What is an Agentic Experience in AI?

An Agentic Experience is an AI interaction where the system not only retrieves information but also proactively reasons, plans, and executes tasks to achieve a user's goal. It shifts from simple conversational AI to a more autonomous, concierge-like service.

How does an Agentic Experience differ from Conversational AI?

Agentic Experience focuses on reasoning and execution, while Conversational AI is centered around retrieval and summarization. Agentic systems use long-term memory for personalized interactions, whereas Conversational AI often relies on session-based memory.

What are the benefits of using a hybrid interface in AI systems?

A hybrid interface combines text and visual elements, enhancing user experience by: - Speed: Faster interactions through clickable elements. - Clarity: Visual representation reduces cognitive load. - Fluidity: Users remain within the agent window without needing to navigate away.

How does long-term memory enhance AI interactions?

Long-term memory allows AI to remember user preferences and history, leading to hyper-personalized experiences. For example, it can automatically select preferred meal options or resume in-flight entertainment from where it was last stopped.

What is the role of radical proactivity in AI?

Radical proactivity involves the AI taking initiative without user prompts. For instance, if a flight delay risks a connection, the AI can proactively hold a seat on a later flight and notify the user, offering seamless service adjustments.

Jinen Dedhia

January 15, 2026

Designing agentic AI experiences for the modern traveler

AI in travel has largely focused on chatbots, recommendations, and information retrieval. As traveller expectations evolve, a new approach is emerging. Agentic AI in travel shifts the focus from answering questions to helping travellers take action across real-world systems.

There is a new mantra quietly taking over boardroom discussions at the world’s leading airlines: “Stop Chatting, Start Doing.”

For the last three years, the industry has been obsessed with Generative AI, building bots that can write polite apologies. But when a passenger’s flight is cancelled at 11:00 PM in a foreign airport, they don’t want an apology. They want a boarding pass for the next flight out, a hotel voucher, and a meal credit, already processed.

This is the shift from Conversational Experiences to Agentic Experiences.

If you are building a B2C airline agent in 2026, your goal is no longer to simulate a conversation. It is to simulate a capable, autonomous concierge who has the keys to your backend systems.

What is an “agentic experience”?

An Agentic Experience is an interaction where the AI doesn’t just retrieve information (“Read-Only”) but proactively reasons, plans, and executes tasks (“Read-Write”) to achieve a user’s goal.

Feature	The Old Way (Conversational AI)	The New Mantra (Agentic Experience)
Core Function	Retrieval & Summarization	Reasoning & Execution
User Input	“What is the policy for…”	“Fix this for me.”
Memory	Session-based (forgets you immediately)	Long-term context (knows your life)

What agentic AI means for travel experiences

In the context of travel, this means AI agents that can:

Understand traveller intent and preferences
Maintain memory across trips and interactions
Access real‑time signals like availability, delays, or pricing
Take actions such as rebooking, upgrading, or confirming changes

For the traveller experience, this represents a fundamental change. Instead of interacting with fragmented tools and interfaces, travellers can rely on a single agent that coordinates across systems on their behalf.

Why travel companies are adopting agentic AI in 2026

1. The UX revolution: The hybrid interface (Agent + UI)

Text is not always the best interface.

One of the biggest mistakes airlines make is trying to force everything into a text bubble. Reading a list of 15 available flights or visualising a seat map via text description is terrible UX.

The new norm is Generative UI, a hybrid approach where the Agent is the Controller and the UI is the View.

The “show, don’t tell” rule

When a user asks to change their seat, the Agent shouldn’t say, “Rows 12 through 15 are open.” Instead, the Agent should instantly render an interactive Seat Map Widget directly within the chat stream. The user clicks “12A” on the visual map, and the Agent handles the backend processing.

Why this enhances UX:

Speed: Clicking a card is faster than typing “I choose the second option.”
Clarity: Reduces cognitive load. Complex data (flight comparisons) is presented visually; complex intent (negotiating a refund) is handled via text.
Fluidity: The user never leaves the Agent window to go to a separate web page. The app comes to them.

This approach, sometimes called generative UI for travel apps, represents a fundamental rethinking of how AI-powered travel platforms deliver information and enable action.

2. The brain: long-term memory & hyper-personalisation

Most travel chatbots today suffer from amnesia, treating loyal customers like strangers. Agentic AI changes this through persistent memory systems that connect to vector databases containing user history, preferences, and behavioural patterns, unlocking personalisation that builds genuine loyalty.

The “Veg meal” & “movie” Factor

It’s the small things that build loyalty.

The Vegetarian Example

Without Memory: The user books a flight. Later, they navigate four menus to select “Asian Vegetarian Meal.”
With Agentic Memory: The Agent sees the user has ordered “Asian Vegetarian” on their last five flights. When the user says, “Book the flight to London,” the Agent responds:
“I’ve booked you on BA123. I also auto-selected the Asian Vegetarian meal for you and put you in a window seat like you usually prefer. Do you want to change any of that?”

The IFE (In-Flight Entertainment) Bridge

Imagine if your Agent connected to the in-flight entertainment system.

Scenario: The user stopped watching Dune: Part Two halfway through on their last flight.

The Agentic Move: Upon booking the next trip, the Agent notes this. When the passenger boards and pairs their app, the screen greets them:

“Welcome back, Sarah. Ready to finish Dune? We saved your spot.”

This turns a transactional booking engine into a Relationship Engine.

3. Radical proactivity (The “Silent” Agent)

The best agentic experience is often the one the customer didn’t initiate.

Scenario: A flight from JFK to LHR is delayed, risking a connection to Mumbai.

The Agentic Move: The Agent detects the risk via webhook, checks availability, holds a seat on a later flight, and then messages:

“Heads up—your connection is at risk. I’ve tentatively held a seat for you on the 8:00 PM flight to Mumbai just in case. Want me to confirm this switch now? No charge.”

This is proactive AI in action, the hallmark of true agentic experiences where the system monitors, reasons, and acts on behalf of the traveller without waiting for input.

Building agentic AI for travel: Key components

The Technical Architecture

To build this, you need a Compound AI System:

The Brain (LLM): Orchestrates reasoning and decisions.
The Toolbelt (APIs): Secure hooks into your PSS (Amadeus/Sabre) to book_flight, get_seat_map, or issue_voucher.
The Memory (Vector Store): Stores preferences like “Veg Meal” or “Last Movie Watched.”
The UI Generator: A frontend framework (such as server-driven UI) that allows the Agent to render widgets, maps, cards, selectors, on the fly.

Key takeaways: Implementing agentic AI in travel

Agentic AI goes beyond chatbots: It executes tasks, not just retrieves information
Hybrid interfaces win: Combine conversational AI with visual, generative UI components
Memory drives loyalty: Long-term context transforms transactions into relationships
Proactivity is the differentiator: AI agents that anticipate needs outperform reactive systems
Architecture matters: Successful systems combine LLM reasoning, secure APIs, vector memory, and dynamic UI.
For travel brands: The shift to agentic experiences isn’t optional—it’s where customer expectations are heading in 2026.

Conclusion

The era of the chatty, apologetic bot is over.

The future belongs to the Agentic Experience, an interface that combines the intelligence of an LLM, the visual utility of a dynamic UI, and the deep context of long-term memory.

Don’t just build a bot that talks. Build an agent that knows your customer and works for them.

Want to explore what agentic AI can unlock for your travellers? DronaHQ’s agentic platform help you go from idea to ready AI agent in a few simple steps. Learn more here.