What is agentic AI and how will it impact airports?

What is Agentic AI and how does it differ from generative AI?

Since 2022, there has been an explosion in the use of artificial intelligence (AI) affecting how we work and communicate. Most people have become familiar with one form of AI called generative AI, encompassing chatbots like ChatGPT and Gemini and image generators such as DALL-E, Midjourney.

These systems are fundamentally reactive, needing an input or a prompt to generate an output. A new system, however, is beginning to gain traction – agentic AI.

By contrast, agentic AI is a proactive system. Agentic AI, like generative AI, begins with a prompt; however, this is used to pursue objectives through multiple actions. All with limited human involvement, it acts like a proactive assistant rather than a reactive tool.

The cycle of agentic AI follows as:

Perception is the starting point. The AI gathers information from its surroundings using sources such as sensors, application programming interfaces, internal databases or direct interaction with users. This ensures the system is working with current and relevant data before taking any action.

Reasoning follows once information has been collected. The AI analyses the data to understand meaning, context and intent. Using capabilities such as natural language processing, computer vision and pattern analysis, it interprets inputs, identifies relationships and determines what is happening within the wider environment.

Goal setting defines what the AI is trying to achieve. Based on user instructions or predefined objectives, the system establishes clear goals and outlines a plan to reach them. This planning stage may rely on decision logic, reinforcement learning or structured problem-solving methods.

Decision-making involves evaluating possible actions and selecting the most effective option. The AI compares outcomes based on criteria such as efficiency, accuracy, reliability and expected impact, using probabilistic models or machine learning techniques to guide its choice.

Execution is where decisions are put into action. The AI carries out tasks by interacting with external systems, triggering automated processes, updating records or responding directly to users as required.

Learning and adaptation occur after actions are completed. The AI assesses results, gathers feedback and adjusts its behaviour to improve future performance. Over time, this enables the system to handle similar tasks more effectively.

Orchestration ensures that multiple agents and systems work together smoothly. Orchestration frameworks manage workflows, co-ordinate resources, monitor progress and handle exceptions, allowing large numbers of agents to operate collaboratively at scale.

Watch an in-depth explainer here:

What impact will agentic AI have on airports?

Airports and their complex operations are the reasons why Agentic AI will transform the industry and boost efficiency. When a passenger travels through an airport, they are travelling through a highly interconnected system. There are many touch points they will come across: parking, checking in, baggage, security, retail, and boarding. These processes are all linked, though involve multiple independent stakeholders such as airlines, airports, ground handlers, regulators, and service providers, each controlling different parts of the passenger journey.

On top of this, airports generate vast volumes of real-time event data, from check-ins and security throughput to aircraft movements, weather updates, and transport flows, which change continuously and require rapid responses. Delays of even a few minutes can disrupt, a challenge historically worsened by siloed data and limited information sharing. Agentic AI, leveraging modern cloud and data platforms, provides a way to connect these dots, enabling faster, smarter, and more coordinated decision-making across the entire airport ecosystem.

Below are some areas where agentic AI could impact and benefit the airport:

Highly dynamic environments: Airports manage constantly changing variables including flight schedules, passenger flows, baggage handling, and ground transport. Small delays can cascade into larger operational disruptions.

Multiple stakeholders: Airlines, ground handlers, security authorities, retailers, and regulators all operate independently, making co-ordination complex. Agentic AI can act as a bridge, aligning decisions across these groups.

Real-time data everywhere: Sensors, check-ins, baggage scanners, aircraft movements, and weather feeds generate massive streams of information. AI agents can process this data instantly to make timely, informed decisions.

Personalised passenger experience: Agentic AI can anticipate passenger needs by integrating airline preferences, travel history, and real-time conditions. Passengers could receive proactive guidance on security queues, gate changes, transport connections, and even personalised offers in lounges or retail areas.

Frictionless travel through automation: AI agents can orchestrate identity verification, boarding, and baggage handling using biometrics, reducing the need for paper documents and manual intervention.

Proactive disruption management: When delays or disruptions occur, agentic AI can automatically rebook passengers, optimise staffing, redirect flows, and communicate updates, reducing chaos and improving recovery times.

Connected, intelligent operations: By linking disparate systems and stakeholders, agentic AI transforms airports from reactive, siloed environments into adaptive, co-ordinated ecosystems that respond intelligently to real-world events.

Early adopters

Agentic AI is set to transform airports by turning complex, fragmented operations into connected, intelligent ecosystems. Airports that adopt these technologies early will gain a significant advantage, improving efficiency, resilience, and overall passenger satisfaction while redefining the travel experience.

Adani Airport Holdings Limited (AAHL), a subsidiary of Adani Enterprises Limited and India’s largest operator of Public Private Partnership airports, is an early adopter, having already announced a strategic partnership with AIONOS, to implement a multilingual, omni-channel AI solution across its airport network.

The collaboration will see Agentic AI platform deliver personalised, real-time assistance to passengers via voice, chat, web and mobile interfaces. The system will operate in multiple languages, including English, Hindi and regional dialects, and will be available 24/7 to provide flight updates, gate information, baggage status, directions and other airport services.

Another early adopter includes VINCI Airports is trialling a virtual assistant powered by agentic artificial intelligence at Lyon Airport. Developed by startup Jumbo Mana, the 3D avatar provides real‑time information to passengers and responds to their questions. The system uses advanced AI and lifelike animation to create a realistic, human‑like interaction.

To explore these possibilities firsthand, join us at the International Airport Review Breakfast Briefing at Crowne Plaza, London Docklands on 18 March 2026. The event will showcase high-value use cases, demonstrate Agentic AI in action, and provide insights on how to implement these solutions effectively. Don’t miss this opportunity to network with industry peers, gain practical knowledge, and position your airport as a recognised innovator in the future of airport operations.

Register now