Your customers want answers now, not in an hour and not tomorrow. They also want personalized help on the channels they're already using, day or night
Human-only teams find it nearly impossible to keep up with these customer expectations. If you want to scale your brand, AI customer service agents are your best bet.
But depending on how they’re set up, AI agents can either improve or worsen customer service.
When it’s implemented well, AI can clear the routine volume that can bog down your team while freeing them up for complex queries.
When it’s implemented poorly, AI can frustrate customers with inaccurate information and loops that lead to nowhere.
9 benefits of AI for customer support
Set up with care, AI can improve response times, resolution rates, and customer satisfaction. When brands are thoughtful and deliberate in how they implement their AI customer agents, they can see some of the benefits below.
1. Instant response times
Even your fastest human agents can’t respond instantly. They need to read the message, work out the best answer, and communicate it back to the customer. AI answers routine questions the moment they come in, with minimal lag and no queue.
Password resets, order tracking, simple returns and exchanges: each one may be easy to address, but together they make up a lot of volume for your team. AI can help clear this volume so your team can do more complex work.
AI can also nudge someone toward a purchase. Let’s say someone at check-out has a quick sizing question. They've already decided to buy, but there’s one small barrier standing in the way. A 4-minute wait gives them time to talk themselves out of it, but an instant answer might tip them toward completing the purchase.
2. 24/7 availability
Once you sell beyond your own time zone, there's no such thing as after hours.
24/7 coverage with people means a night shift or an outsourced team in another region, which can be expensive. An AI agent is available for all of those hours at once, in every market you serve.
Naked Wardrobe, for example, trained an AI agent on their website and documentation. Now, when someone lands on their website at 2:00 a.m., they can get information about order status and returns, as well as pre-purchase product recommendation requests.
Over 90 days, their AI agent resolved 86% of all customer queries autonomously and 94% of product recommendation queries.
3. Faster training
Every time you change a price, a policy, or a return window, a human team has to learn it. That means retraining sessions, updated scripts, and a learning curve. The bigger the team, the longer the lag. An AI agent learns from your documentation, so updating the source updates the agent.
4. Seasonal fluctuation cost efficiency
B2C support teams often need to scale up or down depending on the season. Anyone who's worked a Black Friday Cyber Monday (BFCM) has felt the fluctuation: staff up in October, train everyone before the rush, then ramp back down for the slower months.
AI agents can absorb the surge in routine tickets, so your team doesn’t feel as much seasonal instability. This way, growing brands can handle more volume without the support budget deciding how fast they're allowed to grow.
5. Personalized interactions based on customer data
When AI agents are trained on customer data, they can reply with full knowledge about your customer’s order, preferences, and previous interactions with your brand.
According to Klaviyo’s 2025 Future of Consumer Marketing Report, 74% of customers expect personalized experiences from brands. AI agents that are pulling from the data housed in a unified customer profile can meet this expectation by responding as if they already know your customer. .
6. Human agent productivity gains
A good agent who spends all day resetting passwords may not stay for long. When they quit, years of product and customer knowledge walk out with them.
When AI is handling most of the high-volume, routine requests, your human agents can spend more time on the complex, high-value problems that need a human brain. This is how AI agents can actually make human agents more productive where your brand needs it most.
At Folk Clothing, an AI customer agent answers simple questions before they ever need to reach a human agent. "It's deflecting loads from my inbox, and everything I've seen has been positive. It's already made a noticeable difference to my workload," says Hayley Scott, ecommerce coordinator at Folk Clothing.
7. Multilingual support
Serving customers in their own language used to mean hiring native speakers for each new regional market . As a result, promising regions may have been skipped over because the support headcount was too costly.
AI agents can operate in hundreds of languages, whether it’s German at noon or Portuguese at midnight. A market that may have been costly to serve suddenly becomes accessible, even for a small- to mid-sized brand.
8. Proactive support
Most support waits for the customer to start the conversation. The problem is that a lot of customers never do. A shopper with a sizing question may pause at check-out and click away, and you never hear from them.
An AI agent can reach out at the moment of friction instead of waiting. When someone is about to abandon their cart, an AI agent can follow up with an offer to answer any lingering questions about sizing or materials. From there, it answers the question and guides the shopper back to check out before the sale slips away.
9. Data and insights gathering at scale
Every support conversation tells you something about your customers and your product. AI conversation logs can be analyzed at scale, so your brand can act on customer support patterns: the question 200 people asked this week, the product page that keeps generating tickets, the policy nobody understands. The same logs that resolve the ticket can also tell you what to fix so the same tickets stop coming in.
Understanding the risks of AI customer service
Poorly implemented AI comes with some risks to the customer experience. The good news is that you can mitigate these risks by anticipating and working around them before a customer ever runs into an issue.
Lack of empathy
When someone reaches out in a genuinely bad moment, such as a wrong order that can ruin a wedding or a charge that just overdrew their account, a technically correct AI reply can land much too cold.
Watch for the signals that a conversation has turned emotional, and route those straight to a person who can read the room.
Hallucinations
AI will state something false with total confidence. Without grounding your agent in your real brand policies and documentation, an AI agent will happily invent a return window, make up a product spec, or promise a refund you don't offer.
You can keep it from guessing by limiting its answers with guardrails. That means training the agent on your own sources, such as your product catalog, FAQs, brand guidelines, and help docs, and setting clear rules for what it can say.
When a question falls outside what it's been given, the agent should hand off to a human rather than improvise an answer.
Reasoning loops
It's common to be on the receiving end of a chat with an AI agent that asks for your order number, then asks again, then routes you to a menu that loops back to the start, and 10 minutes later you've solved nothing.
When a conversation becomes complex or starts going in circles, the agent should route the customer to a person with full context, so they're not asked to start over from scratch.
Deskilling of human agents
Lean too much on AI and your team's most valuable skills may start to rust. There are skills that only stay sharp with practice: calming an angry customer, working through an outlier inquiry, and knowing when to make exceptions because it's the right call.
The best course of action is to keep your human agents working on complex, high-value conversations. Let AI carry the routine load, such as where is my order (WISMO) tickets, simple returns and exchanges, and quick product suggestions.
Training and testing time
AI isn't exactly tough to set up, but it does require training and testing. AI agents that are actually ready to serve customers need a few things before launch: clean data, clear brand guidelines, defined escalation paths, and ongoing testing in simulated environments.
Privacy and trust concerns
According to Klaviyo’s 2026 AI consumer trends research, only 13% of people completely trust AI. Plenty of people don't want to hand over their personal information to an AI agent. Many feel the speed at which AI can handle inquiries isn’t worth the potential risk of a data breach.
That hesitation is friction, and no amount of clever routing makes it go away. You design for it by giving those customers an easy door to a person. Review those conversations, fix what's driving customers to a human, and the agent can improve over time.
Forced attempts to sound human
According to Klaviyo’s 2026 AI consumer trends research, nearly 1 in 5 consumers say they see low-quality or generic AI content from brands weekly. For some, it leaves a meaningful impression: 32% say it makes them trust brands less.
AI that tries too hard to sound human usually lands worse than AI that doesn't try at all. Forced enthusiasm and a chummy tone that doesn't fit the moment can make people uneasy. A clear, plainly automated answer is the safer call.
How to get the benefits of AI customer service
The brands that win with AI customer service don't flip a switch and walk away. They launch an AI strategy and build their guardrails as deliberately as they build everything else.
- Start with specific use cases. Test your AI agent with clearly defined, low-risk tasks where the path to an answer is obvious: order status, store hours, and return policy, for example.
- Build in human escalation from day one. The moment AI can’t deliver a good answer, your customer should be able to talk to a human. Design that handoff before you launch.
- Set clear brand guardrails. Spell out what the AI agent can and can't say, and constrain it to facts you've verified rather than letting it improvise
- Keep fine tuning your AI agent after launch. AI gets better with feedback, but only if someone reads the conversations, finds out where it's failing, and fixes the pattern. This is an ongoing process, not a one and done.
- Be transparent about your AI agent. Tell customers when they're talking to an AI agent, and build in easy ways for your customers to access a human agent.
K:AI Customer Agent delivers personalized, on-brand support in your customers’ preferred languages across email, text, chat, and WhatsApp. Use Customer Agent to resolve routine questions, make personalized product recommendations, and free up your human agents for more complex, high-value conversations.
See how Customer Agent can improve your customer experience. Get started with Klaviyo Service.
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