Over the past few seasons, I've seen AI move from hype into everyday utility: recommending sessions, curating meetups, and even optimizing traffic flow. The winning events I've produced are the ones that use attendee data (explicit and behavioral) to deliver contextually relevant experiences — without feeling creepy.
Why it matters: AI enables scalable personalization — from agendas and matchmaking to on-site routing and ROI measurement. When used ethically, data-driven choices improve engagement metrics and sponsor value.
Here are my top 5 strategies to use AI & data without alienating attendees:
1. Start with consent-first data collection
Use short, clear profile prompts during registration (interests, goals, job role) and allow granular opt-ins for matchmaking and content personalization. Transparency builds trust; over-collection drives opt-outs.
Pro Tip: Include a single-sentence privacy blurb at registration: "We'll use your preferences to personalize your agenda and networking — you can edit or opt-out anytime."
2. Use AI for matchmaking, not replacements
Let AI suggest 3–5 best matches and allow attendees to accept or browse more. Humans still make the final choice; the AI is the accelerant. Prioritize shared intent and proximity (time zone, schedule) in the matching algorithm.
Pro Tip: Present matches with a one-line reason ("We matched you because you listed 'sustainability' & 'supply chain'").
3. Create dynamically adaptive agendas
Use behavioral signals (session clicks, dwell time, poll responses) to push personalized session reminders or suggest alternate parallel sessions. This reduces no-shows and increases session relevance.
Pro Tip: Implement a lightweight "smart push" policy: no more than 2 personalized nudges per attendee per day.
4. Measure engagement with meaningful KPIs
Move beyond raw attendance to measure active engagement: chat messages, poll participation, networking acceptances, content downloads, and session completion rates. Tie these to sponsor metrics.
Pro Tip: Build a live dashboard (for internal use) that flags low-engagement sessions early so you can pivot programming in real time.
5. Automate routine workflows to free staff for creative tasks
Use AI to handle registration classification, basic customer queries (chatbots), and content tagging. That lets producers focus on storytelling and onsite experience design.
Pro Tip: Always put a human fallback in chatbot flows — escalations should land with real staff within one or two messages.
Final Thoughts
AI scales empathy when used as a decision support tool rather than a replacement. Personalization done right feels human; done wrong, it feels like surveillance. If you want, I'll draft your registration microcopy and a consent-first data flow you can plug into most platforms.