From Business-to-Customer and Business-to-Business to Agent-to-Agent: The Evolution of Airline and Airport Leadership

The aviation industry is entering a new phase of technological transformation. In addition to established business-to-consumer (B2C) and business-to-business (B2B) interaction models, agent-to-agent (A2A) concepts are emerging as a new perspective for interaction and value creation. In this model, AI-based agents increasingly act as the primary interface between customers and aviation service providers. They orchestrate services, compare offers, and execute transactions autonomously on behalf of travelers. This development fundamentally changes how airlines and airports design customer access, service processes, and digital interaction.

A new interaction paradigm in aviation

For airline and airport management, this development represents a fundamental change. Future customer access, market differentiation, and operational efficiency will no longer depend exclusively on the quality of classical customer touchpoints. Instead, they will increasingly depend on how consistently companies position themselves in emerging agent ecosystems.

The introduction of A2A structures is therefore not only a technological issue but also a strategic, organizational, and methodological challenge.

Agent-to-agent describes a business and interaction model in which companies provide their services primarily not to human users but to autonomous or semi-autonomous AI agents. These agents act on behalf of travelers, companies, or platforms. They make decisions based on defined goals, logic, and preferences; compare offers; initiate bookings; and control services independently. Humans remain strategic decision-makers, while operational execution is increasingly carried out by AI agents.

Changing competitive dynamics for airlines

For airlines, this development can shift the competitive landscape. Where emotional brand messaging, visual user interfaces, and traditional marketing approaches previously dominated, machine-readable and algorithm-friendly differentiation is becoming more relevant.

Booking class logic, ancillary offers, service levels, customer loyalty programs, and operational reliability are analyzed, compared, and prioritized independently by AI agents.

As a result, airlines no longer compete exclusively for the attention of passengers but increasingly for the preference of intelligent AI agents that evaluate options rationally, in a rules-based and data-driven way.

The evolving role of airports

The business model for airports may also change. The role of airports is evolving from primarily infrastructure providers to service-oriented platforms.

Intelligent agents can orchestrate parking, security slots, lounges, and additional services before the trip begins. Physical passenger interaction is therefore prepared before the traveler even enters the airport.

The airport thus becomes part of a broader agent-based service ecosystem.

Technological progress enabling agentic ecosystems

At the same time, the technological maturity of agentic AI has improved. Modern AI agents can understand complex user intentions, pursue long-term goals, learn from interactions, and act across contexts, systems, and providers.

This development is supported by technological advances such as cloud architecture and emerging standards for interoperability.

Standards such as the Model Context Protocol (MCP) simplify interoperability by enabling agents to access enterprise data and tools through a unified integration layer rather than custom APIs. For aviation, this means AI agents can directly interact with operational systems to trigger bookings, access relevant data sources, and automate end‑to‑end service processes. This creates a scalable foundation for more integrated and efficient airline and airport operations.

From user experience to agent experience

Moreover, the rise of agentic AI shifts the design paradigm from the traditional user experience (UX) toward the agent experience (AX).

While UX emphasizes visual design, usability, and emotional perception, AX focuses on structural and logical foundations that allow intelligent agents to operate reliably. This requires clearly defined rules, transparent decision frameworks, and full traceability of agent behavior.

AX also changes the role of design. Instead of creating predefined user journeys, designers increasingly develop flexible interaction environments that allow agents to dynamically adapt services to individual needs.

Within this framework, AX focuses on the structured development and optimization of digital environments in which AI agents operate. Its objective is to enable agents to perform efficiently while ensuring that outcomes remain human-centered.

Delivering such environments requires expertise in conversation design, prompt engineering, and the development of robust ontologies. At the same time, human-in-the-loop (HITL) mechanisms are required to maintain transparency, governance, and trust in agent-driven interactions.

Strategic implications for leadership

For airline and airport leadership, these developments result in new strategic requirements.

The agent experience must increasingly be established as an independent objective. Traditional marketing and performance metrics may be complemented by new indicators such as recommendation rates by agents, selection frequency within agent environments, or the automated solution rate of service cases.

Value propositions must therefore be formulated clearly and consistently to be interpretable by agents and to meet the requirements of agent-based ecosystems.

Transformation management as a success factor

Furthermore, the introduction of A2A structures also requires coordinated transformation management.

Agent-based initiatives typically involve various stakeholders, cross-organizational processes, and strategic considerations related to customer access and data control. Leadership therefore takes on an orchestrating role between strategy, technology, partners, and organizational structures.

In this environment, airline and airport managers increasingly act as coordinators between business goals, technical systems, and agent logic. Key questions include which decisions can be delegated to AI agents, where human oversight remains necessary, and how governance and escalation mechanisms should be designed.

From a management perspective, several strategic questions arise:

• How should airlines and airports position themselves within emerging agent ecosystems?
• Where does agentic AI create measurable value?
• Which processes need to be redesigned to enable this value creation?
• What governance structures ensure security, brand consistency, and scalability?

Technological considerations include future-proof IT architecture, interoperability standards, and data sovereignty. At the organizational level, new competencies, roles, and change management approaches become necessary.

Finally, the objective should be an agent-enabled operating model that clearly defines human-agent-system interaction, governance mechanisms and scalable use case development.

Agent-to-agent interaction represents an important evolution in the aviation industry. As AI agents increasingly act on behalf of travelers, airlines and airports need to adapt their systems, processes, and strategic positioning.

Future competitiveness will depend on how effectively organizations enable their services for agent-driven interaction, and how well they manage the integration of human decision-making and intelligent automation.

Author:

Florian Volk is Consultant in the Solution Group Customer Experience at Lufthansa Consulting.