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AI is no longer a distant concept for membership organisations. It's already influencing workflows, decision-making, and service delivery — sometimes intentionally but sometimes in the background too.
In the first of our 2026 quarterly AI in Membership webinar series, hosted in partnership with Umbraco, we stepped away from product demos and focused on something more fundamental: governance, maturity, and how to identify your organisation’s true starting point.
Because before implementing tools, running pilots, or exploring automation, there is a more important question to answer:
Are we ready to adopt AI responsibly?
One of the clearest themes from the session was that AI adoption is often happening informally.
Even organisations without a formal AI policy are likely to have staff experimenting with generative tools in their day-to-day roles. As discussed during the webinar — and supported by the 2025 Professional Associations Research Network (PARN) research shared in the session — usage across the membership sector is often fragmented, uneven, and unmonitored.
Marketing and communications teams tend to lead the way, using AI to support content creation and efficiency. Other departments remain more cautious. Leadership teams may feel pressure to “do something with AI,” while governance frameworks are still being defined.
The risk is not experimentation itself. The risk is invisibility, because you cannot govern what you cannot see.
The word “governance” can feel restrictive. But in the context of AI, good governance is not about banning tools or stifling innovation.
In fact, a blanket ban is often the worst possible response. It simply drives AI usage underground, removing visibility, shared learning, and risk control.
Effective AI governance creates a safe environment for experimentation. It makes expectations explicit. It clarifies what data can and cannot be shared. It ensures there is always named human accountability for outputs. But most importantly, it builds confidence.
Throughout the discussion, one principle came up repeatedly: human-in-the-loop oversight.
AI can assist with drafting, summarising, analysing, or even automating tasks. But accountability never disappears. If content is published, code is deployed, or a member receives information generated with AI support, a human must remain responsible for reviewing and validating that output.
Governance, done properly, does not slow progress. It enables it.
Another important theme was the idea of AI maturity.
It is tempting to think of maturity as a leaderboard — that some organisations are ahead and others are behind. But maturity is not about speed. It is about clarity and deliberate progression.
Many organisations begin in a decentralised phase, where individuals experiment independently with tools such as ChatGPT. The next stage often involves bringing that activity into the open by approving specific tools, providing organisation-wide access, and introducing shared standards.
As maturity grows, organisations may start embedding AI within existing systems and workflows. They may explore structured prompting, formal review processes, or even more advanced automation models.
The defining feature of maturity is not complexity. It is intentionality. An organisation with clear boundaries, shared understanding, and named accountability may be more mature than one experimenting widely without structure.
For membership bodies and professional associations, the conversation carries additional weight. These organisations hold sensitive professional data. They produce proprietary content that forms a core part of the membership value proposition. They occupy a position of trust within their sectors.
If that trust is damaged through careless AI use, whether through inaccurate information, data exposure, or reputational missteps, the consequences are significant.
At the same time, complete inaction carries its own risk. Competing organisations and alternative providers are already using AI to drive operational efficiencies and enhance user experiences. The challenge is not whether to adopt AI, but how to do so responsibly.
If there was one practical takeaway from the webinar, it was this: start by understanding your current position.
AI maturity begins with visibility. Once you know where you stand, you can move forward deliberately, building confidence rather than reacting to pressure.
This article captures the key themes from the session, but the full discussion explored these ideas in much greater depth, including how to measure meaningful impact beyond productivity and ensure accountability remains clear as automation increases. By accessing the webinar replay, you'll also be able to download your copy of our AI readiness checklist, co-authored with Umbraco.
If you are currently assessing your organisation’s AI starting point, the full session offers practical, experience-led insight tailored specifically to the membership sector.
Complete the form to watch the webinar on-demand.