Australia's mental health sector is witnessing a cautious embrace of artificial intelligence (AI) tools. While AI in mental health care is still emerging, growing evidence shows increasing interest from both the public and professionals. Globally, digital mental health solutions expanded during the COVID-19 pandemic, and Australia was no exception – over 466,000 Australians used digital mental health interventions between 2014 and 2020, with a sharp uptick after 2017 health.gov.au. Today, new AI-driven applications (from chatbots to data analytics) promise to help bridge gaps in the strained mental health system.
This article provides a comprehensive overview of how AI is currently being used in mental health across Australia, highlighting recent research findings, adoption trends, and the mix of optimism and caution that characterizes this fast-evolving field. Drawing from the first comprehensive survey of both community members and mental health professionals, we examine the current landscape, emerging trends, and the careful balance between innovation and safety that defines Australia's approach to AI in mental healthcare.
1.AI in Mental Health: An Overview
Artificial intelligence refers to computer systems that perform tasks normally requiring human intelligence – such as understanding language, recognizing patterns, or making decisions. In mental health, AI typically powers digital tools like conversational chatbots, predictive algorithms for diagnosis, or workflow assistants. Early experiments with AI in therapy date back decades (e.g. the 1960s ELIZA program), but only recently have more sophisticated AI mental health tools become available to the public unsw.edu.au.
Modern chatbots such as Woebot and Wysa leverage natural language processing to engage users in two-way therapeutic conversations, offering cognitive-behavioral exercises and mood tracking via smartphone apps. These applications utilize cognitive-behavioral therapy (CBT) principles, providing practical, skills-based tools to help manage thoughts, emotions, and behaviors unsw.edu.au.
Beyond chatbots, AI algorithms are being developed to detect mental health issues from speech, text, or behavioral patterns, and to assist clinicians by analyzing large datasets. However, the health sector has historically lagged in technology adoption. A 2022 government environmental scan noted that very few Australian digital mental health services were utilizing cutting-edge AI capabilities like conversational agents or virtual reality, despite their promising potential health.gov.au. This slow uptake reflects the unique challenges of mental health care – where issues of trust, safety, and human connection are paramount.
However, the landscape changed dramatically with the release of powerful generative AI systems like ChatGPT in late 2022, spurring a surge of experimentation and putting AI tools directly into the hands of clinicians and consumers. As recent Australian surveys demonstrate, both groups have begun using AI in various ways, albeit with careful consideration for safety and ethics.
With ongoing access barriers to traditional care, an increasing number of Australians (especially younger people) are turning to AI-based mental health support via their phones and computers. These tools are available on-demand, low-cost or free, and private – making them an attractive option for those unable to see a therapist regularly.
2.Australian Research and Usage Statistics
A groundbreaking 2024 study by Orygen (a youth mental health research institute) provides the most comprehensive insight into AI's current role in Australian mental health. This study – the first to survey both community members (general public) and mental health professionals – surveyed 107 community members and 86 mental health professionals, finding significant early adoption across both groups orygen.org.au.
Community and Professional Usage Patterns
The research revealed striking patterns of AI adoption across different user groups:
- 28% of community members reported using AI tools for mental health purposes, primarily for quick emotional support (60% of users) and some using AI as their own personal "therapist" (47% of users) mental.jmir.org
- 43% of mental health professionals had used AI in their work, primarily for research (65% of professional users), report writing (54%), and administrative support
- ChatGPT emerged as the most commonly used AI tool among both groups, essentially becoming a general-purpose assistant repurposed for mental health applications orygen.org.au
This data reveals that clinicians are currently leveraging AI more as a behind-the-scenes assistant than as a direct therapy tool, focusing on administrative tasks, note-taking, and background research rather than direct patient interaction.
Benefits and Positive Experiences
Both user groups reported overwhelmingly positive experiences with AI tools:
- 77% of community users found AI to be generally beneficial
- 92% of mental health professionals reported positive outcomes mental.jmir.org
Reported benefits included immediate access to information and support, assistance with routine tasks, personalized advice, and improved efficiency. These findings align with global observations that AI-powered mental health applications can improve self-management of mild symptoms and relieve administrative burden on human providers.
"We found that mental health professionals were most likely to use AI tools for things like research, report and letter writing, and other kinds of administrative support – and were also keen to see more AI tools developed to help with things like synthesising clinical evidence and tracking patient progress."
Risks and Concerns
However, the study also highlighted significant concerns and risks associated with AI use:
- 47% of community members experienced some form of "risk or harm" when using AI
- 51% of mental health professionals encountered concerning issues mental.jmir.org
Common concerns included questionable or unhelpful advice from chatbots, privacy and confidentiality issues, potential reduction in meaningful human connection, and ethical considerations around data security. Critical risks identified include potential misdiagnosis scenarios where AI lacking full context might provide inappropriate guidance to distressed users, and professional concerns about maintaining client privacy when inputting sensitive information into AI systems.
3.National Context and Public Attitudes
Barriers to Traditional Care
The Australian Institute of Health and Welfare (AIHW) reports that approximately 1 in 5 Australians experience mental illness each year (roughly 4.3 million people) mindhealth.com.au. However, less than half of those who suffer receive the treatment they need, particularly in rural and remote areas where access barriers are significant.
Geographic disparities are stark: there are 4.1 times as many psychologists per capita in major cities compared to very remote areas ruralhealth.org.au. In this context, digital self-help tools, including those with AI-driven features, are increasingly filling critical gaps in mental health service delivery.
Public Sentiment Towards AI in Healthcare
The Australian Values and Attitudes on AI (AVA-AI) study provides crucial insights into public sentiment. The research revealed nuanced public attitudes:
- 60% of Australians support AI development in general
- Only 27-43% support AI use in specific healthcare scenarios
- Support drops to 31-39% for social service applications researchgate.net
This indicates the public is significantly more comfortable with AI in low-stakes settings than in sensitive areas like health and mental health. Importantly, accuracy was consistently rated as the most important factor, while reducing costs was rated least important, and speed was also considered less crucial than maintaining human oversight and contact.
4 in 5 Australians valued continued human contact and discretion in service provision more than any speed, accuracy, or convenience that AI systems might provide. Most think AI systems should augment rather than replace humans in the provision of both health care and social services.
These attitudes reflect the foundational importance of empathy, trust, and human connection in mental healthcare, setting the stage for how AI is being cautiously integrated into Australian mental health services.
4.Trends in Adoption and Professional Engagement
The current state of AI in Australian mental health can be characterized as early-stage but rapidly accelerating. Several key drivers have emerged over the past two years, transitioning the field from small pilot projects toward broader awareness and trial implementation.
The pandemic-era expansion of telehealth and online therapy primed both patients and clinicians to accept digital modalities. Subsequently, the global emergence of generative AI in 2023 demonstrated surprisingly sophisticated conversational abilities, prompting widespread experimentation across healthcare settings.
Professional Organization Initiatives
The Australian Psychological Society (APS) has taken a proactive stance, calling for substantial investment in AI-related research and development. Their initiatives include:
- Funding psychology-led discovery projects to research AI's impact on young Australians' mental health
- Developing AI-related training, guidance, and resources for psychologists
- Ensuring the profession is equipped to ethically navigate AI's role in psychological practice psychology.org.au
The APS emphasizes the need for supporting innovative Australian research to better understand the unique impacts and applications of AI within our health system, recognizing gaps in collective understanding about AI use, experiences, and consequences for Australians.
Innovation and Development Ecosystem
Australia is witnessing significant growth in AI mental health innovation:
- The global AI mental health market is growing at over 30% annually nuclieos.com
- CSIRO's Australian e-Health Research Centre developed "Harlie", a chatbot for autism and neurological injury social skills practice csiro.au
- University programs like BRAVE-Online for anxiety are testing AI enhancements for guided therapy exercises mindhealth.com.au
- Head to Health, the government's digital mental health portal, now lists evidence-based apps with AI-driven features headtohealth.gov.au
Young Australians are often the earliest adopters, being particularly tech-savvy and open to digital mental health applications. Commercial wellness apps increasingly incorporate AI recommender systems to provide personalized content and therapeutic exercises.
5.Current Challenges and Ongoing Developments
Regulatory and Ethical Considerations
Recognition that AI in mental health is new and unproven at scale has prompted active development of safety frameworks. Key concerns include potential mishandling of AI tools that could cause harm – for example, a chatbot providing unsafe guidance to a suicidal user represents a serious risk.
Regulators and professional bodies are actively working on frameworks for safe and responsible AI use in healthcare. The federal Department of Health recently consulted on AI legislation and regulation, with stakeholder recommendations emphasizing:
- Ensuring AI systems are transparent and rigorously tested for accuracy and bias
- Requiring informed patient consent for AI-assisted interventions
- Maintaining human override capabilities in all AI systems
- Implementing robust oversight mechanisms psychology.org.au
"This is a new technology, and we must proceed with caution by addressing the significant concerns raised by survey respondents related to privacy, ethics, and the quality of AI-generated advice to ensure these tools are safe and effective."
Rural and Remote Applications
AI tools are being specifically viewed as solutions for extending mental health reach to underserved rural and remote communities. With the stark disparity in mental health professional availability (over 4 times fewer psychologists per capita in very remote areas), AI-assisted interventions offer significant potential for bridging service gaps.
The government's digital mental health strategy (2023–2028) explicitly identifies AI and machine learning as enabling technologies to improve service delivery and triage systems in the future, particularly targeting underserved geographic regions.
Future Research and Development
Current areas of experimental development include:
- Blended care models combining therapist sessions with AI-based homework and monitoring
- AI-driven analysis of therapy transcripts for quality improvement
- Machine learning applications for predicting treatment outcomes
- Personalized AI interventions through academic collaborations like UNSW's Centre of Research Excellence in Depression Treatment Precision unsw.edu.au
Future surveys are planned to track AI use and acceptability over time, providing longitudinal data on outcomes, user experiences, and evolving attitudes toward AI in mental healthcare settings mental.jmir.org.
6.Conclusion
Australia stands at an early but pivotal point in the adoption of AI for mental health. Current evidence demonstrates a growing base of users and generally positive initial reception, balanced with clear calls for caution and robust safeguards. The present state is characterized by pilot projects, comprehensive surveys, and exploratory usage rather than widespread implementation. Both the public and professionals are gradually building confidence in these technologies while maintaining appropriate skepticism.
Key findings from recent comprehensive research show that commercial AI tools are increasingly being used by both community members and mental health professionals. Users recognize AI's potential advantages for mental health care in terms of accessibility, cost reduction, personalization, and work efficiency. However, they remain equally concerned about reducing human connection, ethics, privacy and regulation, medical errors, potential for misuse, and data security mental.jmir.org.
"We know that increasing numbers of people are experiencing mental health difficulties each year, and less than half of those who suffer get the treatment they need, so AI has the potential to revolutionise mental healthcare by making it more accessible, personalised and efficient."
Over the coming years, longitudinal studies tracking outcomes and acceptability of AI in mental health care will provide crucial data to inform policy and practice. For now, the consensus supports AI as a tool to augment rather than replace mental health care in Australia – improving accessibility, personalization, and efficiency – provided integration is approached thoughtfully and ethically.
Despite the immense potential, integration into mental health systems must be approached with caution, addressing legal and ethical concerns while developing safeguards to mitigate potential harms mental.jmir.org. With this balanced approach, the mental health field may harness AI to help close gaps in care while upholding the fundamental values of trust, empathy, and safety that remain core to psychological practice.
The ethical and social dimensions of AI systems matter to Australians. Most think AI systems should augment rather than replace humans in the provision of health care, and maintaining the human element will be critical even as we leverage intelligent technologies.