AI in membership: the questions everyone wanted answered

This was the most common theme. Many organisations can see the potential but feel overwhelmed by the scale of change.

Tim’s advice was simple: start with a problem, not a platform. Identify a process that is repetitive, slow, or member-frustrating, and explore how AI could help.

Alex added that readiness is not about perfect data or a big budget. It is about clarity. “If you can define the question you are trying to answer, AI can usually help you find it faster,” he said.

This came up several times and reflects a real pain point across the sector. Most membership bodies know their data is scattered across systems.

Alex’s view was to focus on connecting, not migrating. ReadyIntelligence, for example, links to existing systems through APIs so the data stays where it is. What matters most is understanding what data you already have and how it is used.

Tim agreed, adding that data chaos should not stop progress. UKAI started with limited historic information and built from there, using insights from member interactions to shape future data collection.

Takeaway: aim for a single view of truth, not a single database.

The people side of AI remains one of the biggest barriers. Several delegates asked how to overcome fear or scepticism internally.

Tim described this as a confidence gap. The people who could benefit most from AI are often the least confident to try it.

He suggested starting with internal use cases so staff can see value before it becomes member-facing.

This question captured a common hesitation. If the big tech players are integrating AI into everyday tools, why build anything yourself?

Alex’s response was clear. General models do not know your members or your data. “They can answer general questions, but they cannot quote your policies, reflect your permissions, or represent your authority.”

Tim added that waiting for others to solve sector-specific challenges is risky. “If members start turning to public AI tools for answers, you lose your role as the trusted voice.”

Takeaway: own your data, control your knowledge, and build trust through context-aware AI.

The closing questions were about the future. Both speakers agreed that the next phase is less about technology and more about mindset.

Tim described it as moving from experimentation to integration. Once teams trust the tools, AI becomes part of daily workflows, from insight generation to member engagement.