The problem with autoresponding to only general FAQs.

Guests often ask the same questions like Wi-Fi, parking, directions, amenities, and staff spend extra time repeating themselves. Most AI tools only provide canned replies to questions like “What’s the Wi-Fi?” or “Do you have early check-in?” These systems rely on basic classification, so if a guest asks “What is the Wi-Fi?” or “My Wi-Fi isn’t working,” they’ll get the same answer, even though those are two very different needs.

What is Agentic AI?

With Agentic AI, it goes further. It understands context, remembers past interactions, and can even take action, from troubleshooting issues to suggesting alternatives, instead of just firing off a static response.

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References are AI’s knowledge bank

References are the AI’s knowledge bank. They let the Agent handle repetitive FAQs but also support smarter actions like suggesting room upsells, assisting with access issues, or following up on maintenance issues, making responses unique to each guest. 

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Example of References 

Not only can Akia’s AI Agents handle the basics like Early Check-In, Pet Policies, Arrival Instructions, or Local Recommendations, but they can also expand into a wide range of use cases unique to your property.

• Dynamic Policies: Cancellation rules that differ by booking source (OTA vs direct).
  
  
• Operational Requests: Responses to maintenance issues (e.g., AC broken, towels needed, late-night noise).
  
  
• Upsells & Availability: Suggesting another room type when early check-in isn’t available.
  
  
• Amenities in Context: Directions to the pool and towel pickup location, not just “yes, we have a pool.”
  
  
• Check-Out Guidance: Tailored instructions based on room type or guest profile (e.g., key drop vs smart lock code expiration).
  
  

What happens when the AI Agent cannot answer a guest?

When the Agent doesn’t know the answer, a staff member will step in. But instead of the conversation ending there, Akia turns that staff reply into training fuel so the Agent can handle it next time.

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Clone your best employee with AI Agents. 

This is where Self-Learning makes things simple. Many properties assume training an AI is a massive project, but it’s actually easier than onboarding a new hire. It’s basically like cloning your best employee. The Agent shadows your team (feeding it prompts on how to respond to guests appropriately), learns from real conversations (picking up on preferred or approved messages), and will gradually take more off your plate.

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Automatically create References based on staff replies.

With Self-Learning, Akia’s AI Agents automatically build their own knowledge base. Anytime your staff answers a guest question that the AI couldn’t, the system creates a suggested reference. Staff can then approve, edit, or dismiss it, teaching the AI to respond better in the future.

The results so far:

• 75% of all guest requests are now resolved by AI, up more than 15% from last month.
  
  
• Even as guest message volume rose more than 30% month-over-month, accuracy improved with approval rates increased by 5%.

How AI Self-Learning works.

1. A guest asks something the AI doesn’t know (e.g., “The AC is broken.”)
   
   

2. Staff replies as usual (e.g., “Thanks for letting us know. Please try rebooting the AC by turning the thermostat off for 60 seconds and then back on. If it’s still not working, we’ll send a maintenance team member right away.”), and Akia auto-creates a suggested reference, shown in the References page (and a suggested response in the message).

3. You approve/edit/dismiss the suggestion in the reference page. Once approved, it’s saved to the Agent’s reference library so the next time, the AI knows how to respond immediately.

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And it keeps getting sharper: staff edits have dropped by 4%, rejections are down 1%, and each Agent picks up about five new approved responses every week — expanding coverage without any extra work.

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How Self-Training AI improves guest messaging over time

With Self-Learning, properties don’t need to worry about technical setup or long training cycles. The Agent simply learns from staff replies, turning everyday conversations into future answers. Over time, that means fewer repetitive questions for staff, quicker responses for guests, and an AI that continues to improve on its own.

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