although the source does not specify what methods the organization uses: the same family of technology that generates the harm is also, today, what makes it possible to detect it at scale. There, in miniature, is the pattern that recurs in every debate about AI governance: capability advances faster than safeguards, and closing that gap —age verification, image provenance marking, cooperation between platforms and prosecutors, technical training for local police like those in Bath— is not a regulatory luxury, it is the condition for society to reach with confidence the long-term benefits this technology promises in other areas. Ignoring that transition cost, or treating it as minor collateral damage, would be as naive as denying AI's potential to improve lives once it matures with the right protections.