UK-based Internet Watch Foundation says it identified 8,029 AI-generated images and videos of realistic child sexual abuse in 2025, up 14% from 2024
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Context & Ripple Effects
The IWF had already documented generative AI’s use in abusive imagery in 2023, including about 3,000 images that breached UK law. Its later reporting of a sharp rise in AI-generated abuse videos during the first half of 2025 showed that the problem was moving beyond isolated examples.
This report extends that record into a full-year measure and sits alongside the IWF’s longer-running effort to make enforcement operational through hashes for known abusive images. It matters because realistic synthetic material expands the volume and type of content that safety teams must assess.
First-order effects
- The IWF’s identification and triage workload rises as realistic AI-generated abuse material continues to grow, adding a distinct synthetic-content category to existing CSAM reporting.
- Platforms that use IWF intelligence and matching tools face a larger set of suspected abusive material to prioritize for detection, review and removal.
Second-order effects
- The increase strengthens the practical case for combining known-content hashing with processes that can assess newly generated material, since synthetic files may not already exist in hash databases.
- UK rules targeting tools designed to produce CSAM make the findings more relevant to enforcement agencies and services whose products or infrastructure can be used to create or distribute such material.
Third-order effects
- If synthetic CSAM keeps increasing, child-safety enforcement will shift from primarily blocking recirculated files toward detecting and investigating newly created content at scale.
- The pattern points to public-safety AI governance becoming a product and infrastructure issue: model developers, hosting services and platforms may face closer scrutiny over prevention and reporting capabilities.
The trend: Generative AI is expanding the child-safety enforcement surface by increasing the supply of realistic, newly created abusive content that cannot be addressed by reuse detection alone.