Travel & Hospitality: How are AI and Agentic systems redefining the traveler experience?

As a travel & hospitality expert at Converteo, Charlotte Poulin provides her in-depth knowledge of the challenges and specific expectations of this market. In close collaboration with her, Guilhem Bodin, Partner of AI, Agentic & Data at Converteo, supports marketing and digital departments. Hamza Senoussi, Senior Manager in Data & AI Transformation, leads strategic projects that leverage data and the integration of AI agents for measurable impact. Finally, David Spire, Partner of AI and Product Management at Converteo, joins them to help organizations transform their product strategy in the age of AI and data, specializing in AI product build and agentic AI.

Key Takeaways

• The Traveler of tomorrow and AI: Newer generations (Gen Z and Millennials) and emerging markets (India, China) demand ultra-personalized experiences, simplicity, and seamless omnichannel journeys—expectations that AI meets with proactivity and individualization, without dehumanization.
• The rise of GEO and Agents: Generative answer engines are transforming visibility and engagement. “Agents” (ChatGPT Agent, Booking Filters, Travel Assistants) are taking control of purchasing journeys, shifting traffic and making “citations” and e-reputation more critical than a simple link.
• Hyper-personalization, AI, and the Content Factory: Producing text and visual content at scale has become essential for hyper-personalization. AI-driven “Content Factories,” composed of multiple agents (for creation, assembly, and quality assurance), make it possible to industrialize production while ensuring brand compliance and consistency.

The travel and hospitality sector is on the verge of an unprecedented transformation, driven by the emergence of generative AI and agentic systems. Far from being a mere technological innovation, this is a paradigm shift that is redefining the consumer relationship and disrupting traditional strategies. How can players in this market navigate this revolution to turn challenges into opportunities?

The new face of the traveler: New behaviors, new expectations with AI

Web traffic and traditional customer journeys are undergoing a major shift. Users are no longer content to browse passively; they are looking for smooth, personalized, and proactive experiences. This evolution is catalyzed by the emergence of new generations of travelers and markets:

• The impact of new generations and markets: Soon, one in two travelers will come from India and China, bringing with them distinct consumer habits. Gen Z and Millennials, now the majority, favor “bleisure” (combining business and leisure), solo or multi-generational travel, and seek unique experiences where they feel “alone in the world” and pampered.
• The ecology vs. price equation: Although environmental awareness is gaining ground, price remains the primary selection criterion. Brands must therefore innovate to offer value-added deals that align with environmental concerns without sacrificing price attractiveness.
• AI for omnichannel and hyper-personalization: Faced with complex purchasing journeys (over 70% of users consult up to 10 sources), AI is becoming the key to orchestrating existing channels and delivering the right message at the right time. Hyper-personalization, a frequently mentioned concept, is now becoming a reality with AI, enabling “individualization without dehumanization,” which is essential in a sector where human connection is paramount. Travelers trust AI, with 18% of queries on LLMs already related to travel in 2025.

The expansion of intelligent agents in the customer journey

The technological ecosystem is evolving at high speed, with major innovations reshaping how travel is designed, researched, and booked. “Agents” are no longer fiction but a reality that takes various forms:

1. Action and delegation agents (ChatGPT Agent, Flight Deals): These agents can take over for the consumer, automating complex tasks like buying train tickets (ChatGPT Agent) or finding flights using natural language queries (Google Flight Deals). They transform “search” into “action delegation.”
2. Integrated and conversational agents (Apps in Chats, Booking Filters): Players like Accor are integrating directly into LLMs to offer their products within conversations. Booking uses smart filters that apply search criteria automatically through conversational language, drastically simplifying the user experience. Marriott and Expedia are developing inspiration engines and travel assistants (Romi for Expedia, increasing customer satisfaction by 15%).
3. Service and assistance agents (Miami Airport, Westjet, Four Seasons): AI is not limited to booking. Examples like Miami Airport’s conversational AI for people with disabilities, Westjet’s Juliette agent handling claims, or the Four Seasons’ 24/7 concierge service on WhatsApp show how AI enriches the physical experience and post-booking customer service.

These developments are pushing brands to rethink their presence on their owned assets and within these new answer engines. Optimizing for GEO is becoming crucial, as the relevance of the “citation” and the semantic richness of product feeds will determine their ability to capture attention in AI-synthesized responses.

The AI Content Factory: Industrializing creation in the age of hyper-personalization

One of the major challenges of agentic systems is the ability to produce massive amounts of ultra-personalized content. Generative AI offers a solution by revolutionizing production:

• The Potential of AI for Content: AI can generate text (hotel descriptions, landing pages, multilingual translations) and visuals (images, animations, short and long videos) on an unprecedented scale. While 70% of stored marketing content often goes unused, AI allows for targeted and high-performing production.
• The Challenges of Industrialization: Adopting AI at this scale faces obstacles:
  • Integration and Distribution: The bottleneck is not creation but the integration of generated content into CMSs, marketing automation tools, and distribution channels, which requires a connected multi-agent architecture.
  • Governance and Compliance: Managing data quality (DAM), legal compliance (image rights, intellectual property of AI creations), and ethical considerations (disclosing the AI origin of a production) are major issues. Close collaboration with legal teams to define clear frameworks is essential.

The “Creative Factory” of Converteo in action

To concretely illustrate the power of these concepts, Converteo’s “creative factory” presents itself as an agentic platform. Created for the fictional brand “Converteo Hotels,” this interface allows a campaign creator to initiate a detailed brief by defining the campaign, brand, season, and location, while integrating specific instructions and contextual files. A text model (Gemini) processes the brief to generate a scene concept (object, lighting, mood, colors), while a chatbot allows for iteration and refinement of the concept.

The platform then generates a “visual master” using an image generation model (Imagni) and adapts this visual into various formats (vertical, horizontal, square), automatically integrating the brand’s brand book (logo, colors, fonts).

Beyond visuals, the factory also generates emails and SMS from the produced text, and most importantly, adapts images and text messages for different languages (French, Spanish, Italian, Japanese), even going as far as cultural adaptation (for example, avoiding glasses of wine in a campaign for the United Arab Emirates). This demonstration highlights the ability of multi-agent systems to industrialize personalized, consistent, and compliant content production.

Google and OpenAI in the travel sector

The AI landscape is dominated by two giants who approach this revolution with distinct strategies:

• OpenAI, the disruptor and its monetization strategies: Starting from scratch, OpenAI is actively seeking to monetize its innovations. The integration of advertising into conversations and the possibility of acting as a marketplace through partnerships (e.g., Shopify) show a desire to become a full-fledged distribution channel. OpenAI needs to capture behavioral data to compete with historical players.
• Google, the historical giant and its adaptation challenges: With decades of data and a well-established advertising ecosystem, Google is proceeding with caution. Its challenge is to avoid cannibalizing its existing advertising revenue while responding to new user behaviors. The gradual integration of Gemini into the search engine, innovations like shopping in AI Mode, and Branded AI Agents (allowing users to “chat” directly with a brand) illustrate an approach aimed at keeping the user and the transaction within its ecosystem.

These two dynamics raise the question of disintermediation for brands: how to maintain control of the customer relationship when agents act upstream of visits to owned assets?

Capitalizing on data by creating a “builder” culture

Beyond the technical and strategic aspects, the AI transformation requires a cultural evolution within companies, where capitalizing on data becomes a fundamental lever. The importance of fostering a “builder culture” is paramount: every employee is encouraged to embrace AI. This means not only giving everyone the ability to experiment and prototype, but above all, to understand how deep and refined data is the fuel for AI.

This approach promotes acculturation where teams grasp the importance of the quality, structuring, and use of their own data to feed AI models. By allowing employees to become concretely familiar with the tools and potential of artificial intelligence, backed by a perfect mastery of data, companies can stimulate innovation from within and facilitate the transition from proofs of concept to large-scale deployments.

Feedback from experience: Jean-Marie Dabbaghian (Accor)

The integration of AI within large hotel groups like Accor illustrates the complex dynamics of this transformation. Major market players have embarked on ambitious projects, facing ethical challenges, the need for internal team acculturation strategies, and the goal of using AI to improve productivity. These initiatives show that real use cases can effectively address user problems while managing the organizational and cultural aspects inherent in the large-scale deployment of artificial intelligence.

Driving change: Strategies for brands in Travel & Hospitality

Inaction is not an option. For brands in the Travel & Hospitality sector, the strategy must be proactive and focus on two major axes:

1. Optimize external visibility and agentic influence: It is imperative to understand how your brand is perceived and cited by LLMs and agents. This involves auditing your e-reputation, optimizing your content for AI synthesis (GEO), and semantically enriching your product feeds. These platforms must be seen as new distribution channels, with their own rules.
2. Strengthen AI culture and internal governance: The deployment of AI and agentic solutions must not remain at the proof-of-concept stage. This requires breaking down organizational silos, acculturating teams to the challenges of AI, defining a clear vision (AI roadmap), and building an evolving technical architecture (orchestration of specialist agents, connection to existing IS). Governance, particularly on data quality and legal/ethical aspects, is the cornerstone of a successful transformation.

Tomorrow’s journey will be conversational, ultra-personalized, and largely delegated to artificial intelligences. The brands that can capitalize on their deep user knowledge and integrate AI into a strategic and operational vision will be the ones that come out on top.