Exploring the Impact of AI on Today's Counselling and Psychotherapy Practices

Artificial intelligence (AI) is transforming many fields, and counselling and psychotherapy are no exceptions. Here at St Andrews Counselling & Psychotherapy, we think carefully about how the integration of AI tools into mental health care is reshaping how therapists work and how clients receive support. This shift raises essential questions about the therapeutic relationship, the effectiveness of therapy, ethics, and the human connection in treatment. Exploring these changes helps us understand the opportunities and challenges AI brings to mental health services.

A digital assistant device in a therapy room, symbolising AI in counselling

How AI is Being Used in Counselling and Psychotherapy

AI applications in mental health range from chatbots to advanced data analysis tools. Some common uses include:

• Virtual therapy assistants: AI chatbots can provide immediate responses, be available 24/7, and offer coping strategies and emotional check-ins outside traditional sessions. Examples include Woebot and Wysa, which use natural language processing to facilitate what can appear to be therapeutic conversations.

• Screening and diagnosis: AI algorithms analyse speech patterns, facial expressions, and written text to detect signs of depression, anxiety, or other conditions. This helps clinicians identify issues earlier and tailor treatment plans.

• Personalised treatment plans: Machine learning models can recommend therapy approaches based on a client’s history and response to previous interventions.

• Monitoring progress: AI tools track mood changes and symptom patterns via apps or wearable devices, providing therapists with real-time data to adjust care.

  
  

These uses demonstrate how AI can help therapists expand access to mental health resources.

Benefits of AI Integration in Therapy

AI offers several advantages that can improve counselling and psychotherapy:

• Increased accessibility: AI-powered apps and chatbots provide support 24/7, reaching people who might not otherwise seek help due to stigma, cost, or location.

• Consistency and availability: Unlike human therapists, AI tools do not experience fatigue or scheduling conflicts, ensuring continuous support.

• Data-driven insights: AI can analyse large amounts of data quickly, revealing patterns that might be missed by human observation alone.

• Cost-effectiveness: Automated tools can reduce the burden on mental health systems by handling initial assessments or providing supplementary care.

  
  

Challenges and Ethical Considerations

Despite its promise, AI in counselling raises essential concerns:

• Loss of human connection: Therapy between two people relies heavily on empathy, trust, and nonverbal cues. AI works on algorithms, does not feel emotions or empathy and cannot fully replicate these human elements, which limits its effectiveness for clients.

• Privacy and data security: Sensitive mental health data must be protected. AI systems require strict safeguards to prevent breaches or misuse. Clients can inadvertently share sensitive information that is not kept private or secure.

• Bias and fairness: AI models trained on limited or biased data may produce inaccurate or unfair assessments, especially for underrepresented groups.

• Dependence on technology: Overreliance on AI tools might reduce face-to-face interactions, potentially weakening therapeutic relationships. There have been reports in the media of AI failing to pick up on subtle clues and safeguarding issues, which have posed a risk to clients.

  
  

Therapists and developers must carefully balance these risks with the benefits, ensuring AI supports rather than replaces human care.

Examples of AI Tools in Practice

Several AI tools have gained attention for their role in mental health:

• Woebot: A chatbot that uses cognitive-behavioural therapy techniques to help users manage mood and stress. It offers daily conversations and tracks emotional health.

• Tess: An AI mental health coach that delivers personalised text messages based on user responses, designed to provide emotional support between therapy sessions.

• Ginger: Combines AI with human coaches and therapists to offer on-demand mental health support through an app.

• Ellie: A virtual human interviewer developed by researchers to detect signs of PTSD and depression by analysing facial expressions and voice tone.

  
  

These examples highlight how AI can complement traditional therapy by providing scalable, accessible support. These examples of AI support are not meant to replace, but rather to offer something between sessions.

The Future of AI in Counselling and Psychotherapy

AI will likely become more integrated into mental health care, but it will not replace human therapists. Instead, it will serve as a tool to enhance their work. Future developments may include:

• Improved emotional recognition: Advances in AI could better interpret subtle emotional cues, making virtual interactions more empathetic.

• Hybrid models: Combining AI tools with human therapists to create personalised, flexible care plans.

• Greater accessibility: Expanding AI services to underserved communities and languages.

• Ethical frameworks: Developing clear guidelines to protect client rights and ensure responsible AI use.