The IWF’s AI and CSAM Report 2026 examines how generative artificial intelligence is increasingly used to produce child sexual abuse material (AI‑CSAM), lowering barriers for offenders and expanding the scale and speed of harm.
The report finds a rapid rise in AI‑generated sexualised images of children, including realistic depictions that do not rely on existing abuse material, making detection and takedown significantly more difficult. It highlights how offenders exploit open‑source AI tools, online communities, and image‑manipulation techniques to create and share CSAM, often targeting girls disproportionately.
The report concludes that current legal frameworks and platform policies are insufficient to address AI‑CSAM, calling for urgent regulatory updates, improved detection technologies, stronger industry accountability, and international cooperation to prevent the normalisation and proliferation of AI‑generated child abuse imagery.
Methodology
The report uses a mixed analytical approach combining quantitative data from IWF’s hotline reports with qualitative assessments of emerging AI‑CSAM trends. Analysts reviewed flagged content, monitored offender forums, and examined how generative AI tools are used to create or manipulate child abuse imagery. The methodology includes case studies, pattern analysis of reported content, and technical examination of AI‑generated images to identify common production methods and distribution channels.
The report also incorporates expert interviews and cross‑sector consultations to assess legal, technological, and policy gaps. Limitations include the evolving nature of AI tools and the difficulty of tracking content produced outside traditional CSAM ecosystems.
Citation
Internet Watch Foundation. (2026). Harm without limits: AI child sexual abuse material through the eyes of our analysts. https://www.iwf.org.uk/about-us/why-we-exist/our-research/how-ai-is-being-abused-to-create-child-sexual-abuse-imagery/
Record created:
15 September 2026
The IWF’s AI and CSAM Report 2026 examines how generative artificial intelligence is increasingly used to produce child sexual abuse material (AI‑CSAM), lowering barriers for offenders and expanding the scale and speed of harm.
The report finds a rapid rise in AI‑generated sexualised images of children, including realistic depictions that do not rely on existing abuse material, making detection and takedown significantly more difficult. It highlights how offenders exploit open‑source AI tools, online communities, and image‑manipulation techniques to create and share CSAM, often targeting girls disproportionately.
The report concludes that current legal frameworks and platform policies are insufficient to address AI‑CSAM, calling for urgent regulatory updates, improved detection technologies, stronger industry accountability, and international cooperation to prevent the normalisation and proliferation of AI‑generated child abuse imagery.
Methodology
The report uses a mixed analytical approach combining quantitative data from IWF’s hotline reports with qualitative assessments of emerging AI‑CSAM trends. Analysts reviewed flagged content, monitored offender forums, and examined how generative AI tools are used to create or manipulate child abuse imagery. The methodology includes case studies, pattern analysis of reported content, and technical examination of AI‑generated images to identify common production methods and distribution channels.
The report also incorporates expert interviews and cross‑sector consultations to assess legal, technological, and policy gaps. Limitations include the evolving nature of AI tools and the difficulty of tracking content produced outside traditional CSAM ecosystems.
Citation
Internet Watch Foundation. (2026). Harm without limits: AI child sexual abuse material through the eyes of our analysts. https://www.iwf.org.uk/about-us/why-we-exist/our-research/how-ai-is-being-abused-to-create-child-sexual-abuse-imagery/
Record created:
15 September 2026- artificial intelligence (AI) child sexual abuse material (CSAM) grooming
Related content
- < Previous Item
- Next Item >
