Conversational AI for event experiences

The brief was to design a digital support experience that could help people access timely and relevant information across the full event journey. From pre event planning through to live event moments, the experience needed to answer common questions clearly, reduce friction, and ease pressure on support channels.

The opportunity was not just to provide answers, but to design a framework for conversational assistance that could scale across event formats, audience needs, and operational complexity.

Our work focused on the experience architecture behind the concierge, including conversation design, response logic, information structures, and content priorities. Rather than approaching the assistant as a simple chatbot, we treated it as a service layer that needed to connect user intent with accurate and contextually useful information.

This included mapping common support scenarios, defining high priority question types, and structuring responses in a way that felt fast, relevant, and easy to act on.

The approach centred on designing an AI assistant around real attendee needs and real event conditions. This meant identifying the moments where people are most likely to need support, such as registration, timing, transport, location details, event rules, or key updates.

To support those needs, we developed a conversational framework that balanced utility with clarity. Information had to be easy to retrieve, simple to understand, and structured in a way that reduced cognitive load, particularly in time sensitive environments.

The resulting concept was a conversational concierge designed to support attendees across both pre event planning and live event participation.

Key principles included:

• clear response structures for high intent questions
• modular information architecture to support changing event details
• scalable content patterns across logistics, schedules, and FAQs
• interaction design that prioritised speed, clarity, and ease of use
• a system flexible enough to extend across future events and audience needs

Rather than functioning as a one off campaign tool, the concept was framed as a reusable model for conversational support within large scale experiences.

This work demonstrated how conversational interfaces can support live experiences in a way that is both practical and scalable. By focusing on information design, service architecture, and real user needs, the concept showed how AI can reduce friction, improve access to event information, and create a more supported attendee experience.

More broadly, it highlighted the role conversational systems can play within brand ecosystems, not only as engagement tools, but as useful service layers that improve the overall experience.

Please note: This project was developed as a proof of concept. Due to commercial constraints, some aspects of the solution cannot be fully shared.