According to the Klaviyo Future of Consumer Marketing Report, nearly half of consumers (43%) expect a response within 24 hours after reaching out about a negative experience.
To meet these expectations, it’s becoming increasingly clear that human and AI agents need to work together to serve the customer. They need to be drawing from the same customer record, centralized to one place, so that they’re answering as quickly as possible while personalizing their service interactions.
But working with AI requires training. As AI agents become standard in customer service, it’s important your human agents know how to rely on them, when to take the reins, and how to contribute to their improvement.
AI customer service training: overview
AI customer service training teaches human agents how to get the most out of AI customer agents.
First, it’s important to reassure agents that you don’t want to replace them with AI. Klaviyo’s 2026 State of Customer Service Report supports this, too: 44% of companies say implementing Al or automation hasn't led to any significant change in their team’s size or structure. Some teams have seen slight reductions (12%), while others have actually added new employees (25%) as Al has supported growth.
Rather, your goal is to free up more time for your human agents to resolve complex tickets that require judgment and empathy. When AI agents handle repetitive, routine questions, human agents have more time to serve high-value customers, too.
Human agents should also be trained to recognize the limitations of AI. Your AI service platform should be set up to automatically escalate issues, but human agents should also be set up to understand how best to continue those conversations.
What changes when AI handles the routine
According to a Gartner survey of 321 service leaders, 85% said they're adding new responsibilities to frontline agent roles as AI takes over routine work, and 75% are moving agents into new roles. Where headcount is shrinking, most of it is happening through attrition, with that capacity reassigned to higher-value work.
Agents are also moving from processing tickets to managing the AI that processes them. The agent who's best at spotting edge cases trains the AI on those edge cases. The agent who's best at deescalation handles the conversations the AI flags as high-risk.
Rather than answering the same question 50 times a day, human agents are spending their time teaching AI to answer it better.
Essential skills for AI customer service
- Picking up an escalated conversation. AI agents should escalate difficult support tickets on their own. Train human agents to pick up where the AI agent left off without making the customer repeat anything.
- Reviewing AI conversation history. Train agents to periodically review the AI's past interactions and look for patterns, like a question it keeps getting wrong or a policy it keeps misquoting.
- Closing the feedback loop. A good flag doesn't necessarily help anyone fix mistakes. Train agents to report AI misses in a useful way: what the agent got wrong, what the correct answer is, and where it pulled the bad information.
How unified customer data changes training
When agents can see a customer’s full profile, they can better personalize interactions and improve customer satisfaction.
In Klaviyo, a unified profile means agents are working from the same real-time customer view. Training programs built around that shared view should focus on interpretation and action rather than data retrieval.
Take a customer asking for a discount. The AI agent sees the open cart and the loyalty tier and applies the right code on its own. Whether that code can stack with the customer's loyalty points is a judgment call, though, and that's where the human steps in, reading the same profile the AI just used and deciding what's fair.
When the profile hands every agent the same facts, onboarding stops being about how to look a customer up or piece their history together. You train people to read what the profile is telling them, to recognize when a situation calls for judgment the AI shouldn't make alone, and to make that call consistently across the team. The shared view handles retrieval, so your program can focus on interpretation and decisions.
Building your AI customer service training program
- Audit a sample of your support conversations. Look at what your human agents spend the most time on, and which of those tasks are routine enough for AI to handle well. Order status inquiries, return policy questions, and shipping updates follow predictable patterns and have clear answers. Complex complaints, multi-issue tickets, and emotionally charged conversations need a human.
- Determine your escalation criteria. Define clear triggers for when AI should escalate to a human, like frustration or profanity in the customer's language, a mention of a competitor, or a report of a damaged item. These rules set the boundaries for autonomous service.
- Run simulations before launch. Build new skills for your AI agent, then test them across different scenarios to make sure they work as intended before pushing anything live.
- Measure AI and human performance separately. Track the same customer service metrics for each, like first contact resolution, time to resolution, and CSAT, so you can see what the AI handles well and where a human still resolves faster or keeps the customer happier.
- Build a feedback loop into your operations. Set a regular cadence to review flagged conversations and look for where the AI consistently underperforms. Correct mistakes, add to your knowledge base, and run additional simulations to make sure mistakes are corrected.
With these steps, both human and AI agents can benefit. The AI agent improves because human agents have a hand in giving it feedback, and human agents improve because AI agents are handling routine requests that don’t contribute to building more complex skills.
Training your customer service agents to work with Klaviyo
Training only pays off if your AI customer agent is worth working with.
K:AI Customer Agent runs on the same customer data as Klaviyo Service, so it can personalize the customer experience alongside your human agents. That's what gives your trained team an agent that handles real work instead of one they're constantly cleaning up after.
- Clear the questions that flood your queue. Pre-built WISMO skills connect to your order and profile data, so the agent resolves those requests automatically and takes the load off your team.
- Turn a product question into a sale. When a returning customer asks about a product, the agent uses their browsing behavior and purchase history to recommend the right items in real time, driving cross-sell inside a service conversation.
- Follow the customer across channels. The AI agent works over email, text messaging, web chat, and WhatsApp. A shopper can ask about an order in web chat, and the agent resolves it, captures the product they were interested in, updates their profile, and triggers a personalized email follow-up later.
- Hand off to humans on shared data. When a conversation needs a person, it moves into Klaviyo Helpdesk, where your human team works from the same customer profile the agent used. AI and human agents share one view of the customer, so nobody starts over.
That shared data is what makes the training pay off: your team spends their time on the work only people can do, and the AI handles the rest in your brand's voice.
Sign up to put K:AI Customer Agent to work for your team.
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