AI Hall Planning: The Future of Fair Management
The Silent Knowledge Drain
At many fair operators, the knowledge about optimal stand placements lives in the heads of a few experienced employees. They know which exhibitors shouldn’t be placed next to each other, where power supply is limited, and which hall sections can handle heavy exhibits.
The problem: These knowledge carriers are retiring. And with them disappears decades of know-how that was never documented.
How AI Hall Planning Works
Modern AI systems like VisiFair SHOW learn from historical planning data and the explicitly captured rules of experienced planners. The process:
1. Building the Knowledge Base
The system captures planners’ rules and preferences in a structured format:
- Which exhibitor categories belong together thematically?
- What distances must be maintained?
- Where are there technical constraints (load capacity, power, water)?
2. Generating Variants
Based on these rules and current exhibitor registrations, the AI creates multiple planning variants — not one optimal solution, but alternatives with different priorities:
- Variant A: Maximum space utilization
- Variant B: Optimal thematic grouping
- Variant C: Best possible accommodation of exhibitor preferences
3. Finalization in Planning Tools
The chosen variant is transferred to dimensionally accurate planning tools like Fair Designer or Rubin. Final adjustments are made there by the planners.
Knowledge Transfer, Not Knowledge Replacement
A common misconception: AI doesn’t replace the hall planner. It externalizes their implicit knowledge into a system that can be used by less experienced colleagues. The experienced planner remains the expert — but their knowledge is no longer tied to a single person.
Benefits at a Glance
- Faster response to short-notice changes and late registrations
- Consistent quality even with staff turnover
- Thematic structuring for better visitor experiences
- Documented ruleset as a foundation for continuous improvement