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1Repair Windows errors before they cause bigger problems2Fix the driver behind crashes, sound loss and screen glitches3Clear out junk files and repair common Windows errorsAI can help general practices with selected mental health tasks, from appointment administration to documentation and carefully evaluated digital support. The safest model is clinician-led: a tool may assist care, but it should not be treated as a mental health professional, a stand-alone diagnostic service, or crisis care.
What can AI do in general practice?
Potential uses span routine practice operations, tools that support clinicians, and patient-facing interventions. These are different categories: a system that drafts a note is not equivalent to a digital therapy, and neither is automatically equivalent to a general-purpose chatbot.
| Tool category | Possible role | What the evidence or guidance supports |
|---|---|---|
| Administrative automation | Appointment scheduling and reminders, routine communications, billing support, and updating or summarizing records. | The American Psychiatric Association (APA) describes these as possible applications; that does not establish that every product is accurate or improves care. |
| Clinician-facing support | Drafting documentation, summarizing records, assisting screening or care planning, and offering decision support for a clinician to review. | The Royal Australian College of General Practitioners (RACGP) and APA discuss these as potential uses. The GP retains responsibility for clinical assessment and decisions. |
| Purpose-built digital mental health interventions | Structured support or therapy delivered digitally, potentially as part of a care plan. | Use depends on the particular intervention and its evidence, safety, and fit for the patient; the category itself is not proof of effectiveness. |
| General-purpose consumer chatbots | Open-ended conversation or general information, not necessarily designed or validated for clinical mental health care. | The APA says evidence is not yet strong enough for confident conclusions about their mental health use. They should not be presented as diagnosis or crisis care. |
Administrative tasks
Reducing repetitive work may create more room for patient contact, but operational convenience is not the same as a clinical benefit. For example, NHS England reported that an initial AI triage trial at one GP practice in Sussex reduced the number of people queuing on the phone by 29%, while patient satisfaction was maintained. That result concerns one practice and phone access; it does not show improved mental health outcomes or predict what another practice will achieve.
Support during clinical care
RACGP’s June 2026 review identifies screening, documentation, care planning, and support outside clinic hours as possible roles for AI. A clinician-facing system may help organize information or flag something for review, but its output is a prompt to assess—not a confirmed diagnosis or a substitute for clinical judgment.
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Digital support for patients
A practice may consider a purpose-built digital intervention as one element of a broader care plan. The relevant question is whether that specific tool has suitable evidence and safeguards for the intended users and task. A general-purpose chatbot should not be assumed to have the same design, evaluation, or oversight as a clinically evaluated intervention.
How strong is the evidence?
The evidence is developing, and findings from research settings do not automatically transfer to routine general practice. RACGP reports that a 2024 review in Psychological Medicine synthesized 85 studies on AI for mental health diagnosis, monitoring, and interventions. Much of the underlying work took place outside general practice or in research settings, so its direct applicability to everyday GP care remains partly unestablished.
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The APA’s consumer advisory also cautions that research on general-purpose generative AI chatbots does not yet support strong conclusions. It notes a lack of high-quality, large-scale clinical trials to establish the effectiveness, safety, and appropriate use of mental health technologies, including purpose-built tools. Evidence for one product or use case should not be generalized to a different tool or task.
WHO’s guidance is relevant to governance and responsible design, rather than a clinical practice guideline for GPs. In its 20 March 2026 update, WHO recommended assessing and monitoring mental health effects, involving mental health experts and people with lived experience—including young people—in co-design, and adapting systems to cultural, linguistic, and local needs.
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No. Current guidance supports AI as an adjunct to professional care, not as a replacement for trained clinicians or the therapeutic relationship. The UK government’s 17 March 2026 ministerial answer says AI must not replace trained mental health professionals, particularly for people in acute distress. That statement concerns the UK context, but the safety distinction matters wherever a practice uses a tool.
A tool should not be relied on to diagnose a patient or manage a crisis on its own. If someone may be at immediate risk or needs urgent support, the practice needs a clear route to appropriate human assessment and local crisis services. A chatbot’s availability outside clinic hours does not make it a crisis service.
How should a practice assess a tool before using it?
Start with the task, not the product pitch. A system suitable for drafting routine communications may not be suitable for screening or care planning. RACGP and WHO guidance point to a practical assessment across clinical, technical, and organizational dimensions.
- Define the use case and users. Specify what the tool will do, who will use it, which patients it is intended to support, and what decisions remain with a clinician. Avoid vague goals such as “improve mental health care.”
- Check independent evidence. Ask what was evaluated, for which task and population, and whether the study setting resembles your practice. Distinguish measured outcomes from vendor claims, and do not treat an administrative result as proof of better clinical outcomes.
- Assess safety and escalation. Identify how the tool handles inaccurate outputs, false positives, and false negatives. For patient-facing use, confirm what happens when a person reports acute distress and how a clinician or crisis service is reached.
- Review data handling and consent. Establish what patient information is collected, who can access it, how it is used, and what privacy and cybersecurity protections apply. Explain the tool’s purpose and data practices to patients and obtain informed consent where appropriate.
- Test performance across people and languages. Consider whether accuracy and usability have been assessed for the populations your practice serves. Check for bias, cultural fit, language coverage, accessibility, and barriers related to digital literacy.
- Check workflow and oversight. Confirm how the tool fits with the practice’s electronic medical record and day-to-day processes, who reviews its outputs, and how errors are corrected. Clinicians should verify AI-generated summaries and independently confirm any suggested diagnosis through clinical evaluation.
- Plan monitoring and accountability. Set out who is responsible for the tool, how patient outcomes and tool performance will be followed, and what would trigger a pause or review. Include input from clinicians and people with lived experience when assessing impact.
- Consider access and sustainability. Check whether patients can use the tool without creating an unfair digital barrier, and clarify funding or reimbursement before making it part of routine care.
How can a practice introduce AI without weakening care?
Begin with a limited, defined use
RACGP recommends beginning with stable patients who have mild-to-moderate symptoms rather than starting with crisis or complex cases. A practice should introduce a tool only within a comprehensive care plan, with a specific purpose and a named clinician responsible for oversight.
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Explain the role to patients
Patients should know whether AI is being used, what it is intended to contribute, what information it uses, and who can access that information. Provide a way to ask questions and, where applicable, discuss alternatives. Clear explanation helps patients understand that an AI-generated suggestion is not itself a clinical decision.
Review outputs and follow outcomes
Clinicians should check summaries and other generated material rather than transferring them uncritically into care. Follow-up should cover both the patient’s outcomes and the tool’s performance, including errors, uneven results across groups, and workflow problems. If the system creates a safety concern or cannot be adequately monitored, its use should be reconsidered.
What this means for patients
Ask the practice what the tool is for, whether a clinician reviews its contribution, and how your information is handled. If an app or chatbot is suggested, ask whether it is a purpose-built intervention or a general-purpose chatbot, what evidence supports that specific use, and what to do if your symptoms worsen. Digital support can be an addition to care; it should not be your only route to help when you need professional assessment.
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