Tatiana Tantri Indah Sari
The travel industry is currently navigating a transformative period driven by the emergence of agentic artificial intelligence (AI), a sophisticated iteration of AI that promises to collapse the traditionally disparate processes of research, planning, and booking into a single, intuitive conversational interface. This technological leap, while offering unprecedented convenience and personalization, hinges critically on a single, overarching factor: whether travelers will ultimately decide to trust it. Online travel agencies (OTAs) such as Expedia and Booking.com are at the forefront of this integration race, striving to embed their extensive services within the frameworks of large language models (LLMs) developed by tech giants like Google and OpenAI, thereby creating new competitive dynamics and partnership opportunities.
One of the most pressing questions for industry stakeholders, and a frequent query fielded by advanced answer engines like Skift 2.0, revolves around how exactly agentic AI is fundamentally altering the travel booking landscape. The immediate answer points to a paradigm shift in how consumers will interact with travel services, moving away from multi-platform searches and manual comparisons towards a unified, AI-driven concierge experience. Expedia, for example, exemplifies the complex strategy unfolding across the sector. It is actively exploring and integrating with third-party agentic assistants to enhance its offerings, while simultaneously implementing robust measures to police and prevent the unauthorized scraping of its proprietary pricing and inventory data, a critical asset in the highly competitive online travel market. This dual approach underscores the delicate balance between embracing innovation and safeguarding intellectual property in the age of generative AI.
Understanding Agentic AI and Its Evolution in Travel
The concept of agentic AI represents a significant leap beyond earlier forms of artificial intelligence that have gradually permeated the travel sector. For years, basic chatbots provided rudimentary customer service, answering frequently asked questions or assisting with simple transactions. Recommendation engines, powered by machine learning, offered personalized suggestions based on past behavior, but largely operated within predefined parameters. The advent of Large Language Models (LLMs) like OpenAI’s GPT series and Google’s Gemini marked a pivotal moment, enabling AI to understand and generate human-like text, engage in complex conversations, and process vast amounts of unstructured data.
Agentic AI builds upon these LLMs by adding a layer of proactive capability and multi-step task completion. Unlike a passive chatbot that merely responds to queries, an agentic AI can independently initiate actions, orchestrate multiple steps to achieve a goal, and interact with various external tools and APIs. For instance, instead of merely suggesting a flight, an agentic AI could understand a user’s travel preferences, search for flights and accommodations across multiple providers, compare prices, book tickets and hotels, arrange ground transportation, and even suggest activities—all within a single conversational thread. This capability is powered by sophisticated reasoning engines that allow the AI to break down complex requests into smaller, manageable tasks and execute them sequentially. The integration relies heavily on robust API architectures, which allow the AI agent to "plug into" and interact with the back-end systems of airlines, hotels, OTAs, and other travel service providers.
A Shifting Competitive Landscape: OTAs and AI Giants Vie for Dominance
The strategic maneuvers by established OTAs and burgeoning AI developers are reshaping the competitive dynamics of the travel industry. For OTAs, the imperative is clear: adapt or risk disintermediation. Companies like Expedia and Booking.com have invested heavily in AI research and development, recognizing that future customer engagement will increasingly occur through conversational interfaces.
OTAs’ Strategic Maneuvers:
Expedia Group, under the leadership of CEO Peter Kern, has articulated a strategy that embraces AI as both a partner and a potential threat. While integrating its vast inventory and booking capabilities with third-party agentic assistants, thereby expanding its reach, Expedia has also become a vocal advocate against the unauthorized scraping of its proprietary data. This data, encompassing real-time pricing, availability, and user reviews, is the lifeblood of its business model. Unfettered access by AI models could erode its competitive advantage and undermine its significant investments in data aggregation and processing. Inferred statements from Expedia executives often highlight the balance between fostering innovation through partnerships and safeguarding intellectual property to ensure a fair competitive environment. They emphasize that while AI offers immense potential for enhancing the customer journey, the foundational data that makes those journeys possible must be protected.
Booking.com, a subsidiary of Booking Holdings, has adopted a similar approach, focusing on leveraging AI to enhance personalization and streamline the booking process. The company has experimented with AI-powered trip planners and recommendation engines, aiming to provide a more intuitive and efficient experience for its global user base. Their strategy often involves developing proprietary AI capabilities while also exploring integrations with external LLM providers, ensuring they maintain control over their core booking funnel and customer relationships. Executives from Booking Holdings have consistently pointed to AI as a key driver for future growth, enabling them to offer hyper-personalized travel itineraries and dynamic pricing in real-time.
The urgency for OTAs stems from the understanding that if AI agents become the primary interface for travel planning, the direct traffic to their websites and apps could diminish. Their value proposition will increasingly rely on the depth of their integrations, the quality of their data feeds, and their ability to offer exclusive deals or bundled services that AI agents can seamlessly access and present to users.
AI Developers’ Inroads:
Tech giants like Google and OpenAI are not merely providing the underlying AI technology; they are actively positioning themselves as central players in the travel ecosystem. Google, with its longstanding presence in travel search (Google Flights, Google Hotels) and its powerful AI capabilities (Bard, Gemini), is uniquely positioned. Its agentic AI could leverage its vast knowledge graph and real-time data to offer comprehensive travel planning directly within its search interface or through its AI assistant. This could potentially disintermediate OTAs by providing a direct path from intent to booking, though Google has often maintained a partnership-oriented approach with travel providers.
OpenAI, through its ChatGPT platform and its expanding plugin ecosystem, has already demonstrated the potential for agentic AI in travel. Users can now enable plugins that allow ChatGPT to interact with services like Expedia, Kayak, and Tripadvisor, enabling it to search for flights, hotels, and even make reservations. Microsoft, a major investor in OpenAI, is integrating similar capabilities into its Copilot assistant, promising a seamless travel planning experience directly from productivity applications. The race among these AI developers is to become the default "AI travel agent," capturing user attention and loyalty at the very beginning of the travel planning funnel.
The Traveler’s Perspective: Trust, Personalization, and Potential Pitfalls
For the end-user, agentic AI promises a new era of travel planning characterized by unprecedented convenience and hyper-personalization.
Benefits:
A recent survey by Amadeus (2023) indicated that 65% of travelers are open to using AI for trip planning, citing time savings and personalized recommendations as key motivators. Agentic AI can learn individual preferences over time, crafting itineraries that perfectly match interests, budget, and travel style. Imagine an AI agent that knows you prefer boutique hotels, vegetarian dining, and early morning flights, and automatically factors these into every suggestion. This seamless planning can significantly reduce the mental load associated with organizing complex trips, saving hours of research across multiple websites. Furthermore, by accessing a wider array of booking options and dynamically comparing prices, AI agents could potentially uncover better deals or more optimized itineraries than a human might find.
Challenges and Concerns:
Despite the allure of convenience, several critical challenges remain, primarily centered around trust.
- Trust in Accuracy and Reliability: Travelers need to be confident that the information provided by the AI is accurate, up-to-date, and that bookings made through the agent are reliable. What happens if an AI-booked flight is cancelled, or a hotel reservation is incorrect? The accountability framework for AI-driven bookings is still evolving.
- Data Privacy: Agentic AI requires access to significant personal data—preferences, past travel history, payment information—to deliver personalized experiences. Concerns about how this data is collected, stored, and protected are paramount. A 2023 Deloitte study on consumer trust in AI revealed that while adoption is growing, privacy concerns remain a significant barrier for 45% of consumers.
- Bias in Recommendations: AI models are trained on vast datasets, and if these datasets contain inherent biases, the AI’s recommendations could reflect them. This might lead to a lack of diversity in suggested destinations, accommodations, or activities, potentially creating "filter bubbles" where users are only exposed to information that reinforces existing preferences.
- Loss of Human Touch and Disintermediation: While efficient, some travelers value the human element of travel planning—the expert advice of a travel agent, the personal touch of a customer service representative. Over-reliance on AI could lead to a perceived loss of empathy or nuanced understanding in complex situations. The challenge for AI is to augment, rather than completely replace, the human connection.
The Data Dilemma: Scraping, Proprietary Information, and Fair Use
At the heart of the agentic AI revolution in travel lies a fundamental conflict: AI models require vast quantities of data to learn, operate, and provide accurate, comprehensive results. Much of this critical data—including real-time pricing, inventory, user reviews, and proprietary algorithms—resides on the platforms of OTAs and other travel providers. This creates a significant "data dilemma."
Expedia’s proactive stance on policing AI scraping highlights this tension. The company views its aggregated data as a proprietary asset, built through years of investment and strategic partnerships. Unauthorized scraping by AI models, whether for training purposes or to power competitive services, is seen as a threat to its business model and a violation of its terms of service. This isn’t just about protecting current revenue; it’s about safeguarding the competitive edge derived from unique data insights. The legal and ethical implications of AI scraping are complex and largely uncharted territory. Existing copyright laws and terms of service are being tested by the scale and speed at which AI can ingest information.
The industry is grappling with how to balance the need for AI innovation, which thrives on data access, with the rights of data owners to protect their intellectual property. This will likely lead to a mix of approaches:
- API-driven Partnerships: Secure, controlled access to data through mutually beneficial API agreements, allowing AI agents to query and book through official channels.
- Data Licensing: Formal agreements for AI developers to license proprietary data for training purposes.
- Legal Challenges: Increased litigation over unauthorized data scraping, as companies seek to enforce their rights.
- Industry Standards: The potential emergence of industry-wide protocols for ethical data use and AI interaction.
This data dilemma will undoubtedly shape the future partnerships and competitive strategies between AI developers and travel companies, determining who controls the flow of information and, ultimately, the customer relationship.
Broader Implications and the Future of Travel
The advent of agentic AI extends its influence far beyond the immediate interactions between travelers and booking platforms, promising to ripple through the entire travel ecosystem.
Impact on Travel Suppliers (Airlines, Hotels, Tour Operators):
For airlines, hotels, and tour operators, agentic AI presents a double-edged sword. On one hand, it could lead to reduced direct bookings if AI agents become the primary booking channel, potentially increasing reliance on intermediaries and impacting profitability due to commission structures. On the other hand, AI platforms offer new, highly personalized distribution and marketing channels. Suppliers will need to ensure they have robust, real-time APIs that can seamlessly integrate with AI agents, providing accurate inventory and pricing. This might also necessitate a re-evaluation of their direct booking strategies, perhaps focusing on unique value propositions or loyalty programs that AI agents can’t easily replicate or disintermediate. The ability to push dynamic, personalized offers through AI channels could become a significant competitive advantage.
Job Market Transformation:
The widespread adoption of agentic AI will inevitably lead to a transformation of the travel industry’s workforce. Traditional roles, particularly those focused on repetitive booking tasks or basic customer service, may see a decline. A 2023 report by the World Economic Forum predicted that AI could displace millions of jobs globally, with sectors like customer service being particularly vulnerable. However, this shift is also expected to create new roles. There will be an increased demand for AI prompt engineers who can effectively communicate with and train AI agents, AI experience designers focused on optimizing user interaction, data scientists to manage and analyze the vast datasets, and specialists in AI ethics and governance to ensure fair and unbiased outcomes. Travel agents, rather than disappearing, may evolve into high-value consultants, focusing on complex, bespoke itineraries, crisis management, or niche travel experiences that require human empathy and judgment.
Regulatory Landscape:
As agentic AI becomes more pervasive, regulators globally will face increasing pressure to establish clear guidelines and frameworks. Key areas of concern include:
- Transparency in AI: Demands for clarity on how AI makes decisions and generates recommendations.
- Consumer Protection: Ensuring accountability for AI-driven bookings, protecting consumers from misleading information, and establishing clear recourse mechanisms in case of errors.
- Anti-Monopoly Concerns: Monitoring the concentration of power among a few dominant AI platforms or data aggregators.
- Data Protection: Extending existing regulations like GDPR and CCPA to cover the unique challenges posed by AI’s data collection, processing, and usage, particularly concerning sensitive personal information used for personalization.
Innovation and Competition:
The intense competition among tech giants and OTAs is spurring rapid innovation. This environment could also empower smaller, agile players to develop niche AI solutions for specific travel segments or unique challenges. Startups focusing on sustainable travel planning, accessibility-focused itineraries, or hyper-local experiences, leveraging AI to connect with specific user needs, could find new avenues for growth. The constant push for more intuitive, efficient, and personalized AI experiences will continue to drive technological advancements across the board.
Conclusion: A Transformative, Yet Evolving Journey
The travel industry stands at a pivotal juncture, poised for significant transformation driven by the relentless advancement of agentic AI. This powerful technology promises a future where travel planning is seamless, hyper-personalized, and incredibly efficient, collapsing complex multi-step processes into intuitive conversations. However, realizing this potential hinges on overcoming substantial challenges, primarily the critical need to build and maintain traveler trust.
The ongoing strategic dance between established online travel agencies like Expedia and Booking.com, and AI powerhouses such as Google and OpenAI, defines the current landscape. While OTAs seek to integrate AI to enhance customer experience and operational efficiency, they simultaneously grapple with the imperative to protect their proprietary data, a cornerstone of their competitive advantage. The data dilemma, concerning the ethical and legal boundaries of AI scraping, will continue to be a defining battleground, shaping future partnerships and regulatory interventions.
For travelers, the benefits of agentic AI—unprecedented personalization, time savings, and potentially better deals—are compelling. Yet, concerns about data privacy, the accuracy of AI-generated information, potential biases, and the loss of human interaction remain significant hurdles to widespread adoption. Addressing these concerns through transparent AI development, robust ethical guidelines, and clear accountability mechanisms will be crucial.
Beyond the immediate booking interface, agentic AI will have profound implications for travel suppliers, the global job market, and the regulatory environment. It will necessitate adaptability from airlines, hotels, and tour operators, who must refine their strategies for distribution and direct engagement. It will also reshape the workforce, demanding new skills and fostering the emergence of new roles. Ultimately, the journey with agentic AI in travel is not merely about technological adoption; it is about a holistic transformation that requires careful navigation, collaborative innovation, and a steadfast commitment to ethical development to truly unlock its potential for a more intelligent and enjoyable travel experience.
Anjar Salim
Chandra Hamzah
Budi Mulyono
