AI is now on the creative team — here's how to use it well

AI has been part of event production for some time now — quietly optimizing schedules, automating logistics, generating placeholder visuals. What the Eventex Awards 2026 winners, however, show is something different: a growing body of work where AI isn't running in the background. It's on stage, named, visible, and doing creative work that shapes how audiences experience the event. 

AI as a genuine creative collaborator appeared five times more often in Platinum-winning entries in the latest edition of Eventex Awards than in non-winning entries. That gap doesn't happen by accident — and it points to a specific way of working that wins awards.

The 3 roles AI plays in award-winning event work

The strongest AI-driven work, presented in the Eventex Excellence Report 2026, falls into three distinct roles. Each requires a different kind of human input — and produces a different kind of creative output.

1. Narrative: AI as voice, character, or storyteller

The most emotionally powerful use of AI in this year's data isn't invisible. It's the centerpiece.

What made it work:

• Deep cultural research preceding any AI application
• A clear narrative role defined before the technology was chosen
• Full transparency — the AI voice was acknowledged
• Human authorship at every creative decision point

‍

2. Production: AI expanding the volume and variation of creative event assets

A second role for AI is less visible but equally significant: generating the volume and variation of assets that traditional production simply cannot match at speed or scale.

What made it work:

• A strict creative constraint that forced AI into a specific role
• Human cultural expertise informing every AI-generated output
• AI used to deepen specificity, not replace it with generic assets
• Clear creative ownership maintained throughout

This approach connects directly to a broader principle in award-winning event design: the strongest work treats its tools — whether AI, architecture, or how to stage audience participation — as creative material with a defined role. 

‍

3. Experience: AI responding to or co-creating with participants in real time

The third role is the most interactive — and the fastest-moving area of development in this year's entries.

What made it work:

• AI given a specific interactive brief rather than open-ended creative freedom
• Human moderation and creative direction maintained throughout
• Audience engagement designed around the AI interaction, not added to it
• Outcomes defined and measured before the event

‍

What separates creative AI use from decorative AI use across 1405 entries

All case studies this year share the same common threads:  

• Defining the role precedes selecting the tool. The teams that used AI most effectively didn't start with "let's use AI." They started with a creative problem — narrating a legacy, building at cultural scale, personalizing at volume — and identified AI as the right tool for that specific job.
• Human expertise shapes every output. Mexican folklore. A deceased artist's voice and gesture. The emotional arc of a farewell. In each case, the cultural and narrative intelligence was human. AI executed and expanded it.
• Transparency is built in. The strongest AI work in 2026 didn't hide the technology. It named it, framed it, and let audiences experience it openly. That transparency is also an ethical obligation — particularly when working with voices, likenesses, or cultural material.
• Permissions and authorship are established early. Working with AI-generated likenesses, voices, or culturally specific material requires clear rights frameworks before production begins. This is not a legal footnote — it's a creative and reputational decision.

What this means for your next brief

AI works best when it has a job to do — a specific cultural context, a narrative role, a creative constraint that forces it toward specificity rather than generality. Before reaching for it, ask:

1. What is the one thing AI can do here that the team cannot do at this scale, speed, or fidelity?
2. Who owns the cultural and narrative intelligence that will inform the AI output?
3. How will the AI's role be communicated — and does that communication serve the experience?
4. What permissions, rights, and authorship frameworks need to be in place before production begins?
5. How will you measure what the AI contribution produced, specifically?

‍

‍

‍

FAQ

‍