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AI Adoption in Travel: What Marketers Must Do Now

  • Writer: Shermain Jeremy
    Shermain Jeremy
  • Aug 19
  • 5 min read

Updated: 2 days ago


AI Adoption in Travel
Image created using AI

I recently revisited a Harvard Business Review article that claimed only a small percentage of companies were using AI effectively. At the time, that was true. But the landscape has shifted dramatically.


By 2024, 69% of marketers had integrated some form of AI into their operations, and 63% were using generative AI. Yet only 38% felt their integration was mature — and 43% said they were still experimenting.


The takeaway? AI adoption is high. Effective, scaled use is not. And in travel and tourism — especially among DMOs — the gap is even wider.


The Industry Truth About AI Adoption: Travel Isn’t Slow Because of Fear — It’s Slow Because of Structure

Recent McKinsey research on agentic AI reveals a critical insight: While many industries have aggressively adopted and scaled AI capabilities, travel remains one of the slowest sectors to transform. Not because the technology isn’t ready. Not because travelers aren’t ready. Not even because marketers are afraid.


The root causes are deeper and more systemic:

  • Highly fragmented data systems

  • Legacy vendor dependencies

  • Outdated website and CRM infrastructure

  • Budget constraints and seasonal funding cycles

  • Siloed departments across tourism boards and government

  • Political oversight that slows experimentation

  • Limited in-house AI literacy

Meanwhile, traveler expectations have exploded.


A Growing Gap Between Travelers and Tourism Boards

In 2023, traveler AI adoption hovered around 14% to 19%. By late 2024, it surged dramatically:

  • 40% of global travelers used AI tools for trip planning

  • 34% of Americans expected to use AI for their next trip

  • Up to 38% in markets like the U.S. and U.K. already use AI-based trip assistants

  • 64% globally say they plan to rely on AI for research or planning

That is not a slow trend. It is a behavioral shift. Travelers are moving faster than the organizations serving them — creating the perfect storm: An industry where travelers demand AI-enabled service, but the institutions responsible for destination storytelling are falling behind in delivering it.


The Tourism Paradox: Innovation Meets Authenticity

Travel is fundamentally human — rooted in culture, heritage, and emotional connection. But travelers are now engaging with AI at scale — often before they ever land in a destination.

Picture this: A traveler planning a visit asks ChatGPT about your local food festival. The AI generates a confident answer about a festival that ended three years ago. Yikes! But this is happening every day.


DMOs feel torn between embracing AI to keep up with expectations or protect authenticity and accuracy by keeping everything human. The truth is: Trustworthy AI requires human cultural guardianship — not avoidance.


Why Avoiding AI Adoption in Travel Isn’t Safe Anymore

While some destinations hesitate, competitors are accelerating. Travel brands that adopt AI strategically are seeing:

  • Higher personalization

  • Faster response times

  • More efficient visitor servicing

  • Stronger campaign performance

  • Better insights into traveler intent

Avoidance is no longer caution. Avoidance is a risk.


The Four Critical Risks Every DMO Must Manage


1. Confabulation — When AI Gets It Wrong With Confidence

This is the most dangerous risk in tourism. Unlike retail or tech, misinformation in travel can really ruin someone’s experience.


Example: Your AI chatbot confidently shares hiking trail hours that changed months ago. A traveler arrives frustrated, leaves a bad review, and your brand takes the hit.


Mitigate it with:

  • Verified local data sources

  • Human review

  • Continuous content updates

  • Feedback loops from real travelers


2. Consumer Reactance — When Trust Breaks Down

Travel is emotional. When travelers discover they were speaking to a bot — or get generic, inaccurate AI advice — the trust damage can be long-lasting.


Mitigate it with:

  • Clear labeling of AI assistants

  • Seamless routing to human teams

  • AI responses that carry your destination’s unique voice


At the end of the day, transparency earns trust.


3. Copyright and Ethical Use — The Legal Frontier

With AI-generated images, itineraries, and content comes risk: Who owns it? Can it be used publicly? What if it resembles a copyrighted work?


Mitigate it with:

  • AI tools that provide usage rights clarity

  • Human transformation of AI outputs

  • Documentation of the creative process


This protects both the brand and creative partners.


4. Cybersecurity — The Hidden AI Vulnerability

With more AI assistants comes more risk:

  • Prompt injection

  • Data leakage

  • Exposed APIs

  • Vulnerable vendor tools


Mitigate it with:

  • Restricted access to AI tools

  • Collaboration with cybersecurity experts

  • Regular audits

  • Government-grade protections for traveler data


Case Studies: When Human-AI Partnership Works


GuideGeek — AI With Transparency and Humanity

Matador Network’s GuideGeek is a blueprint for ethical, high-impact AI in travel. Travelers appreciate it for two reasons:

  1. It’s transparent.

  2. Human teams continuously monitor, refine, and correct responses.

Research shows high satisfaction from:

  • Families

  • Travelers with disabilities

  • Travelers with diverse language needs

A great example of human oversight creating cultural and emotional intelligence.


Kerala’s MAYA — Cultural Sensitivity Done Right

Kerala Tourism’s MAYA chatbot exemplifies how to scale local expertise. It is trained on culturally relevant data, then refined daily by local tourism experts. This proves that AI can scale service without diluting authenticity — if humans remain in the loop.


A Practical Roadmap for DMOs: Risk-Smart AI Integration

Phase 1 — Foundation

  • Audit processes

  • Identify repetitive tasks

  • Train teams on AI literacy

  • Establish ethical and accuracy guidelines


Phase 2 — Piloting

  • Start with low-risk use cases

  • FAQ chatbots

  • AI-assisted social copy

  • Email drafting

  • Itinerary ideas

  • Track accuracy and traveler satisfaction


Phase 3 — Scaling

  • Build structured feedback loops

  • Integrate with CRM and visitor data

  • Build destination-specific knowledge bases

  • Keep human oversight for culture, emotion, and nuance


This is how destinations build responsible, culturally aligned AI systems.


The Future of Destination Marketing: Human-AI Synergy

The destinations that win in the next decade will not be the ones that adopt AI blindly — or avoid it entirely. They will be the destinations that:

  • Use AI for scale

  • Use humans for authenticity

  • Use data for precision

  • Use culture for resonance


AI cannot replicate the warmth of local hospitality — but it can amplify it. AI cannot replace cultural knowledge — but it can scale access to it. The future is not AI or humans. It is AI guiding the journey, and humans grounding the meaning.


Take Action Today

If you’re a DMO or tourism marketer, start small:

  • Audit your workflows

  • Identify three tasks AI can streamline

  • Launch one low-risk pilot

  • Build a testing and feedback system

  • Preserve human oversight at every visitor touchpoint


The goal is not perfection. The goal is progress — grounded in authenticity, accuracy, cultural integrity, and traveler trust.


How are you using AI as part of your travel marketing strategy? I’d love to hear from you. 


Sources & Further Reading

AI Adoption in Marketing

AI Adoption in Travel & Tourism

Traveler Behavior & Consumer Insights

AI Risk, Trust & Governance

Case Studies Highlighted


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