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As of 13 August 2026, AI can only partly analyse training feedback.
Most people should hand this to a purpose-built tool.
Can you do it?
5 minutesto a draft.
30 minutesto something you’d act on.
Cost, all in£0
Skill neededchat-fluent
Who has to check ita colleague
What the alternative costsThe alternative is analysis by an HR or learning specialist; the supplied tool data gives no price for that service.
If this goes wrong: the analysis hides an important minority view or misreads a complaint, leading to poor training changes and reduced trust in the feedback process.
What to actually do
Use a tool built for this
The route this page recommends
Do it yourself
Second choiceA chat interface, chat-fluent skill, and roughly 30 minutes until you can act on the result.
How to actually do it
- Open the feedback source, such as the survey export, form responses or meeting notes, and collect the complete responses rather than only the most recent comments.
- Remove names, email addresses, employee numbers and identifiable personal details, then label each response with a simple source reference and, where relevant, its course, session or team group.
- Gather the training objective, course content, delivery format, intended audience and any questions you want the analysis to answer.
- Paste the context and anonymised feedback into a chatbot using the prompt above, replacing each bracketed slot with your material.
- Compare every reported theme, count and quoted example against the source responses, correcting any grouping that does not match the original wording.
- Send the checked findings to an HR, learning or management colleague, resolve the flagged questions, and record which training changes you will make and why.
Prompt
Analyse the training feedback below for a UK workplace. First, remove or ignore names, email addresses and other identifying details. Do not infer protected characteristics, motives or personality traits. Produce: 1) the main themes, with the number of comments supporting each theme only where the source allows a reliable count; 2) representative short quotes labelled by source reference; 3) positive findings; 4) problems and requests; 5) minority views, contradictions and outliers; 6) differences between [COURSE, TEAM OR SESSION GROUPS] only where the data supports them; 7) practical training changes ranked by likely usefulness; and 8) questions that need human follow-up. Separate what the feedback explicitly says from your interpretation. Do not invent comments, counts, causes or conclusions. Mark uncertain findings as uncertain. Keep the tone neutral and suitable for sharing with an HR or learning colleague. Training objective and context: [PASTE CONTEXT]. Feedback: [PASTE ANONYMISED FEEDBACK].
Open it prefilled in ChatGPT or Claude, or copy it into Gemini, which takes no prefill link.
Hand it to a person
The distant thirdA person who owns the outcome does this end to end, worth it when the failure is dear.
What it gets wrong
- AI cannot know whether a blunt comment reflects a one-off delivery problem, a wider workplace issue or a deliberately excluded concern.
- AI cannot safely identify the meaning of sarcasm, coded language or silence in a small group without people who know the setting.
- AI cannot decide whether a suggested training change is fair, proportionate or appropriate for a particular employee or team.
- AI cannot take responsibility for employment decisions or for the consequences of acting on an incomplete analysis.
What caps this at PARTLY: judgement under ambiguity, private data access and stakes of error.
How we scored this
Five axes, each scored nought to two by hand: ten means AI carries the task cleanly, and the thresholds that turn a total into YES, PARTLY or NO are published in the methodology. Each axis name links to its definition.
| Axis | Score (0–2) |
|---|---|
| Output | 2 |
| Inputs | 1 |
| Verification | 1 |
| Liability | 1 |
| Effort delta | 2 |
| Total | 7 / 10 |
The methodology and its thresholds are published in full.
FAQ
- Can ChatGPT analyse employee training feedback?
- Yes, it can sort anonymised comments into themes, summarise recurring points and suggest training changes. Treat the result as a working analysis: compare it with the original responses and have a colleague check the interpretation.
- Is it safe to put employee feedback into AI?
- Only use feedback that has been anonymised and that your organisation permits you to process in that tool. Remove direct identifiers, avoid unnecessary personal details and check your employer's data-handling rules before pasting anything.
- Can AI identify themes in training feedback?
- Yes, especially when the responses are clearly labelled and the task asks for evidence, minority views and uncertainty. It can still combine different meanings or miss a concern, so check each theme against the source comments.
- Can AI decide what training changes to make?
- It can propose and rank possible changes, but it cannot decide which change is fair or suitable for your workplace. A responsible manager or learning professional must consider the context, resources, employee impact and any wider performance issue.
Nearby answers
- Can AI create a leadership training programme?PARTLY
- Can AI create an employee development plan?PARTLY
- Can AI create an equality and diversity training course?PARTLY
- Can AI identify employee training needs?PARTLY
- Can AI help prepare for a difficult performance conversation?YES
- Can AI write a performance improvement plan?YES
Assessed by gpt-5.6-luna (gpt-5.6-luna) on 2026-08-13, second-checked by an independent model. Wrong somewhere? Email [email protected] and it gets re-checked.
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