Why AI Orchestration Will Define the Next Generation of Airport and Travel Services
Why AI Orchestration Will Define the Next Generation of Airport and Travel Services
Publish Date: 2026-06-28 07:56:00
Source Domain: www.cybersecurity-insiders.com
Using an unordered list, summarize the following article with between 4 and 8 key points.
Airports have become one of the most visible testing grounds for AI.
Airlines and airports have invested heavily in technologies designed to improve efficiency and deliver more personalized experiences. This growing prioritization is reflected in reports that in 2025 alone, airlines invested $36 billion in technology while airports spent nearly $15 billion.
The focus is shifting from individual applications to system interoperability. Travelers demand seamless transitions between digital tools and human support.
Airports offer a useful lens into this challenge because expectations are high, conditions can change by the minute, and disconnected systems can quickly turn minor disruptions into major frustrations. As adoption accelerates, the primary challenge is no longer deployment, but orchestration—ensuring systems share intelligence and coordinate actions.
Moving Beyond Isolated AI Experiences
Most AI deployments today are designed to solve specific problems within individual applications or channels. While these siloed tools can be highly effective within their intended scope, customer journeys rarely stay within a single channel.
Before reaching security, travelers interact with multiple assistance systems. Every touchpoint generates context that is currently trapped in isolation.
Every interaction generates valuable context, yet that information is often confined to the system where it originated. This confinement creates friction for customers and significant and operational blind spots for organizations.
AI orchestration addresses this issue by creating a shared intelligence layer that allows information and context to move with the customer rather than remaining trapped within individual systems. Instead of treating each interaction as a separate event, orchestration enables information gathered in one interaction to inform the next.
The Importance of Human Expertise
Weather disruptions are a prime example. While AI can identify alternative flights, complex scenarios—like families with checked luggage—require human judgment.
Orchestration recognizes when to escalate. It routes the traveler to a specialist with full history attached, eliminating repetitive questions and accelerating resolution. This ensures automation adds value while human expertise provides empathy and complex decision-making. It’s what we call a Tandem Care approach, where AI and human expertise work together with full context to make better decisions in the moment.
For travel organizations, this creates opportunities to improve service quality, increase efficiencies and make better use of both AI and human expertise.
Governance and Security Must Be Built into the Architecture
Airport environments provide a useful example because nearly every customer interaction depends on information flowing across multiple systems and stakeholders. By the time a traveler reaches a human representative, information may have already passed through numerous applications, databases and operational workflows.
Technology leaders must understand how information moves through the organization and ensure appropriate controls remain in place as AI becomes more involved in customer-facing operations. As AI expands into customer-facing roles, accountability becomes a strategic requirement.
Data privacy and security remain among the leading concerns of enterprise leaders evaluating agentic AI deployments. As AI systems gain access to more enterprise data and participate in more business processes, organizations need confidence that decisions are explainable, auditable and aligned with governance requirements.
This is particularly important where AI systems interact directly with customers or support critical business decisions. Successful AI scaling requires building governance and oversight into the architecture from day one.
A Model for the Future of Customer Experience
The implications extend beyond travel. With 74% of organizations planning agentic AI deployments within two years, the demand for continuity and consistency is universal.
Meeting those expectations requires more than deploying additional AI tools. It requires connecting systems, preserving context and creating pathways for information to move intelligently between automated and human-led experiences. Physical AI is also increasingly becoming a part of CX, globally, with the integration of robotics and autonomous systems.
Organizations that build these capabilities effectively will be positioned to deliver more responsive, resilient and trusted customer experiences while managing increasingly sophisticated AI deployments.
Airports provide a glimpse of a future where success belongs to those who connect people and technology to respond effectively as circumstances change.
In the evolving CX landscape, trust is earned by making every interaction more seamless, accountable, and human.
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About Tony Lama
Tony Lama is Senior Vice president and General Manager of Avaya software, where he leads the company’s global product strategy, roadmap and go-to-market execution. With more than 27 years of experience in enterprise communications and customer experience technology, he has helped organizations modernize operations, accelerate cloud transformation and adopt AI at scale. Prior to Avaya, Tony held leadership roles at AWS, Twilio, Aspect Software and Edify, where he served as CEO.
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