AI in Conferences, Exhibitions and Major Events: Leadership Training Course

Programme Summary

AI in conferences, exhibitions and major events is a five-day training course for senior event leaders at strategic level, culminating in an AI adoption roadmap for their own event portfolio. Organisers face rising attendee expectations and pressure to prove sponsor value, while AI tools arrive faster than the policies to govern them. The approach takes leaders from use-case selection through forecasting, personalised journeys and onsite analytics to data protection and responsible governance. Mars Training Centre UK delivers this programme in AI in conferences, exhibitions and major events.

The Business Case

Event organisations hold rich data on registrations, sessions, footfall and sponsors, yet most decisions on programmes, venues and staffing are still made on instinct. Governed well, AI improves those decisions; used carelessly, it exposes attendee data and produces biased recommendations.

• Attendance and Attendee Satisfaction: Improve as forecasting, personalised agendas and matchmaking align the programme with what delegates value.
• Sponsor and Exhibitor Revenue: Strengthens as lead quality, engagement and return on sponsorship are measured and reported with evidence.
• Operational Cost and Risk: Fall as staffing, queues and crowd flows are planned from data and AI use is governed by clear policy.

Principles and Evidence Base

• ISO/IEC 42001:2023 Artificial Intelligence Management System: Structures the policies, roles, risk assessment and controls for event AI in Session 4.
• OECD AI Principles: Frame the fairness, transparency and accountability tests applied to attendee-facing tools in Sessions 3 and 4.
• ISO 20121:2024 Event Sustainability Management Systems: Provides the management system logic used to embed AI decisions into event planning and review in Sessions 1 and 5.

Intended Participants

• Leaders accountable for the strategy and performance of a conference, exhibition or major events portfolio.
• Directors who approve event technology investments, platforms and supplier contracts.
• Senior managers responsible for attendee experience, sponsorship sales or event operations.
• Officials who plan high-profile government, protocol or state events.

The programme serves conference organisers, exhibition centres, government and protocol departments, and corporate events and marketing functions.

Learning Outcomes

1. Participants will be able to prioritise AI use cases across the event lifecycle by value, feasibility and risk.
2. Participants will be able to evaluate forecasting and planning models for attendance, programme and venue decisions.
3. Participants will be able to design personalised attendee journeys that use chatbots, recommendations and matchmaking.
4. Participants will be able to construct an onsite analytics plan for crowd flow, queues and service performance.
5. Participants will be able to justify a measurement approach for sponsor and exhibitor return.
6. Participants will be able to formulate data protection and responsible AI controls for event technology.

Programme Structure

Day 1: AI in Conferences, Exhibitions and Major Events

Where in the event lifecycle can AI create value, and how ready is the organisation?

• Event Lifecycle Map From Concept to Post-Event Review
• AI Use-Case Inventory for Event Organisations
• Value, Feasibility and Risk Scoring Matrix
• Event Data Sources and Data Maturity Assessment
• ISO 20121 Management System Logic for Event Decisions

Day 2: Forecasting, Programme and Venue Planning

How can data and AI improve decisions made months before doors open?

• Attendance and Registration Demand Forecasting
• Dynamic Pricing and Ticketing Scenarios
• AI-Assisted Programme Design and Speaker Selection
• Venue Layout, Capacity and Space Optimisation
• Generative AI for Content, Marketing and Briefing Packs

Day 3: Personalised Attendee Journeys and Matchmaking

How are attendees and exhibitors given relevant, trustworthy recommendations?

• Attendee Segmentation and Personalised Agendas
• Event Chatbots and Virtual Assistants
• Delegate and Exhibitor Matchmaking Engines
• Accessibility and Multilingual Services
• OECD AI Principles for Attendee-Facing Tools

Day 4: Onsite Analytics, Sponsor Value and Governance

How is the live event measured, sponsor return proven and AI use governed?

• Crowd Flow, Queue and Footfall Analytics
• Real-Time Operations Dashboards
• Sponsorship and Exhibitor Return Measurement
• Attendee Data Protection and Consent Management
• ISO/IEC 42001 Policies, Roles and AI Risk Assessment

Day 5: Applying AI Across the Event Portfolio

How are priorities, tools and controls combined into one adoption roadmap?

• Use-Case Prioritisation for a Participant Event
• Supplier and Platform Selection Criteria
• Change Management for Event Teams
• Peer Challenge of AI Adoption Roadmaps
• Event AI Adoption Roadmap Presentation

Methodology

The programme is built around case analysis of AI use in international congresses, trade exhibitions, sporting events and government summits. Participants test tools on sample registration, session and footfall data in short data exercises and apply each method to an event they lead.

• Suggested activity: Scoring a long list of event AI use cases for value, feasibility and risk.
• Suggested activity: Designing a matchmaking flow for a trade exhibition with consent checkpoints.
• Suggested activity: Building a sponsor return report from sample engagement data.

Capstone Output

Each participant completes an event AI adoption roadmap for their portfolio. It contains prioritised use cases, data and platform requirements, an attendee journey design, onsite measurement indicators, a sponsor reporting approach and the governance controls needed, ready to present to senior management for approval and funding.

Frequently Asked Questions

Is AI in conferences, exhibitions and major events suitable for leaders without a technical background?

Yes. It suits event directors, sponsorship heads and government events officials. It assumes senior experience in events but no programming or data science skills.

Which standards underpin AI in conferences, exhibitions and major events?

It draws on ISO/IEC 42001:2023 for AI management, the OECD AI Principles for responsible use, and ISO 20121:2024 for event management system logic.

How is the AI adoption roadmap for conferences, exhibitions and major events used at work?

You take back a roadmap that senior management can approve and fund, with prioritised use cases, platform needs, indicators and governance controls.

How does AI in conferences, exhibitions and major events differ from general AI strategy programmes?

It addresses event-specific decisions such as attendance forecasting, matchmaking, crowd flow and sponsor return, which general AI strategy programmes do not cover.