AI Is Now Table Stakes, So What Comes Next? Understanding Agentic AI in Travel and Hospitality & By Duane Overgaard

The rapid ascent of generative AI rests on a simple operational truth: organizations that can harness and unify large, diverse datasets are able to build more efficient systems and deliver more relevant experiences. In travel and hospitality, every booking, modification, payment event, and on-property interaction produces signals that, when connected, enable faster decisions and more precise service. Generative models have become the engine that turns these signals into actions, refining distribution, streamlining operations, and elevating the traveler journey from planning through post-stay. Investment has followed. And the overwhelming majority (73%) of senior leaders  in hospitality reported increasing AI budgets, and industry analysis shows broad confidence that AI is improving core traveler touchpoints.

The question for executives is no longer whether to deploy AI, but how to design for what comes next. That next phase is agentic AI systems that don’t just analyze and recommend, but act with autonomy, in context, and at enterprise scale. Traditional automation excels at routine steps, yet struggles when data is incomplete, when systems are fragmented, or when conditions change mid-journey. Agentic systems operate more like collaborators than tools: they learn from machine data and human feedback, adapt to shifting inputs, and execute cross-functional work with speed and consistency. In an industry where an early-arrival note touches front office, housekeeping, F&B, and transportation, this shift from suggestions to end-to-end execution is decisive. 

The most visible pressures sit in distribution and the supplier–distributor relationship. Global chains and independents depend on a complex grid of GDS, OTAs, TMCs, wholesalers, and metasearch to reach demand. Each node imposes different content, pricing, and policy requirements, and stale or inconsistent data can create leakage, misrepresentation, and friction with partners. The architecture is resilient but not uniformly adaptive. Agentic AI changes tempo by translating property data into structured, channel-ready content in near real time, aligning availability and offer presentation to demand signals rather than schedules, and compressing the lag between a change in conditions and its reflection across channels. This is not a theoretical construct; it is the operating model required by a market that now moves faster than batch processes. 

Business travel exposes a second set of constraints, and an immediate opportunity for agentic systems. Despite decades of digitalization, a meaningful share of global corporate hotel bookings still triggers manual phone or email exchanges between agents and properties to confirm details, verify payments, collect invoices, or resolve discrepancies. DerbySoft’s AI Voice Agent was built for this class of work. Operating continuously across time zones, it confirms booking elements, validates virtual card details, and secures compliant invoices, reducing manual call costs for early adopters while freeing agents for higher-value program management. External coverage of recent pilots points to significant reductions in manual handling and a growing share of bookings completed without human intervention. 

Financial precision is the companion problem. Commission reconciliation has long consumed time and attention on both sides of the supplier–distributor relationship, with errors and omissions dragging out payment cycles and clouding cash-flow visibility. DerbySoft’s acquisition of Arise brought specialized AI automation for agent–hotel communication and commission reconciliation into our platform, consolidating booking data into unified records and accelerating accurate settlement for both TMCs and hoteliers. The transaction reflects a broader market direction: integrating targeted agentic capabilities into established connectivity to remove long-standing friction instead of adding yet another silo. 

Customer experience is where agentic AI becomes most tangible for travelers. A leading OTA recently introduced a planning assistant that builds and adjusts complex itineraries, rebooks automatically during disruptions, and communicates directly with customers—compressing wait times and lifting satisfaction by resolving problems at source. A major U.S. airline unveiled an AI-driven digital concierge integrated into its app to guide journeys, manage disruptions, and coordinate multi-modal options. Many hotel brands are rolling out AI concierges that curates hyper-local recommendations and coordinates on-property experiences with staff oversight. These initiatives differ in execution yet share the same principle: moving from episodic assistance to continuous, context-aware action. 

The marketing layer is evolving in parallel. Performance teams have long tuned budgets and bids across metasearch, paid search, and OTA media with sophisticated but manual routines. Agentic systems now adjust spend and creative in response to demand patterns, inventory, and audience signals in real time. DerbySoft’s AI-powered digital marketing solutions reflect that direction, combining automation with optimization to manage multichannel performance at operational speed. The outcome is not just improved return on ad spend, but a marketing function that is synchronized with distribution and revenue rather than adjacent to it.

These capabilities are powerful, but adoption is not automatic. Most hotel companies operate dozens of systems—PMS, CRS, POS, spa, CRM, transport—procured over years, each with its own data model and API posture. Incomplete integrations force handoffs, and edge cases remain common in daily operations. Successful implementations therefore start with high-impact workflows where data quality and interfaces are within reach, layer in human oversight for exceptions, and expand as confidence and connectors mature. Industry guidance stresses data integration, explainability, and measured piloting as critical to trust and scale, especially where autonomy touches financial transactions or traveler itineraries. 

The sector examples you referenced underscore this trajectory. During irregular operations, agentic systems detect disruption signals, rebook inventory against policy, notify travelers, and resolve downstream logistics without waiting in a queue. In trip planning, agents assemble itineraries that adapt to preference shifts, availability, and local context rather than serving static recommendations. In pricing and revenue, models apply continuous context to protect yield while staying competitive. In loyalty, programs move from passive accrual to proactive engagement that anticipates attrition risk and responds with relevance. In hotel operations, agents coordinate housekeeping and maintenance against live occupancy and arrival forecasts, reducing waste and smoothing peak loads. Each is a version of the same structural change: decisions moving closer to the moment they are needed. 

The implications for GDS and TMC workflows are pragmatic rather than rhetorical. GDS remains essential infrastructure for enterprise travel, but the work surrounding it—content quality, policy enforcement, exception handling, reconciliation—benefits from agents that act across systems. TMCs can redeploy human time from repetitive verification to advising on program design, supplier strategy, and traveler well-being, while traveler experiences improve because problems are addressed before they become calls. Reports covering AI deployments across airlines and intermediaries suggest that this pattern is beginning to scale, and that regulatory scrutiny will rise alongside it, particularly in areas like dynamic pricing and explainability. Governance and transparency will therefore sit alongside engineering as leadership priorities. 

DerbySoft’s roadmap aligns to these realities. Connectivity remains the foundation, because agents are only as effective as their access to accurate, timely data and the ability to execute safely across systems. The addition of AI Voice Agent targets one of the industry’s most entrenched operational bottlenecks: repetitive outbound calls to properties. The integration of Arise’s automation strengthens the financial backbone by unifying records and compressing reconciliation cycles. Our digital marketing solutions extend autonomy to the growth engine, so demand generation adjusts with the same agility as distribution. These are not discrete tools; they are complementary capabilities designed to reduce friction across the travel commerce stack. 

What comes next is a design challenge more than a technology purchase. Teams will need to clarify where autonomy creates value and where human judgment must remain primary, and they will need to build clear escalation paths between the two. Leaders will need to invest in data disciplines that support agentic behavior across brands, regions, and partners. And they will need to engage proactively with evolving regulation to ensure that pricing, personalization, and decisioning remain transparent and fair. Those moves turn AI from capability into advantage.

DerbySoft’s moves, from acquiring Arise to launching AI Voice Agent and expanding AI-powered marketing, signal how the industry is shifting from automation to autonomy. These are not isolated innovations but part of a larger convergence where intelligence is embedded directly into the connective tissue of travel commerce.

The future belongs to organizations that embrace this shift. AI is now table stakes. The competitive horizon lies in agentic intelligence: systems that do not simply support decisions, but carry them out, ensuring that operations, distribution, and guest experiences move in sync with the speed and complexity of global travel.

About the Author

Duane Overgaard is the Divisional CEO, Hospitality, of DerbySoft. With over 30 years of experience in the hospitality industry, he has a diverse skill set that includes account management, business development, and contract negotiation. Duane has held various leadership positions at renowned companies such as Sabre Corporation, Wyndham International, and Hilton Hotels & Resorts, where he has demonstrated expertise in hotel management and marketing strategy. He is known for his strong team-building and competitive analysis skills. Duane is currently based in the Dallas area of the United States.