AI and its impact on child sexual abuse material
How AI Is Changing Child Sexual Exploitation
A child no longer has to be involved in creating a sexually explicit image to become a victim of online sexual exploitation. Today, an ordinary photograph from a birthday party, a
school event, or social media may be enough for Artificial Intelligence (AI) tools to generate sexually explicit content.
In 2023, the National Center for Missing & Exploited Children (NCMEC) received more than 31 million CyberTipline reports of suspected child sexual abuse material (CSAM), including 4,700 reports involving generative AI. The Internet Watch Foundation (IWF) also assessed 8,029 AI-generated images and videos depicting realistic child sexual abuse in 2025. On a single dark web forum, nearly 14,000 suspected AI-generated images were identified within one month. These figures show that AI-generated CSAM is no longer a concern for the future. It is already changing how child sexual exploitation occurs online.
While public discussions often focus on deepfakes, they tell only one part of the story. AI is reshaping who can become a victim, how abusive content is created and shared, and the challenges involved in identifying victims, supporting survivors, and investigating these crimes.
More Than Just a Change in Terminology
Before discussing the role of AI, it is important to understand why the language around child sexual exploitation has changed. For many years, the term child pornography was widely used in research, media reports, and legal systems. Today, most child protection organisations, researchers, and law enforcement agencies use the term child sexual abuse material (CSAM) instead.
The change isn’t just about using different words, this reflects a different way of understanding what these images actually represent. Unlike pornography which involves consenting adults, children cannot consent to sexual activity or to the creation of sexually explicit images. These images are evidence of child sexual abuse and exploitation. Using the term child sexual abuse material shifts the focus back to the child and the harm they have experienced rather than treating the material as another category of explicit content.
The change in terminology also reminds us that the harm does not end when an image is created. Every time the material is viewed, shared, edited, or redistributed, the abuse continues, leaving the child vulnerable to repeated victimisation. How AI Is Changing Child Sexual Exploitation
Child sexual exploitation didn’t begin with AI. Children were being exploited online long before generative AI became widely available. What AI has done is change how easily abusive content can be created, how quickly it can spread, and who can become a victim.
In the past, creating child sexual abuse material usually involved direct contact with a child, existing abuse images, image editing software. Today, realistic sexually explicit images can be generated from an ordinary photograph or even a text prompt. Many of these tools are inexpensive, freely available, and require very little technical knowledge. As a result, creating abusive content has become easier than ever before.
Perhaps the most disturbing change is that a child no longer needs to be photographed in a sexually explicit situation for abusive images of them to be created. A photograph from a school website, a family gathering, or a social media account may be enough. AI can manipulate these ordinary images into realistic sexually explicit content, often without the child or their family ever knowing. Some children only discover these images after they have already been shared online.
Reports from UNICEF, the Internet Watch Foundation (IWF), and WeProtect Global Alliance have warned that AI is lowering the barriers for offenders. What once required advanced editing skills can now be done within minutes using widely available AI tools. As a
result, abusive content has become faster, easier, and far more accessible. This has contributed to a growing volume of AI-generated CSAM and has created new challenges for investigators to distinguish real abuse from synthetic material.
These developments show that AI has not just replaced existing forms of child sexual exploitation. Instead, it has expanded them. The technology has created new ways to exploit children while making existing forms of abuse easier to create, manipulate, and distribute. The impact of AI isn’t limited to image generation either. Experts have also raised concerns that generative AI may also be used to create convincing fake identities, impersonate children or trusted adults, and automate conversations that may facilitate online grooming. Although research in this area is still developing, these developments suggest that AI could change not only how abusive images are created, but also how offenders approach and manipulate potential victims.
Offenders can create or manipulate sexually explicit images of a child and use them to threaten, blackmail, or pressure victims into sending money, sharing additional images, or complying with other demands. Even when victims know the image is fake, the fear that others may believe they are real can cause significant emotional distress and place children at risk of further exploitation.
The Hidden Harm Behind AI-Generated CSAM
One of the biggest misconceptions about AI-generated child sexual abuse material is that it does not create “real” victims because the images may not involve physical abuse at the time they are created. However, this assumption overlooks the fact that sexual exploitation is not defined only by physical contact. When AI is used to create sexually explicit images of an identifiable child from an ordinary photograph, that child loses control over how their image is used. At the same time, AI can also generate entirely synthetic images that do not depict an identifiable child, raising separate concerns about the normalisation of child sexual abuse, the demand for abusive material, and the challenges faced by law enforcement.
For many children, discovering that these images exist can be frightening. It may leave them feeling ashamed, anxious, or as though they have lost control over how their image is being used, and who has access to it. They may wonder who has seen the image, where it has been shared, or whether other photographs of them could also be misused. This uncertainty itself can create ongoing stress long after the image has been created.
Unlike many other forms of abuse, the harm does not end with a single incident. Once an image enters the online environment, it can be copied, altered, and redistributed repeatedly across websites, messaging platforms, and online communities. Unlike physical evidence that can be recovered or removed, digital images can continue to circulate for years, making it difficult for victims to know whether the abuse has truly ended.
Research has shown that the effects of online child sexual exploitation can continue long after the images are created or discovered. Some survivors describe feeling as though they are constantly being watched or worrying that someone they meet may have seen the images. Others avoid social media, become hesitant to form new relationships, or struggle to trust others because they no longer feel in control of how their image is being used. For children and adolescents, these experiences can affect friendships, school, confidence, and their sense of safety during the important years of development.
The impact is rarely limited to the child. Parents and caregivers may experience guilt, fear, anger, or helplessness after learning that their child’s image has been manipulated or shared online. Schools, mental health professionals, and child protection services may also become involved in helping children cope with the emotional impact. What began as the misuse of a single photograph can affect an entire family and the people supporting that child.
New Challenges for Investigators and Child Protection Agencies
AI-generated child sexual abuse material (CSAM) has created new challenges for investigators and child protection agencies. In some cases, investigators must determine whether an image depicts a real child, has been digitally manipulated, or has been generated entirely by AI. Answering these questions can take time and often requires specialised digital forensic expertise, particularly when there is uncertainty about whether a real child may be at risk. AI-generated images can also make victim identification more difficult. In some investigations, photographs contain details that help investigators identify a child or determine where abuse occurred. When images are generated or heavily manipulated by AI, these clues may be altered or removed, making it more difficult to identify victims or establish whether an actual child is involved.
As AI-generated CSAM becomes more common, investigators are having to adapt to new forms of digital evidence. This has increased the need for specialised training, improved forensic techniques, and closer collaboration between law enforcement agencies, technology companies, and child protection organisations. Responding effectively will require not only new technology but also the expertise and judgement of the professionals working to protect children.
Can AI Also Help Protect Children?
Although generative AI has created new opportunities for child sexual exploitation, it is also becoming part of the response. Child protection organisations, researchers, and technology companies are exploring how AI can be used to detect child sexual abuse material (CSAM), support investigations, and improve online safety. Rather than replacing investigators, these tools are intended to help them manage the growing number of reports and identify cases that may require immediate attention.
One way AI can help is by detecting known CSAM more quickly and identifying images that have been copied, altered, or shared across different online platforms. It can also help identify patterns in offending behaviour and flag content that may require further investigation. As the amount of online content continues to grow, these tools can reduce the time spent on routine tasks, allowing investigators to focus more on identifying victims and protecting children.
However, AI is not a complete solution. Like any technology, it can still make mistakes, overlook important details, or incorrectly classify content. Child protection decisions cannot rely on AI alone because understanding the context of an image or online interaction often requires human judgement. Investigators, digital forensic specialists, and child protection professionals continue to play an essential role in assessing evidence, identifying victims, and supporting children throughout the investigation process.
For this reason, many experts view AI as one tool within a broader child protection response rather than a solution on its own. Reports from UNICEF, the U.S. Department of Homeland Security, and WeProtect Global Alliance emphasise that protecting children requires more than new technology. Effective responses also depend on strong laws, cooperation between countries, responsible action by technology companies, and continued investment in child protection services. As AI continues to evolve, using it responsibly alongside human expertise may become an important part of preventing online child sexual exploitation.
What Needs to Happen Next?
There is no single solution to AI-generated child sexual abuse material (CSAM). As generative AI continues to develop, efforts to protect children will also need to adapt. Governments, technology companies, law enforcement agencies, researchers, educators, and child protection organisations all have an important role in reducing the risks associated with these technologies.
In India, there is currently no single law that deals exclusively with AI-generated child sexual abuse material. However, this does not mean that such content exists in a legal grey area. Depending on the circumstances, offences involving AI-generated CSAM may be addressed under existing laws, including the Protection of Children from Sexual Offences (POCSO) Act, the Information Technology Act, and relevant provisions of the Bharatiya Nyaya Sanhita. The Government of India has also stated that existing legal safeguards apply to harms arising from AI while work on broader AI governance continues.
Technology companies can also help by introducing stronger safeguards into AI systems, such as improving the detection and removal of abusive content, and responding quickly to harmful material when it is identified. At the same time, laws and policies will need to keep pace with advances in AI. Because online child sexual exploitation often crosses national borders, international cooperation will continue to be essential.
Prevention doesn’t stop with laws or technology either.
Parents, caregivers, teachers, and young people need to understand that an ordinary photograph shared online today can be manipulated in ways that were almost unimaginable only a few years ago. That doesn’t mean children should stop using the internet or avoid social media altogether. Rather, it simply highlights the growing importance of digital safety, responsible online behaviour, and open conversations about the risks of sharing images online.
Above all, it’s important not to lose sight of the children at the centre of this issue.
AI may have changed how child sexual exploitation occurs, but it has not changed its impact on victims. Whether abuse involves a camera, digital image manipulation, or generative AI, the consequences for children are real and long-lasting. As technology continues to evolve, protecting children, supporting survivors, and preventing further harm must remain the priority.
Article by: Anita Antony
Date: 02-09-2026
REFERENCE
Department of Homeland Security. (2024). Artificial intelligence and combatting online child sexual exploitation and abuse.
Internet Watch Foundation. (2026). AI-generated child sexual abuse: 2026 report on trends, data & human impact.
Ministry of Electronics and Information Technology, Government of India. (2026, March 11). Legal safeguards in place to prevent potential harms that may arise from AI and related technologies. Press Information Bureau.
National Center for Missing & Exploited Children. (2024). Generative AI CSAM is CSAM. https://www.missingkids.org/blog/2024/generative-ai-csam-is-csam
Pfefferkorn, R. (2025, July). Addressing AI-generated child sexual abuse material: Opportunities for educational policy. Stanford Institute for Human-Centered Artificial Intelligence.
RAINN. (n.d.). What about AI-generated CSAM—Like deepfakes?
UNICEF. (2026, February). Artificial intelligence and child sexual abuse and exploitation. Issue Brief.
WeProtect Global Alliance. (2025). The role of artificial intelligence (AI) in proliferating and tackling child sexual abuse content online.
Canadian Centre for Child Protection. (2017). Survivors’ survey: Executive summary 2017.
https://content.c3p.ca/pdfs/C3P_SurvivorsSurveyExecutiveSummary2017_en.pdf