Understanding and responding to members’ needs has always been central to strong unions. But capturing the nuances of breakroom chats, phone conversations and meeting discussion is practically impossible, and traditional listening methods like online surveys and feedback forms don’t allow for expansive responses.
AI offers a faster, cheaper and more inclusive way to listen at scale and make sense of what members are saying.
Why understanding members matters
Members, like the rest of the population, are not a homogenous mass. They work in different sectors, under different governments and employers, at every career stage. They face different workplace concerns, have a range of expectations from their union and a varied willingness to get involved.
Without a deep understanding of the different needs of their members, unions risk:
Speaking only to the largest groups of members or the loudest voices
Missing what matters to members in emerging sectors
Building campaigns on assumptions rather than the nuances
If we don’t know our members in depth, we end up only speaking to the most accessible groups, leaving others feeling unseen. And knowing members well, helps unions design support that meets real needs, strengthen relationships and identify new opportunities to organise.
What AI can do
AI tools don’t offer a magic solution but, used responsibly, they can make listening, analysing and planning faster, more powerful and significantly more cost-effective and labour intensive.
There are survey tools which encourage verbal feedback, offer prompts when the question isn’t answered or when the answers offers a chance to go deeper. Then there are tools which can analyse the feedback and give insights into member groupings and their sentiment. Such tools can:
Collect qualitative data at scale: through short voice or text surveys that capture what members think and feel in their own words.
Turn unstructured responses into usable data: automatically grouping ideas, locations or themes for analysis
Generate dashboards and personas: to help understand different segments of the membership’s position on a campaign or issue, willingness to get involved, and messages and activities which are likely to work
How to get started
1. Begin with a clear question
Decide what you need to know and why. For example:
What persuades potential members to join?
What’s stopping people from becoming reps?
How likely are members to take part in industrial action?
Avoid collecting data just because it’s possible – every question should inform a real decision, preferably linked to your strategic priorities.
2. Choose the right tool
Once you know what you want to find out, choose the right tool. Voice surveys are quick and easy to use for members, and transcribe and analyse responses instantly.
3. Structure your data
AI can convert free text or spoken answers into structured data – tagging themes or categorising by region, role or sentiment, for example. It saves hours of manual coding, but human oversight remains vital. Spot-check outputs for errors before using them. You might also wish to pilot with small groups before scaling up so you can iron out any issues. And remember – asking the same groups of members will gather the same responses – cast your net widely.
4. Interrogate the findings
AI can identify themes, but humans must interpret them. Ask whether the insights make sense. Follow up where results surprise you, they might need further research. Treat AI as an assistant that accelerates your thinking, not a replacement for analysis.
5. Apply the insight
Use AI outputs to:
Spot the issues among members you never realised you could organise around
Identify the needs of smaller segments of membership, especially the ones where it’s not easy to get face-to-face
Map the behaviour patterns of members who are likely to leave and tailor early engagement comms to those at risk
Craft campaign messages, asks and channels for different groups of members
Understand and address concerns over voting in ballots or taking industrial action, especially the undecided who need convincing to secure your success
6. Be responsible
Always check where data is stored and how it’s processed. Not all AI tools treat data the same way – free platforms likely use US-based servers and may store data for model training, making them unsuitable for personal or identifiable information. Licensed tools within Microsoft or Google environments are safer for member data. Before running any AI project check GDPR and data protection compliance and be transparent with members about how their information will be used.
Final thoughts
AI helps unions listen at scale, interpret at speed and act with confidence. Used well, it reveals what really matters to members and supports better recruitment, retention and engagement decisions.
But AI is only a tool. The real value comes from how unions use the insight – with human judgement and a clear purpose at the core of every decision.
