By Jasdev Bhakar
An Examination of Emerging Uses, Benefits, and Risks of Generative AI for Maladaptive Daydreamers
Why Is AI Becoming a Mental Health Resource?
It is the middle of the night. You are alone in the dark; the only light is coming from your phone screen. You type out a problem that has been weighing heavily on your mind and, within seconds, receive what appears to be understanding, reassurance, and perhaps even a path forward. It can feel as though the presence on the other side of the conversation understands exactly what you are thinking. However, it is not a friend, therapist, or someone drawing upon lived experience. It is an AI chatbot.
For many people, this scene has become increasingly familiar. Generative AI platforms such as ChatGPT, Google Gemini and Claude, among others, are now used to help navigate countless aspects of daily life. Whether seeking travel advice, recipe ideas, help drafting an email, or answers to complex questions, AI can provide immediate assistance at any hour. It is therefore unsurprising that these platforms have also become, albeit unintentionally, a source of mental health support.
Available 24 hours a day, these platforms offer users a private space to discuss thoughts, emotions, and concerns. They can help organise complex feelings, provide educational information about mental health, and encourage self-reflection. For many people, AI is appealing because it is accessible, inexpensive, and available without long waiting lists or the anxiety that can accompany discussing deeply personal issues face-to-face.
However, accessibility should not be confused with expertise. AI can be a useful tool, but it also has limitations.
Understanding AI’s Role and Limitations
Generative AI platforms often make you feel as if you are talking to a thoughtful and knowledgeable human, because that is what they are designed to do. However, AI responses are generated by sophisticated language modelling, enabling them to recognise patterns in human communication and produce plausible, contextually appropriate replies.
Several processes occur when a user engages with a generative AI platform:
Pattern Recognition
The AI analyses a user’s words and identifies patterns associated with emotions, concerns, and topics based on the large amounts of text it was trained on, including books, articles, websites, and other written material.
Context Tracking
The system retains information from the current conversation, allowing it to follow the flow of discussion and respond in ways that appear consistent and relevant.
Predictive Response Generation
Rather than understanding emotions in a human sense, AI predicts which words are most likely to be helpful, supportive, or informative based on the conversation context.
Safety Mechanisms
Most major AI systems include safeguards designed to identify signs of self-harm or dangerous requests and respond when these situations arise.
While these capabilities can make AI feel supportive, they also reveal important limitations.
Lack of Nonverbal Information
Unlike a therapist, AI cannot observe facial expressions, body language, tone of voice, or behavioural changes. These cues often provide critical information about a person’s wellbeing and can influence how a mental health professional responds.
The Validation Problem
Generative AI is generally designed to be cooperative and helpful. While modern systems are increasingly capable of challenging inaccurate assumptions, they may still occasionally reinforce mistaken beliefs, unhealthy thought patterns and behaviours.
Bias and Limited Context
AI systems reflect patterns found within their training data. As a result, cultural assumptions, societal biases, and incomplete information can sometimes influence responses. Experiences that fall outside common frameworks may be misunderstood.
Data Privacy Concerns
Many users share highly personal information with AI systems. Questions remain about how this data is stored, processed, and potentially used in the future. Users should be aware that privacy practices vary across platforms.
These strengths and limitations become particularly relevant when considering how AI is being used by people with Maladaptive Daydreaming (MD).
Why People with Maladaptive Daydreaming Turn to AI
People with MD often face unique challenges when seeking support. Although awareness of the condition is growing, MD is not currently recognised as a formal diagnosis in the Diagnostic and Statistical Manual of Mental Disorders (DSM). As a result, many individuals struggle to find professionals who understand their experiences, access appropriate treatment, or receive reassurance that what they are experiencing is real and worthy of attention. For some, this can lead to years of searching for explanations and attempting to understand their own patterns of daydreaming.
In the absence of widely available specialist support, AI may appear to fill some of these gaps by offering information, opportunities for self-reflection, and a space to discuss experiences that may be difficult to explain elsewhere. Thus helping to explain why AI has become an increasingly popular tool within the MD community.
How People with Maladaptive Daydreaming Are Using AI Today
People with MD are using AI tools in a variety of ways, many of which can enhance or extend their daydreaming experiences.
Record-Keeping
AI platforms can help organise complex daydream narratives, timelines, character relationships, and fictional worlds.
Visual Aids
AI image-generation tools are being used to create visual representations of daydream characters, locations, and scenes.
Interactive Roleplay
Interactive platforms allow users to create and interact directly with fictional characters through conversational roleplay, creating highly immersive experiences.
Content Generation
Generative AI tools can help develop storylines, dialogue, worldbuilding details, and character backstories, often producing large amounts of content in a short period of time.
Multimedia Immersion
AI music-generation tools can create customised songs and soundtracks that complement specific daydream scenarios.
Potential Risks for People with Maladaptive Daydreaming
For some maladaptive daydreamers, AI can be used without significant problems. However, for others, it can exacerbate the difficulties they experience due to MD.
More research is needed to understand the long-term effects of these interactions, but they highlight why thoughtful use of AI is particularly important for people with MD.
Using AI to Support Recovery and Self-Management
While AI can facilitate maladaptive daydreaming, it can also be used to support self-awareness and behaviour change. Rather than acting as a creative collaborator, AI may be most helpful when used as a structured coaching or self-reflection tool.
Potential uses include:
- – Tracking daydreaming triggers and behavioural patterns
- – Monitoring progress and identifying successful coping strategies
- – Supporting reflection on emotional needs and experiences
- – Assisting with goal-setting and habit formation
- – Providing grounding exercises and practical problem-solving support
Used in this way, AI may help individuals remain focused on their real-world wellbeing rather than becoming further immersed in fantasy.
Practical AI Prompts for Self-Management
One way to use generative AI constructively is through prompts inspired by Cognitive Behavioural Therapy (CBT) principles.
1. Intercepting the Compulsion
When the urge to daydream becomes intense, this prompt encourages users to pause and identify what is happening in the present moment.
Copy and Paste Prompt
“Act as a strict, non-judgmental CBT-based accountability coach. I am experiencing a strong urge to maladaptive daydream right now. Do not write stories or discuss characters. Ask me three brief questions, one at a time, to help identify my immediate real-world trigger. Then guide me through a two-minute grounding exercise.”
2. Deconstructing the Fantasy
This prompt encourages reflection on the emotional needs underlying recurring daydream themes.
Copy and Paste Prompt
“I am trying to understand the themes in my maladaptive daydreams. I will describe a repetitive fantasy scenario. Do not expand on the plot. Analyse which unmet emotional needs this scenario may represent, such as validation, safety, connection, achievement, or control. Then suggest two realistic actions I can take today to meet those needs in real life.”
3. Harm Reduction
For those attempting to reduce rather than eliminate daydreaming, structured limits may be helpful.
Copy and Paste Prompt
“Help me create a scheduled daydreaming plan. I want to limit my daydreaming to 20 minutes per day. Help me design a realistic daily routine and a step-by-step ritual that signals when daydreaming time is over, and it is time to return to reality.”
4. Real-World Project Management
Many people report daydreaming more when faced with overwhelming or difficult tasks.
Copy and Paste Prompt
“I am procrastinating on a real-life task because it feels overwhelming, and I am tempted to escape into a daydream. The task is: [INSERT TASK]. Break it into four micro-steps, each taking less than five minutes. Keep the response concise and encourage me to begin the first step immediately.”
These prompts are not a substitute for professional mental health treatment and may not be suitable for everyone.
Purpose-Built Mental Health Apps
It is important to recognise that not all AI tools function in the same way. Generative AI platforms are designed for open-ended conversation, whereas some digital mental health apps are designed to support emotional wellbeing through evidence-based approaches. One example is the mental health app Wysa, which combines conversational AI with techniques drawn from CBT, mindfulness, and stress-management approaches. It has been approved for use in the UK’s health service, and many of its core features are available free of charge.
Finding the Right Balance
AI is neither a therapist nor a villain. It is a powerful technology that is increasingly accessible at times when people are seeking answers, comfort, or understanding. For people with MD, AI can serve a variety of functions. It can deepen immersion in daydream worlds, whilst also supporting users in developing coping strategies and staying connected to their real-world goals.
The important question is not whether people with MD should use AI, but how they use it. The goal should be to ensure that technology supports engagement with real life rather than becoming an increasingly sophisticated escape from it.