AI-Driven Customer Service in Travel & Hospitality: Booking Assistance, FAQs & Itinerary Support

Executive Summary

Travel and hospitality are undergoing a structural shift driven by conversational AI. Customer expectations have moved toward instant responses, personalised recommendations, and seamless booking flows. AI chatbots and agents—powered by LLMs like ChatGPT—are now central to digital service delivery across airlines, hotels, online travel agencies, tourism boards and mobility companies.

Across the industry:

  • 40% of travellers have already used AI for trip planning, and 62% are open to future use.

  • 78% of organisations deploy AI for customer service.

  • 73% of companies use or plan to use AI-powered customer support

  • 56% of business owners use AI for customer-service tasks

  • 80% of companies use AI for customer interactions

This whitepaper consolidates insights from industry publications, academic research and strategic analyses to map out how AI is transforming booking assistance, FAQ automation and itinerary generation.

1. The Shift Toward AI-Enabled Travel Experiences

1.1 Rising Consumer Adoption

Kantar research indicates a meaningful change in traveller behaviour: nearly half of travellers now use AI tools to build itineraries, discover destinations, and compare options. Travel planning—which historically required multiple websites and manual research—is being compressed into minutes through agentic AI.

McKinsey reinforces this trend, emphasising that agentic AI will become the “default interface” for travel decision-making.

1.2 Business Adoption Is Even Higher

Across multiple reports (Fullview, Chatbase, Tidio), 70–80% of companies have deployed AI in some part of the customer service pipeline. In travel, this includes:

  • flight & hotel booking assistance

  • pre-trip FAQs

  • cancellation/refund support

  • itinerary customisation

  • multilingual guest services

  • real-time disruption management (delays, rebooking)

Hotels and online travel agencies are early adopters, driven by labour shortages and high demand for 24/7 service coverage.

2. Key Use-Cases in Travel & Hospitality

2.1 Booking Assistance

Based on insights from KSolves, Cognigy and Seekda:

  • AI chatbots now originate a growing share of first-contact booking interactions.

  • They reduce website drop-off by clarifying room types, flight conditions, or package options instantly.

  • They automate:

    • room/flight availability checks

    • fare comparisons

    • upsells (extra baggage, upgrades, breakfast)

    • cross-sell recommendations (car rentals, insurance)

In hotels, chatbots often handle 40–60% of pre-booking questions.

2.2 FAQ Handling

Frequently asked questions consume most support volume.
Examples:

  • hotel check-in/out times

  • cancellation policies

  • fare rules

  • child/infant policies

  • visa or travel document requirements

  • loyalty programme queries

AI resolves these with high accuracy, significantly reducing workload for front-desk teams.

Why it matters

  • Immediate answers reduce customer frustration

  • Increased self-service funnels more users toward booking completion

  • Support agents can focus on complex cases

Academic research (MDPI, Taylor & Francis) confirms that well-designed travel chatbots increase perceived trust and booking likelihood.

2.3 Itinerary Suggestions

This is the category where LLMs shine.

Based on Kantar, McKinsey, and Tredence reports:

  • AI can generate itineraries that reflect personal preferences, budget, time of stay, mobility needs, seasonality, and real-time availability.

  • New “agentic AI” models even refine itineraries through multi-step dialogues.

  • OTAs, tourism boards and travel apps are deploying AI-driven recommendation engines that outperform static guides.

Outcome:
Travellers spend less time planning and more time booking.

3. The Impact of Agentic AI

McKinsey and Tredence independently identify a new wave: agentic AI—AI systems that take actions autonomously.

Examples in travel:

  • rebooking travellers automatically when a flight is cancelled

  • adjusting itineraries based on weather or event changes

  • contacting hotels or partners through APIs

  • suggesting optimal travel windows based on price trends

This represents the next frontier of travel automation.

4. Benefits for Travel & Hospitality Providers

4.1 Operational Efficiency

AI reduces support load by 30–60%, depending on the organisation.
Hotels report 24/7 coverage without expanding staff headcount.

4.2 Revenue & Conversion Lift

AI improves bookings through:

  • instant answers (fewer abandoned carts)

  • dynamic upsells and cross-sells

  • personalised product matching

4.3 Better Personalisation

AI continuously learns from user behaviour:

  • preferred budget

  • travel style

  • food preferences

  • itinerary pacing

  • accommodation type

This creates more relevant recommendations.

4.4 Multilingual Support

AI eliminates language constraints, enabling hotels to service international guests without hiring multilingual staff.

5. Challenges & Risks

5.1 Accuracy & Hallucination Risks

As EHL Hospitality Insights notes, AI must be governed with strict validation layers.

5.2 Integration Complexity

Legacy PMS, CRS and OTA systems can slow down adoption.

5.3 Data Privacy

Hospitality organisations must comply with:

  • GDPR

  • PCI-DSS

  • local data residency rules

Chatbots must not expose PII without encryption and consent.

5.4 Over-Automation

Poorly designed bots frustrate travellers, especially in complex cases such as visa issues or multi-region itineraries.

6. Strategic Recommendations

6.1 Build Hybrid AI + Human Workflows

AI handles:

  • FAQs

  • booking questions

  • itinerary drafts

  • instant rebooking

  • 24/7 availability

Humans handle:

  • escalations

  • complex itinerary builds

  • emotional-sensitive cases

  • VIP travellers

6.2 Prioritise APIs & System Integration

Integrate AI with:

  • airline GDS

  • hotel PMS

  • booking engines

  • loyalty systems

  • CRM platforms

This ensures real-time data accuracy.

6.3 Treat AI as a Revenue Channel, Not a Cost Centre

AI can drive:

  • upgrade revenue

  • cross-sell opportunities

  • personalised bundles

  • direct booking over third-party platforms

6.4 Adopt Agentic AI Early

Companies that deploy agentic AI gain structural advantages:

  • faster response times

  • lower costs

  • richer personalisation

  • higher customer lifetime value

7. Outlook: The Future of AI in Travel & Hospitality

Based on McKinsey, Tredence, and MDPI analyses:

  • LLM-driven trip planning will become mainstream

  • Most customer service will shift to AI-first interactions

  • Travel apps will pivot from “search engines” to “autonomous travel advisors”

  • Hoteliers will use AI for operational optimisation

  • Personalised, dynamic itineraries will replace static guides

  • AI-native travel startups will challenge OTAs with faster discovery and booking flows

Travel companies that adopt early will be positioned ahead of competitors as customer expectations evolve.

Conclusion

AI is rewriting the customer journey in travel—especially in areas such as booking assistance, itinerary creation and FAQ support. With travellers increasingly comfortable using AI tools, and hospitality providers adopting AI at record pace, the industry is moving toward always-on, personalised digital service.

Businesses that embrace conversational and agentic AI will unlock:

  • higher conversion

  • lower support costs

  • improved guest satisfaction

  • richer customer insights

The future of travel is AI-assisted, AI-enhanced and ultimately AI-optimised.

Travel, Hospitality, Booking Assistance, FAQ, Itinerary, AI Customer Service, AI Travel, Custom GPT Use Case, Custom GPT, Travel AIFrancesca Tabor