You have picked your tool. The governance is done. The pilot went well. Now you need to train twelve clinicians, eight administrators, and a practice manager who has already told you she does not trust computers to write medical notes. Where do you start?
Training is the step that most practices underestimate. They assume that because the tool is intuitive, people will figure it out. They send a link to a tutorial video and call it done.
This is like giving a new registrar a copy of the BNF and assuming they can prescribe safely. The tool is only part of it. The clinical judgement around the tool — when to use it, how to review its output, when to override it — is what makes the difference between safe practice and risky practice.
Understanding your team
Before you plan any training, understand who you are training. Every practice team falls into roughly four groups when it comes to new technology.
The Enthusiasts (typically 15–20% of the team). They have already tried AI tools. They read articles about it. They are the ones who pushed for adoption. They need the least technical training but the most governance training — because their enthusiasm can outpace their caution.
The Pragmatists (typically 40–50%). They are open to AI if it genuinely helps. They want to see evidence, not promises. They will adopt if the pilot data is convincing and the training is practical. They are your key group — win them over and you have critical mass.
The Cautious (typically 20–30%). They have concerns about patient safety, data protection, or the principle of AI in clinical care. Their concerns are often well-founded and important. They need to feel heard, not steamrollered. Given time and evidence, most will come round.
The Resistant (typically 5–10%). They do not want to use AI and may never want to. They may have deeply held views about the doctor-patient relationship, technology in medicine, or simply prefer their existing workflow. Respect their position — but ensure they understand the practice’s standards even if they choose not to use the tool themselves.
You do not need 100% adoption to succeed. You need the Enthusiasts and Pragmatists on board, the Cautious feeling respected, and the Resistant understanding that the practice has made a collective decision. Trying to force unanimous enthusiasm is counterproductive.
What training must cover
Training for AI documentation tools is not a software demonstration. It is clinical skills training. Here is what every clinician needs to learn.
1. Tool mechanics. How to start and stop the tool. How to set it up. How to adjust settings. Where the generated note appears. How to edit it. This is the easy part, and most suppliers provide good tutorial materials for this.
2. Note review skills. This is the critical clinical skill. Every clinician needs to be able to apply the four-point review from Module 3: Structure, Accuracy, Safety-netting, and Sign-off. They need to practise identifying hallucinated negatives, confabulated details, and missed information. Use examples from your pilot if possible.
3. Consent and communication. How to explain AI documentation to patients. What to say at the start of a consultation. How to handle patients who decline. How to document the patient’s decision. Practise this with role-play — it feels awkward the first few times.
4. When to pause or stop. Sensitive consultations, safeguarding disclosures, patients in distress, complex mental health presentations — when does the tool get paused? This needs to be a reflex, not a decision made under pressure.
5. Error reporting. What to do when the AI gets something wrong. How to correct the note. Whether and how to report the error. Where to record patterns of errors. Make this simple or people will not do it.
6. Governance awareness. Everyone does not need to know the DPIA inside out. But they do need to know that a DPIA exists, that patients have been informed, that the tool is on the AVT Registry, and who to contact if they have concerns. A one-page summary is usually sufficient.
How to deliver training
The most effective training format I have seen in general practice combines three elements.
A group session (60–90 minutes). Cover the why (why the practice is adopting this tool), the what (which tool, how it works, the governance), and the how (live demonstration with real scenarios). Include time for questions. Record the session for anyone who cannot attend.
Supervised practice (1–2 sessions). Pair each clinician with someone who has already been through the pilot. They use the tool in real consultations with the experienced user sitting in for the first few. This is how registrars learn to consult — it works for AI tools too.
Follow-up at two weeks. A brief check-in after everyone has been using the tool for a fortnight. What is working? What is not? What questions have come up? What errors have been seen? This is where you catch problems early and adjust your approach.
Budget at least half a day per clinician for initial training, including supervised practice. This feels expensive in terms of clinical time. But the cost of poor training — errors in notes, governance failures, disengaged staff — is much higher.
Training non-clinical staff
Do not forget your administrators, receptionists, and practice managers. They do not use the AI tool directly, but they are affected by it.
Receptionists need to know what to say when patients ask about AI. Practice managers need to understand the governance framework. Administrators who work with clinical correspondence need to know what AI-generated content looks like and how to identify it.
A thirty-minute briefing for non-clinical staff, covering what the tool does, how patients are informed, and what to say if asked, is usually sufficient.
The training that never stops
Initial training gets people started. Ongoing training keeps them safe.
Plan for a refresher session every six months. Review any significant errors or near-misses. Update training when the tool is updated or when guidance changes. Share anonymised examples of good practice and lessons learned.
The best practices I have seen treat AI competence the same way they treat other clinical skills — as something that needs regular review, reflection, and development. This is not a one-off training event. It is a new area of clinical competence that your team will be developing for years.
Consider adding AI documentation skills to your practice’s appraisal and CPD framework. If clinicians are using AI tools daily, their competence in reviewing AI output is a professional skill that should be reflected in their appraisal evidence.
Key Takeaway
Training is clinical skills development, not a software tutorial. Cover tool mechanics, note review skills, consent processes, when to pause, error reporting, and governance awareness. Deliver through group sessions, supervised practice, and two-week follow-ups. Train non-clinical staff too. Plan for ongoing refresher training every six months.