Aipedia: Social workers
Social work students can learn to use AI responsibly on placement, but they need clear rules and close supervision. Social Work England's research found most recent graduates had received no AI training.
Part of: AI in social work
In short
Students meet AI in two places: at university, where they may use it for assignments, and on placement, where they may see AI transcription and drafting tools in daily use. Social Work England's research found most recent graduates had no AI training, and the Research in Practice report it commissioned covered both education and practice. Practice educators and placement supervisors have to decide what students may use AI for, check their work, and make sure confidential information from placements does not end up in public tools or assignments.
SWE's research summary, drawing on the Research in Practice report of January 2026 on AI in social work education and practice, found that most recent graduates had no AI training. It also found that use of AI across employers is uneven and policies vary, so a student may move between placements with very different approaches. SWE said AI may affect some professional standards, which may need updating.
In a GOV.UK blog, SWE's executive director said AI cannot replace professional judgement. For students, that judgement is still being formed, which makes over-reliance on AI a particular concern.
On placement, students may observe or use the employer's approved transcription and case-recording tools, draft records or letters with AI support, and use AI to research legislation or theory. Outside placement, some will use public chatbots for assignments, reflective logs or portfolio evidence that draw on placement experiences.
Practice educators and supervisors have these responsibilities:
See the professional standards.
The biggest risk is placement information leaving approved systems. A student who pastes case details into a public chatbot to help write an assignment or reflective log may disclose confidential, special category data. Standard 2.6 sets the expectation for registered social workers, and placement agreements and university policies usually set similar rules for students. BASW's guidance, as reported, warns against entering sensitive information without explicit, informed consent.
For the wider risk, see AI on personal devices.
Illustrative scenario: a final placement student uses a public chatbot to turn their notes from a home visit into a case recording, then saves the output to the employer's system after only a quick read. The note contains a detail the student did not observe. The practice educator, assuming the student wrote it, countersigns it. The error is found when the family disputes the record. The placement provider and university both review what happened, and the practice educator's own oversight is questioned.
Students on placement are usually covered through the arrangements of their university and the placement provider; check the placement agreement. Independent practice educators who supervise students off-site should check that their own PI covers practice education and their oversight of student work; see independent social workers: does PI cover AI? and PI for social workers.
Practical controls include:
Related: AI transcription and case recording and AI in supervision.
Apex arranges PI for independent practice educators and social work consultants. A broker can review whether your cover extends to supervising students who use AI tools; see the AI in social work hub.
Only as the placement provider allows. Practice educators should agree at the start which tools may be used and for what, and should check AI-assisted work. SWE's research found most recent graduates had no AI training, so supervision matters.
Not with identifiable or confidential information in a public tool. Placement details should be anonymised and handled in line with the placement agreement and university policy. BASW warns against entering sensitive information without explicit, informed consent.
SWE's research found most recent graduates had no AI training and said some standards may need updating. Until education catches up, placement providers and practice educators may be the first place students learn how AI tools are used safely in practice.
The practice educator is responsible for their own oversight, including what they countersign. Standard 3.8 requires clarity about accountability for delegated work. Checking student records properly, knowing AI may have been used, is part of that.
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