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Insights on events, technology, and the future of gathering
Artificial intelligence is no longer a futuristic promise for the events industry -- it is operational technology being deployed at scale. From registration to post-event analytics, AI capabilities are woven into the platforms organisers already use. The shift happened gradually, then suddenly: what started as chatbot experiments in 2023 has matured into production-grade tools that handle real workloads.
For event organisers, the question is no longer whether to adopt AI, but which applications deliver genuine value versus those that are still more marketing than substance. This guide separates the practical from the aspirational.
The most visible AI application at events is the conversational assistant -- an AI-powered bot that attendees can interact with via the event app, website, or messaging platform. Unlike the rigid chatbots of previous years, modern assistants understand natural language and can handle nuanced questions about schedules, speakers, venue logistics, and session content.
Canapii's AI assistant, Fero, exemplifies this evolution. Attendees can ask questions like "What sessions about sustainability are happening tomorrow afternoon?" or "Where can I find vegetarian lunch options?" and receive accurate, context-aware responses drawn from the event's actual data. This reduces the volume of support queries and helps attendees navigate complex programmes without waiting for a staff member.
The key differentiator for quality assistants is grounding -- responses must be based on the event's real data, not hallucinated content. Look for assistants that cite their sources and gracefully acknowledge when they do not have an answer.
AI-powered speech-to-text has reached the accuracy threshold where it is genuinely useful at events. Live transcription displayed alongside presentations improves accessibility for attendees who are deaf or hard of hearing, and helps non-native speakers follow technical content more easily.
Real-time translation takes this further, making multilingual events possible without a team of human interpreters for every language pair. While the quality is not yet equivalent to professional interpretation for diplomatic or legal contexts, it is more than adequate for conference sessions, product demos, and panel discussions.
For organisers, the cost savings are significant. A single AI translation service can cover ten or more languages simultaneously at a fraction of the cost of human interpretation teams.
Networking is consistently rated as the primary reason professionals attend events, yet most event apps offer little more than an attendee directory. AI matchmaking analyses attendee profiles, stated interests, session attendance, and behavioural signals to suggest relevant connections.
The best implementations go beyond simple keyword matching. They consider complementary expertise (not just shared interests), availability windows, and meeting preferences to propose meetings that both parties are likely to accept. Some platforms even suggest optimal times and locations within the venue.
Results vary by implementation quality, but well-tuned matchmaking consistently increases the number of meetings booked per attendee by 40% to 60% compared to manual networking.
One of the most practical AI applications is automatic session summarisation. The AI processes the transcript of a session and generates a concise summary including key takeaways, action items, and notable quotes. Attendees who could not attend a session get a useful overview without watching a full recording. Those who did attend get a reference document they can share with colleagues.
This feature is particularly valuable for multi-track events where attendees inevitably miss sessions they wanted to attend. Instead of choosing between conflicting sessions, attendees can rely on AI summaries to cover the ones they missed.
Every AI application at events processes personal data -- attendee profiles, location patterns, conversation content, facial images. Organisers have a responsibility to be transparent about what data is collected, how it is processed, and who has access.
Key principles for responsible AI deployment at events:
Consent first: Attendees must explicitly opt in to AI-powered features that process their personal data. Facial recognition, matchmaking, and behavioural tracking should never be enabled by default.
Data minimisation: Collect only what is needed for the specific feature. A session recommendation engine does not need access to networking conversation content.
Transparency: Clearly communicate which features use AI and what data they process. Put this information in the event app, not buried in a privacy policy.
Retention limits: AI-processed data should be deleted after the event unless the attendee consents to longer retention. Session transcripts, matchmaking data, and behavioural analytics should have defined expiry dates.
The near-term trajectory is clear. AI will handle more of the operational workload -- automated session scheduling based on attendee demand signals, predictive catering based on attendance patterns, and dynamic agenda adjustments when sessions run over or rooms reach capacity. The role of the organiser shifts from manual execution to strategic oversight, with AI handling the repetitive decisions that consume time but do not require human judgement.
The events that get AI right will feel more personalised, more responsive, and more valuable to attendees. The ones that deploy AI carelessly will feel surveilled. The difference comes down to design choices made before the event, not the technology itself.
From Fero, our conversational assistant, to smart matchmaking and live transcription -- explore what AI can do for your events.