Janette Roush
SVP, Innovation & Chief AI Officer · Brand USA
A practical look at AI's dual impact on tourism: how it's reshaping where travelers discover destinations and how it's changing the way we work every day. Designed for tourism professionals of any size — from state DMOs to independent hoteliers.
How AI Is Changing the Travel Experience
The gap between adoption and trust is the opportunity. Travelers are experimenting with AI for trip planning, but they still want authoritative, verified information. That's exactly what DMOs are built to provide.
Booking.com and Expedia now integrate directly into ChatGPT, pulling real inventory data into conversational trip planning.
An experimental browser that reads all your open tabs and generates a custom interactive research page — decoupling content from the websites that created it.
Google's AI-generated summaries answer queries directly, reducing click-through to destination websites. Zero-click search is accelerating.
Google Gemini reads photo and video backgrounds to answer destination questions. AI now identifies amenities from your images and infers sentiment from guest reviews.
DMOs are already trusted, nonprofit sources of truth about their destinations. In an era of AI hallucinations and social media misinformation, that credibility is a strategic asset. DMOs can become the verification layer — curating the data that AI systems rely on.
This framework enables tourism dispersal, predictive analytics for visitor guidance, and eventually bookable experiences through everyday chat tools. The buildability window is roughly two years — the time to plan is now.
How AI Is Changing Our Work
The second half of the keynote focused on tools and workflows that any tourism professional can adopt immediately — regardless of team size or technical background.
Upload a recording, get a transcript, and edit your video by editing text. Delete filler words with one click. Auto-translate captions and voiceover into dozens of languages using your own voice clone. Brand USA already uses this for South American outreach in Spanish and Portuguese.
Three live examples of AI-built tools shared during the keynote:
The Agents of Change webinar series — hosted entirely on a website built with AI, replacing a ~$20K/year platform license. Free and fully functional.
Visit janetteroush.com →AI searched five leagues for home game schedules and built two experiences: "maximize games in 5 days" and "plan a road trip from this city."
Try the Road Trip Planner →Replaced a static PowerPoint with a living website where each strategy layer gets its own page. A single source of truth that updates in real time and adapts to different audiences.
A workflow shared from Brand USA's research team (Chelsea Benitez, Head of Research):
Any tips for prompt engineering?
Prompting is overhyped — context is what matters most. Use the CRIT framework: Context (give AI background), Role (tell it who to be), Interrogate (let AI ask you clarifying questions — this is the key step most people skip), and Task (define the deliverable). Tools like Claude Code that access your files provide context automatically.
What about security concerns?
Every organization needs an AI policy and paid, secure AI tools. Free tools use your data for model training. Paid versions offer SOC 2 compliance, data protection at rest, and the ability to turn off model training. Set guardrails: keep payroll and banking data out, but strategy documents are generally low risk. Your staff deserves to understand the safety posture of the tools they're asked to use.
Will AI replace data analysts?
AI democratizes basic data understanding for everyone. Trained analysts using AI become exponentially more capable. The key distinction: AI can write deterministic Python and R scripts, keeping analysis transparent and out of the black box. As destinations adopt DaaS frameworks, the volume of data to analyze will grow dramatically — analysts will focus on bigger predictive questions while laypeople handle routine analytics with AI assistance.
What about the environmental impact of AI — data centers and water usage?
AI infrastructure carries real environmental costs — data centers require significant energy and water for cooling, particularly in drought-prone regions. As the industry scales, these concerns deserve serious attention. We shouldn't conflate individual culpability with corporate responsibility on the part of the AI labs building these data centers. We can weigh our personal impact on water consumption through AI tools against water consumed when we stream video content or scroll social media, and weigh the impact of the AI industry's water usage against that of other large-scale industries. These are important conversations to have, and they should inform how we hold AI providers accountable — they shouldn't keep you from exploring tools that can meaningfully benefit your organization and your career.
AI image generation — for fun and punchlines only, never destination photography.
See your website through AI's eyes. Audit your structured data and schema markup.
Experimental browser that reads open tabs and generates custom interactive research pages.
What problems do we solve for our stakeholders? How can AI help us do this better or faster? AI is a tool — keep it grounded in the work that matters. The inventors don't know what AI can do for tourism. That discovery is on us. Keep ChatGPT or Claude open on a second monitor, and try something new every day.
You have full permission to experiment.