Open Access Webinar: Getting AI-Ready for Smarter Member Engagement

AI Imperative for Associations

Artificial intelligence has shifted from experimental curiosity to a core operational expectation in professional associations. What began as pilots for content generation or basic automation has accelerated into broader deployment, with tools now embedded in daily workflows for membership management, events, education, and communications.

Recent surveys capture the momentum: adoption rates among association professionals doubled year-over-year to 39% in 2025, while the share with formal AI policies climbed from 23% to 40%. Yet a significant gap persists—many organisations remain only somewhat or not very prepared for AI's broader impacts, often due to siloed data systems that prevent meaningful insights. Fragmented information limits the ability to deliver timely, relevant interactions, such as personalised networking recommendations or tailored learning paths.

The stakes centre on member retention and growth. Members now anticipate experiences akin to those in consumer platforms—personalised content, predictive suggestions, and efficient support. High comfort with AI use exists provided it stays human-centred and transparent, but inaction risks eroding perceived value. Associations that fail to connect data across functions may struggle to identify at-risk members, customise engagement, or demonstrate clear ROI on dues.

Non-obvious tensions emerge between enthusiasm and caution. While AI promises efficiency gains and deeper connections, regulatory developments like the phased obligations of the EU AI Act extending into 2026 demand governance that many lack. Smaller associations, in particular, grapple with resource constraints, balancing experimentation against risks to member trust and data privacy. The trade-off is stark: early movers build momentum through incremental wins, while laggards face steeper catch-up costs in both technology and culture.

Broader industry reports underscore urgency for 2026 planning. AI is increasingly viewed as the operating system for performance—automating routine tasks to free staff for strategic work, while enabling predictive analytics for renewal and engagement. Organisations prioritising data quality and cross-functional alignment now position themselves to capitalise on these shifts.