Untangling Tourism Tech

Destination marketing organisations are losing visibility they can't see in the numbers. Fabienne Wintle and Liz Ward sit down to unpack why DMO website traffic is dropping by an average of 30%, even as AI tools like ChatGPT and Gemini keep sending travellers information pulled straight from DMO content. They walk through what's actually happening in the server logs, the framework in Tourism Tribe's DMO AI Playbook, and why the travel purchase cycle is compressing into a single AI-assisted session.

Topics covered:

Zero-click search, the "invisible surge," and why it doesn't show up in Google Analytics

Reading server logs to separate AI indexing bots from live-retrieval bots

Using Cloudflare to track bot activity without blocking the bots that matter

The Compass Model in Tourism Tribe's DMO AI Playbook

Crawlable versus queryable content, and why digitising internal knowledge is now the priority

How ChatGPT's retreat from travel bookings and Google's agentic shopping push are reshaping the travel purchase cycle

What any DMO, regardless of size, can do now to protect its value

Tourism Tribe helps tourism operators and destination marketing organisations stay ahead of AI and technology change. Find the DMO AI Playbook and more at tourismtribe.com.

Subscribe to Untangling Tourism Tech for a new episode every few weeks.

AI can inspire a trip in seconds. Getting tourists to actually book those experiences has been a different story. In this episode, Liz Ward talks with Daniel Blickling and Dhruv Sharma from Traveloris, a B2B AI trip planner that does something most tourism tech has only promised: it generates personalised, locally-informed itineraries and handles live booking in the same session.

Topics covered:

- How the travel purchase cycle has shifted more in the past two years than in the previous 25
- What Traveloris is, how the widget works, and why the B2B model makes it low-risk for operators
- The three-year journey to crack live booking across 25+ booking channels
- A live demo of the Cairns Discovery Tours trip planner
- Why ChatGPT pulling back from travel fulfilment opens the door for specialist tools
- Practical advice for DMOs on turning high-intent LLM referral traffic into bookings
- What's coming next: accommodation booking and a chat analytics agent
- Tourism Tribe's AI Playbook and Pocket Rocket app for tourism operators

Daniel Blickling is the founder of Traveloris (previously Traveler AI), with a background in aerospace avionics engineering and head of innovation technology at British Airways. Dhruv Sharma is the product manager, previously a strategy consultant at Boston Consulting Group and product lead at Telstra.

Tourism Tribe helps tourism operators stay ahead of technology and AI. Find out more at tourismtribe.com.

Learn more about Traveloris at traveloris.com.

Most tourism operators have tried AI. Fewer know what to do next. In this episode, Fab and Liz unpack the AI "driver's licence" journey, from basic ChatGPT prompts to building autonomous agents that do your work while you sleep.

They cover:

Where most operators and DMO staff are sitting right now with AI (hint: 80% are on L-plates)

What moving to your P-plates actually looks like: custom GPTs, Gemini image editing, AI video tools

Fab's "Robin" agent that writes social media reel scripts from a single idea 

How Liz swapped her old workflow for NotebookLM and Gamma.app to produce polished presentations fast

What working on your full open AI licence looks like: building agents that run on a separate machine and report back via Telegram

A real-life tour operator case study: how to automate a 30-minute manual booking process using AI and existing systems

Whether you're just getting started or wondering what's possible beyond ChatGPT, this episode will show you where the road leads.

Links:

Tourism Tribe: https://www.tourismtribe.com

Podcast page: https://www.tourismtribe.com/podcast

Pocket Rocket: https://my.tourismtribe.com

NotebookLM: https://notebooklm.google.com

Gamma.app: https://gamma.app

Welcome to the 2026 season premiere of Untangling Tourism Tech! In this episode, Liz and Fab dive into the massive technological shift currently reshaping the tourism landscape: the move from static AI models to active, goal-oriented AI Agents.

If 2023 was the year of the "Chatbot," 2026 is officially the year of the Digital Doer.

Inside this episode:

Brain vs. Body: Learn why Large Language Models (LLMs) are like a static "brain" that just waits for a question, while AI Agents act as the "body" that can actually perform tasks, follow rules, and execute a playbook.

The Agnes Water Case Study: We revisit the famous Paperbark Walk to explain how old AI models fail by giving outdated advice, and how new AI Agents can fix misinformation loops by checking real-time data.

Agent Legibility: Discover why the new priority for Destination Marketing Organisations (DMOs) isn't just "pretty websites," but creating "legible" data that AI Agents can find and use.

Digitising Local Knowledge: How regional tourism can maintain its competitive edge by turning the "lived experience" and "soul" of local staff into machine-readable formats.

The Google Evolution: A look at how Google Workspace is moving beyond simple search to become an integrated business assistant that understands your emails, documents, and back-office operations.

Key Takeaway:
Don't wait for the technology to be "perfect." The tools are already "plug and play". This episode is your guide to taking small, progressive steps to ensure your destination remains relevant and sustainable in this new era of AI partnership.

This episode gets real about why short, simple video is the fastest way for tourism operators to grow their reach and why perfectionism is costing them visibility. Liz and Fab break down practical ways to repurpose content, use smart AI tools without losing your voice and stay ethical and transparent in an AI driven social landscape. It’s a no nonsense chat that shows operators how to show up confidently on camera, keep their humanity, and let tech do the heavy lifting without taking over.