How AI can support unions in running surveys
The first week of results to our union staff AI survey offers a chance to demonstrate how AI can support quick data analysis – and simple data transformation
Nick Scott
January 14, 2025
A week ago we launched the first ever global survey of trade union staff on AI. We want to know their experience, hopes and fears with AI.
The survey will be open for a few more weeks, but I wanted to get a sense of what might be in it. And show how AI can help do this task quickly, including some categorising data in a way that is really useful.
In the survey, I specifically didn't bother to worry about creating a drop down list for "Union", "Job role" and "Country" because I knew I could get AI to help me – and therefore make it easier for users who don't like to spend time searching long lists of options.
Watch the video to see how I quickly analysed the results:
How AI can enhance union surveys: Key opportunities
Unions love surveys. There’s a lot of members, and lots of views to take account of. However they often face common challenges - from survey design to analysis of results. AI can help at every stage – that it is really important to understand its limitations and how to use it responsibly.
Survey design and testing | Data cleaning and categorisation | Analysis and insights | Time-saving automations |
|---|---|---|---|
Generate question variations to test different phrasings | Standardise free text responses into consistent categories | Quickly summarise key themes from open-ended responses | Create template emails for survey reminders |
Help identify potential bias in question wording | Clean and format messy data | Identify patterns and correlations across different questions | Generate initial drafts of survey reports |
Suggest additional questions based on survey objectives | Flag potential data quality issues or inconsistencies | Generate initial hypotheses for deeper investigation | Prepare data visualisations of key findings |
Make the language simpler and more plain, finding different ways to word complex questions | Convert varied location formats into standard geographical categories | Create draft summaries of findings for different audiences | Format results for different outputs (presentations, reports, social media) |
Important safeguards when using AI with survey data
AI can potentially do a lot, as the table above shows. However it is important to be honest: sometimes using tools like ChatGPT actually create more work than doing it yourself, particularly in terms of data analysis. They can get things wrong (in particular anything involving maths), make things up, or get confused in a number of different ways. This is particularly the case with the free versions of the tools
And, at other times using AI is not responsible. To be responsible in your use of AI tools you should:
Never input personal or identifiable information – the survey I added was anonymous and did not contain names, emails or another other personal data.
Always verify AI-generated analysis against the raw data. In this case, I just wanted to get a sense of the overall numbers, so the response Claude.ai gave me was fine. But if I were doing serious research I’d check everything it says for myself.
Keep human oversight of question design and final conclusions.
Be transparent about AI use in your survey processes.
Complete the survey on AI in trade unions
AI is changing work. As unions, we've faced many changes before - and helped workers navigate them.
Now we need to look at how AI is changing our own work, as staff working in unions. In 2024, Unions 21 spoke to hundreds of union staff about AI. We learned many are already using AI tools to help with their work.
Some staff talk openly about using AI. Others keep it private - not telling colleagues or leaders they use it.
To help workers deal with AI at work, we first need to understand how we use AI ourselves.
This study is the first to look at AI use across unions worldwide. Your answers will help unions develop practical and ethical ways to use AI responsibly.
Add your voice to this important research. Already 450+ union staff from 25 countries are sharing their experiences.
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