XDW 2026 · Day 3 · Brussels · 4 June

The Implementation Lab

An optional third day for organisations ready to convert AI thinking into operational policy. A focused working session built around the DTTT AI Transparency Framework, with limited places.

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03
Day three · The Implementation Lab

From principles to policy in practice

4 June 2026 Thursday
Morning · 09:30–13:00

AI Policy, Transparency and Governance

A focused discussion examining the policy implications shaping AI integration. Day 3 will look at AI through a strategic lens, exploring where governance frameworks are forming and what capabilities are needed.

09:30
30 minutes
Registration
10:00
1 hour, 15 minutes
AI Policy Challenges
A strategic opening on the policy questions DMOs are confronting as AI moves from experimentation into implementation. The session looks at AI Policy, Transparency and Governance as a connected set of issues, examining how DMOs are shaping their own strategies.
11:45
1 hour, 15 minutes
Preparing for AI's Future: Use Case Exchanges
A peer-led format built around shared experience. Participants will bring live cases of how their teams are preparing for the future of AI, surfacing the concerns, the unknowns and the practical responses that are starting to take shape. The exchange treats these challenges as something the community can work through together by trading use cases, comparing approaches and learning from one another's best practices.
11:15
30 minutes
Coffee and Networking
Afternoon · 14:00–16:45

Working Sessions on the Framework

The afternoon moves from recap into working sessions. Two rounds of parallel groups break down the Tier 1 Models and Tier 2 Instruments of the DTTT AI Transparency Framework, with what is developed in the room contributing directly to its next iteration.

13:00
1 hour
Lunch
14:00
15 minutes
Framework Recap
The DTTT AI Transparency Framework: First Committee Discussion
A working session on the DTTT AI Transparency Framework, the open suite of models for recording and communicating AI use across tourism organisations. The session walks through the framework in detail, including the Transparency, Productivity, Environmental and Content Integrity Models and opens the first governance committee discussion. Participants will help shape the next iteration by raising questions, proposing refinements and contributing direct knowledge from their own organisations.
14:15
60 minutes
Parallel • Tier 1 Models
Pick your model
Working groups will focus on assessing and discussing the four Tier 1 Models from the AI Transparency Framework. Each model addresses a different dimension of AI use, from how AI contribution is recorded, to how time savings are measured, to how environmental intensity is graded, to how the ethics of AI-generated visual content are assessed.
Model 01
AI Transparency Model
How AI contribution is recorded across any piece of work using the A to E scale.
Model 02
Productivity and Delivery Extension Model
How AI time savings and capability extension are measured and reported.
Model 03
AI Environmental Impact Model
How the relative energy intensity of AI use is graded and disclosed.
Model 04
AI Content Integrity Model
How the ethics of AI-generated and AI-manipulated visual content are assessed.
15:15
30 minutes
Coffee and Networking
15:45
60 minutes
Parallel • Tier 2 Instruments
Pick your instrument
Working groups will examine the framework’s Tier 2 Instruments, which focus on team and organisational structures rather than individual outputs. These instruments examine the capability, maturity and wellbeing of the people doing the work, providing the organisational intelligence needed to manage AI adoption over time.
Instrument 01
AI Maturity Model
A baseline assessment of where an organisation sits on its AI journey, suitable for all staff including those not yet using AI.
Instrument 02
AI Capability Model
A scenario-based individual assessment for people already using AI regularly, producing an archetype profile and development path.
Instrument 03
AI Wellbeing Instrument
A periodic reflection on what AI is doing to people inside the organisation, tracking the human impact of AI adoption over time.