Agentic Customer Service: How to Adopt Full-Journey AI Support in 2025

Customer support has started to shift. The old model of reactive replies and fragmented tools is giving way to something more fluid, something more intelligent. Instead of treating each inquiry like a standalone event, agentic AI steps in to manage conversations with context and purpose.

Agentic customer service is built around outcomes. An AI agent understands what the customer is trying to achieve and takes the necessary steps to get them there. It can navigate questions, solve problems, follow up when it makes sense, and stay aligned with your business goals along the way.

It’s a shift more businesses are starting to make. In fact, 63% of support teams are already applying AI to improve how they work, and adoption continues to accelerate. 

This guide is here to walk you through what agentic customer service actually means. You’ll get a clear view of how it works and how to implement it inside Tidio, plus a calculator to help you project real results.

What is agentic customer service?

Agentic customer service is built around AI agents that know what the customer is trying to achieve and work toward that outcome. Instead of waiting for a person to step in, the agent stays active throughout the conversation. It might issue a refund, check inventory, update a shipping address, or follow up when someone leaves a cart behind.

The AI agent doesn’t rely on a script or a predefined path. It decides what to do based on context. If someone has reached out before, the AI agent can use past interactions to move things forward more smoothly. If the request is new, it finds the best way to respond using available data and support content.

Tidio’s Lyro is a good example of an AI agent designed to resolve customer issues from start to finish. It connects with your store to handle tasks like checking order status or processing a refund, and it uses your knowledge base to give accurate, on-brand answers in real time.

These agents operate with autonomy, taking action on their own when appropriate. Along the way, they learn from each exchange and gradually improve how they handle similar cases.

Agentic support gives teams more flexibility to handle volume and stay available around the clock, even when the queue is full or the team is offline.

Why choose agentic AI over traditional chatbots?

Most traditional chatbots stick to scripts. They follow rules and rely on predefined chat triggers, handing off the conversation to a human the moment something unexpected happens. Agentic AI is built to do the work itself. It understands the goal behind a request and adapts to get there with less friction.

Here are some of its benefits:

• It resolves common requests but knows when to escalate: agentic AI is designed to handle inquiries like refund eligibility and product questions on its own. If the situation requires a human, it transfers the conversation without losing context, avoiding the kind of cold handoff that can frustrate customers. 
• It remembers what’s already been said: agentic AI uses previous interactions to inform new ones, so customers don’t have to repeat themselves. In fact, 70% of people expect support to already know their history when they reach out again.
• It follows up at the right moment: idle carts, long response gaps, or checkout hesitation can all trigger helpful outreach. Companies with proactive customer service see a 20-30% increase in client satisfaction. Couple that with the fact that 82% of users expect immediate problem resolution, and it becomes obvious why agentic AI is superior.
• It adapts with experience: static flows need regular updates, but agentic systems improve as they go. The more interactions they handle, the better they become at recognizing intent and responding with precision.

What agentic customer service can do: capabilities that matter

Support works better when the AI behind it has direction. Instead of responding one message at a time, the agent focuses on where the conversation is going and takes steps to get there. It handles common requests and moves things forward, creating a sense of momentum for the customer.

The way this happens depends on a few core capabilities:

Autonomy: AI that handles tasks from start to finish

Autonomy means the agent takes initiative. It understands the purpose behind a message and acts on it without needing a detailed script. There’s no waiting for someone to direct the next step. The agent can recognize the intent behind the request and respond with the right solution.

Lyro puts this into action by resolving questions like refund status or return eligibility in seconds. It pulls from your policy details and uses your help content to give customers a clear, accurate response. Tasks that used to sit in a queue get handled immediately, which helps reduce response times across the board.

Memory: personalized support based on past interactions

When an agent remembers what’s already happened, the experience becomes smoother. Customers don’t have to repeat themselves or start fresh every time. The AI can use previous conversations, order history, or preferences to guide the reply.

Lyro applies this in follow-ups and status checks. If someone recently made a purchase, it can confirm the delivery or recommend something that fits their browsing behavior. This keeps conversations connected without relying on manual notes or agent memory.

Read more: Learn how to build a product recommendation chatbot for your needs.

Proactivity: support that reaches out first

Proactive support means acting on signals before the customer makes a request. When someone lingers on a page, returns to an abandoned cart, or seems unsure at checkout, these moments often benefit from a timely nudge.

Inside Tidio, these touchpoints can be handled through chatbot automation flows that trigger messages based on behavior. Then, Lyro can join the conversation when the customer replies, picking up the thread and providing answers in real time. This setup helps guide visitors toward their next step without adding pressure on your team.

Read more: Explore proactive live chat examples, tools, and tips.

Your 8-step path to agentic customer service 

Using agentic support doesn’t require a massive rebuild. Most teams begin by plugging in what they already have, then go from there. The key is knowing what to set up first, what to hand over to AI, and when to bring your team back in.

Here’s a step-by-step guide to get started with Tidio’s agentic customer service tool:

1. Audit your current setup

Start by looking at the types of questions your team handles most often. Go through your recent tickets, live chat transcripts, and order-related messages. Patterns show up quickly. These can be anything from questions about shipping status and returns to product availability, and an AI agent like Lyro can manage them on its own.

Once you know what’s coming in most often, it’s easier to decide what to automate first. Lyro works best when it’s focused on repetitive, high-volume topics where your team shouldn’t have to step in. Gathering this data upfront also helps you spot quick wins—places where an AI agent could jump in today and start saving your team time.

2. Centralize your knowledge base

Before you can hand anything over to AI, make sure to gather your FAQs, shipping policies, return instructions, and product details in one place. Turning them into a single, reliable source of truth your agent can pull from is what does the trick.

Tidio makes this part simple. You can add content directly through the built-in knowledge panel or paste in links from your help center. Once everything’s there, Lyro will know exactly where to look when a customer asks for something, and your replies stay accurate without needing constant tweaks.

Read more: Learn what it takes to create a solid knowledge base chatbot. Also, be sure to explore Lyro’s knowledge base while you’re at it.

3. Connect your live chat and store

To make the most of an AI agent, it needs access to real customer data. Connecting your Shopify store or any ecommerce platform you use lets the system pull in things like order details and purchase history automatically.

Tidio handles this with a quick, no-code integration. Once connected, Lyro can answer questions like “Where’s my package?” or “Can I still cancel my order?” using real-time information, without asking your team to dig through order records.

To connect Tidio to your Shopify store, head to the Shopify App Store and install the Tidio Live Chat & AI Chatbots app. Once it’s added, you’ll be guided to your Tidio panel, where you can set up the chat experience and activate the widget. Tidio is free to test-drive, so the entire process will be perfect for testing how the tool fits your store’s needs.

If you’re using a custom theme, just make sure to turn on the Tidio embed under your theme’s App embeds section so the chat shows up for visitors.

Read more: Here’s all you should know about AI agents for Shopify.

4. Launch goal-based AI agents

Once your setup is in place, it’s time to let your AI agent start handling real conversations. Start small. Pick a single task that shows up often, like checking order status or confirming product availability. These types of requests tend to follow a clear pattern, which makes them a good fit for automation.

Inside Tidio, Lyro can be trained on your support content to manage these tasks directly in the chat. You don’t need to build a custom flow for it. Just connect your knowledge base, and Lyro will use that information to guide its responses. From there, you can track how well it performs and gradually expand its scope based on real results.

If you want to go further, you can create custom flows using Lyro Simple Actions. These are specific tasks that let you build responses to particular phrases or questions and add extra logic, like checking inventory or pulling in discount info.

You can use templates or build your own flow in Tidio’s visual editor. Once active, the task becomes part of Lyro’s conversation, triggered automatically without breaking the flow.

5. Set escalation and learning rules

Not every conversation needs to stay with the AI. Some cases are sensitive, unusual, or too complex for automated handling. 

With Lyro, you can set escalation rules that transfer chats to a human agent when certain phrases or topics come up, like cancellation or refund requests. This helps keep conversations on track and ensures customers get the right level of support when it matters most.

6. Track results and retrain weekly

Once your AI agent is running, it’s helpful to check in regularly and see how it’s performing. You can start by reviewing key metrics, like first-contact resolution handle time, or any changes in conversion. These give you a clear picture of what’s working well and where customers are still getting stuck.

Inside Tidio, you’ll find a dedicated Unanswered Questions section that shows which queries Lyro couldn’t confidently respond to. You can turn these into new Q&As directly from the dashboard. This makes it easy to close gaps and keep your AI knowledge base growing. Updating things weekly helps keep your AI aligned with real conversations and customer needs.

7. Expand to omnichannel

Once things are running smoothly on live chat, you can start bringing agentic support to other channels your customers already use. Instagram, WhatsApp, and Messenger are easy to connect in Tidio, so your AI agent and automation flows can stay active wherever conversations are happening. Everything routes through one place, which keeps your support consistent and easier to manage.

This kind of setup matters more than ever. As many as 70% of consumers are willing to spend more with companies that offer seamless conversational experiences across channels. Expanding your support this way helps meet those expectations while giving your team a complete view of the customer journey.

Read more: Explore the topic of omnichannel customer service in more detail.

8. Measure your impact with the ROI calculator

Once your support automation is in place, it’s helpful to get a clear picture of the results. Tidio’s ROI calculator gives you a quick, visual summary based on your support volume, handle time, and other key data. 

In just a minute, you can estimate how much time your team could save, how support costs might shift, and where automation is adding value. It’s a simple way to check progress and share impact with your team or leadership.

What’s next for agentic customer service

Agentic AI is still evolving, and the direction in which it’s heading is already clear. AI tools are getting better at recognizing intent and adapting to user behavior. We’re starting to see product suggestions based on browsing history, follow-ups tailored to customer habits, and offers that land at exactly the right time. This kind of personalization is already possible through flows and integrations that protect customer privacy, using server-side data without overstepping.

There’s also more focus on how AI handles information behind the scenes. Teams want to know what data is being used, how decisions are made, and whether everything lines up with privacy rules. Customers want that clarity too. Being open about how the system works is becoming part of the experience.

As these systems grow, support starts to look a lot more like a growth channel. Instead of just focusing on answers, conversations move into loyalty invites, personalized discounts, and higher conversion rates. Support tools begin to drive revenue in ways that used to belong to sales or marketing.

Tidio is already helping teams move in that direction. Lyro handles the back-and-forth, Copilot supports agents during live chats, and automation flows connect the dots between systems. Whether you’re automating common questions or building something more advanced, Tidio’s agentic AI gives you the tools to grow without rebuilding everything around it.

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