In Pursuit of Clean Data for an Agentic Travel Future
The travel industry is entering a pivotal moment. As agentic AI (autonomous systems that can act on behalf of a user) becomes more feasible, the quality of data underpinning those systems becomes critical. According to PhocusWire, the ambition is for travel agents to evolve into AI agents that can make decisions without human supervision. But that ambition depends on trust, and trust depends on clean, consistent, and interoperable data.
The Promise of Agentic Systems
Agentic AI could transform how travellers plan, book, and experience trips. Rather than manually selecting flights, hotels, tours and so on, travellers might issue high-level instructions like “give me a five-day nature-and-culture trip within two hours of London” and let the AI handle the rest. This extends beyond recommendation engines or chatbots, it’s about agents that reason, act, adjust options and execute transactions autonomously.
As generative AI advances (for example Google’s Gemini or OpenAI’s latest models), the building blocks for such agents are forming. But a crucial prerequisite is that underlying systems and databases be ready: able to speak the same language, connect reliably, and present data in forms agents can trust and use.
Why Clean Data Matters
The travel ecosystem is notorious for fragmented legacy systems, inconsistent data formats, and silos across suppliers, OTAs, distribution systems, property management systems and more. Without a reliable, “clean” foundation, issues like mismatched rates, incorrect availability, identity errors or broken bookings escalate.
Clean data means:
Consistency — common data models, standards, taxonomies
Accuracy — correct, validated values (rates, dates, property features, availability)
Timeliness — minimal latency or stale data
Interoperability — APIs, connectors, schemas that let systems interact smoothly
Agents depend on that. If the AI agent pulls incorrect availability or rate data, user trust falters.
Key Areas of Impact
Here are some of the domains in travel where agentic AI and clean data intersect:
Operations and backend systems. Operational orchestration, such as dynamic pricing, yield management, availability updates, is already data heavy. Autonomous agents will require deeper integration across internal systems. Travel companies may need new roles (e.g. Chief AI Officer) and architectures to support that future.
Distribution and channel dynamics. A central question: will agentic systems prefer OTAs or go straight to suppliers? Agents will likely favour direct, clean APIs and minimal friction. That could shift power structures in distribution.
Traveller experience and in-destination services. Agentic assistants could handle real-time itinerary changes, suggestion delivery, dynamic reconfiguration, bookings while en route, etc. But doing so reliably depends on real-time, correct local data (weather, transport, events).
Digital identity and permissions. For agents to act, they need authorised access to traveller identity, preferences, loyalty status, payment, etc. This demands secure and trustworthy identity infrastructure and consented data sharing.
Challenges to Address
Transitioning to an environment where agents thrive is not trivial. Key barriers include:
Legacy systems and fragmented data models. Many travel players run decades-old systems that don’t integrate neatly with modern AI architectures. Clean data often requires significant rework or replacement.
Privacy, consent and trust. How do travellers feel about AI agents having access to personal details, booking authority, or identity credentials? Transparency and governance are vital.
Uneven supplier readiness. Smaller suppliers (independent hotels, local experiences) may lack the infrastructure, APIs or digital maturity to fully participate in agentic future.
Power shifts and competitive tensions. Agents may privilege suppliers with high data quality or direct access, potentially marginalising intermediaries. The balance between OTAs, suppliers and new agent layers is uncertain.
Data governance and standards. Without industry-wide agreement on schemas, protocols, taxonomies, agents will struggle to navigate a patchwork of systems effectively.
Steps Toward Clean Data Readiness
To prepare for the agentic future, travel organisations should:
Audit and clean existing data sets, identify gaps and inconsistencies
Invest in common data models, APIs and middleware that support interoperability
Establish governance, validation and monitoring to ensure data accuracy
Pilot small agentic features (e.g. automation in booking or suggestion agents)
Build trust through transparency in how the AI uses data, and secure identity/permission handling
Aggregate or partner to support smaller suppliers in data maturity
Why This Matters
We are at a crossroads in travel. The idea of AI agents acting fully autonomously on behalf of travellers may sound futuristic, but the foundations are being laid now. If industry players don’t take steps to ensure their data is clean, consistent and integrable, they risk being sidelined by more agile competitors.
Clean data is not a technical luxury—it is the currency on which the agentic travel future depends. For travel brands and technology firms, this is the moment to invest defensively and proactively. Your ability to operate in an agentic world could define whether you lead the next wave of travel innovation or get left behind.
