How AI Customer Service Transforms Service Interactions - Klaviyo
2026-03-10 21:09 Diff
https://www.klaviyo.com/blog/ai-customer-service-adoption

In 2026, shoppers are relying on AI to find what they need. And AI is presenting them with a search shortcut: rather than sifting through information, shoppers are getting instant answers that can help speed up their decision making.

Klaviyo’s 2025 AI Shopping Index found that 68% of consumers use AI for instant answers, and 56% use it for personalized recommendations—and the use cases for AI in customer service continue to grow.

To learn more about the current state of AI in customer service, we surveyed 500+ customer service leaders. Here are a few of the key findings from Klaviyo’s 2026 customer service research:

  1. Nearly one-third of respondents have partially implemented AI across parts of the customer service journey, and one-fifth have fully implemented AI.
  2. AI has a high success rate for resolving customer service inquiries, with over 60% of respondents stating it’s very successful for some inquiry types.
  3. 63% of customer service leaders believe AI and automation have improved the quality and efficiency of customer service interactions.
  4. 47% of customer service leaders say customer discomfort or trust concerns about AI-driven interactions are the biggest challenges to adopting or scaling AI.

Keep reading to find out how B2C brands are currently using AI to improve customer experience and efficiency.

Where is AI succeeding and falling short in the customer support process?

Customers have always expected quick answers. But thanks to AI, “quick” means “right now.”

In fact, according to Klaviyo’s 2025 Future of Consumer Marketing Report, 38% of consumers expect a response within 4 hours of reaching out to a brand about a negative experience.

AI succeeds at helping brands meet some of these consumer expectations. According to our customer service research, AI is great for responding to FAQs, tracking order statuses, helping with account management, and collecting customer feedback.

There are gaps, of course. AI can struggle with interactions that require judgment calls, like delivering refunds and returns, making policy exceptions, and communicating with empathy.

Here’s how customer service leaders responded when we asked, “How successful has your company been in resolving each of the following types of customer service inquiries with AI or automation?”

Type of inquiry

Very successful

Neutral

Not successful

N/A or not automated

General FAQs (e.g., policies, hours)

62%

24%

2%

11%

Customer feedback or satisfaction surveys

60%

27%

2%

10%

Product or service information

59%

27%

3%

11%

Order status or delivery tracking

57%

28%

2%

13%

Billing, payment, or invoice inquiries

57%

28%

3%

12%

Account or profile management

56%

27%

4%

13%

Returns, refunds, exchanges, cancellations

51%

28%

4%

16%

Loyalty or rewards program inquiries

49%

29%

2%

20%

Booking, reservation, or check-in/check-out (hospitality only)

44%

26%

2%

27%

How do you set up an AI-powered customer service tech stack?

When we asked where their teams have adopted AI across the customer service journey, here’s how customer service leaders responded:

  • 61% have fully or partially implemented AI for customer inquiries and chat support.
  • 57% have fully or partially implemented AI for agent assistance and response suggestions.
  • 53% have fully or partially implemented AI for customer ticket summarization.
  • 53% have fully or partially implemented AI for predictive analytics or proactive outreach.

With that in mind, here are some AI customer service tech essentials to get you started for 2026:

AI-powered CRM: data collection, consolidation, and storage

You’ve heard it before: AI is only as good as the data it’s trained on. If your customer and product data is messy, incomplete, or siloed across several software platforms, your AI customer agents won’t be able to deliver the best results.

An AI-powered CRM collects, consolidates, and analyzes customer data from website behavior, purchase history, email marketing, text message marketing, social media, customer service interactions, and more. It combines these data and analytics capabilities with marketing and customer service so that brands can personalize interactions across the customer journey.

When your customer data is centralized in a single source of truth like this, it makes all kinds of AI customer service use cases possible (more on these next).

AI customer agent: instant, personalized customer service, 24/7/365

An AI customer agent automatically ingests your brand’s storefront, support pages, and customer data so it can guide shoppers with tailored recommendations, fast answers, and quick resolutions across channels. When your AI customer agent is embedded within your CRM, it means your agent is keeping up with how customers are interacting with your brand in real time.

Your AI agent can tackle your most common customer service questions, like those about order tracking, shipping timelines, return windows, whether something is in stock. These inquiries are perfect for AI because the answers are usually straightforward, and they probably make up a large chunk of your service team’s ticket volume.

It’s a win-win: customers get instant answers, and your team gains bandwidth for high-touch moments. Natural wax melt brand Happy Wax, for example, uses an AI customer agent to reduce support tickets. Within 90 days, over 50% of conversations handled by the agent were fully resolved without any service team involvement.

Similarly, tea brand Harney & Sons was struggling with a fragmented service and retention tech stack that created challenges for both customers and their in-house team. By consolidating their customer service tools into a CRM with embedded AI, they streamlined their operations and improved the customer experience.

The brand’s AI customer agent now works 24/7 to autonomously answer support and recommendation queries. In a 60-day period, 77% of product recommendation queries were resolved by their customer agent.

Self-service customer hub: everything they need in one place

A self-service customer hub gives your customers an on-site destination where they can save favorite items, track orders, initiate returns, manage loyalty points, and get personalized product recommendations based on their actual behavior.

An AI customer agent can operate as an embedded part of a customer hub, running in the background and available to answer questions and provide recommendations. When the hub and AI agent are both embedded within your CRM, you can implement them without developer resources.

Apparel brand Ministry of Supply, for example, improved their customer experience with a customer hub and an embedded AI customer agent. Now, customers can log in to a personalized hub on the Ministry of Supply website to view recently viewed items, order history with links for repurchasing, and recommendations for what they should buy next.

Meanwhile, an AI customer agent is available for a quick turnaround on customer questions when they come up, with an option to “talk to a human” throughout. Within a 60-day period, the AI agent autonomously resolved 84% of product recommendation chat queries, while the hub surfaced relevant product recommendations to boost cross-selling.

AI-powered helpdesk: human involvement when it matters most

With an AI-powered helpdesk that’s embedded in your CRM, every support conversation lands in one workspace tied to the customer’s complete story: marketing engagement, browsing behavior, order history, past service interactions, and much more. This gives both your AI and human agents full context when jumping into a conversation with a customer.

Here’s what a customer service interaction might look like when your helpdesk is AI-powered and embedded in your CRM:

  1. Your AI customer agent recognizes exactly when it needs to escalate a conversation to a human agent.
  2. AI within the helpdesk automatically tags the conversation with the appropriate information and routes it to the correct human agent for resolution.
  3. Because your human agent has visibility into the customer’s complete history of interactions with your brand, they’re able to resolve the customer’s problem quickly and smoothly, without toggling between tools or asking them to repeat themselves.

When the Harney & Sons AI customer agent detects that a customer inquiry requires a human touch, for example, it passes the conversation on with full context preserved. The support team can now resolve tickets with less toggling between tabs, contributing to wins like a 25% PoP reduction in average service ticket resolution time in 30 days.

What is a good AI customer service strategy for 2026?

When we asked them about the biggest barriers to AI adoption in 2026, customer service leaders said they’re most worried about consumer discomfort with AI (47%), the overall cost of AI tools (37%), and data quality, privacy, or compliance challenges (36%).

With that in mind, how can customer service teams successfully and cost-effectively use AI to reduce repetitive work, so their human agents can spend more time on conversations that need empathy, judgment, and expertise?

Here’s what it might look like in practice:

  • Address the trust gap. Train your AI on your storefront and customer data, label AI interactions clearly so customers always understand who they’re talking to, and always offer customers the option to speak to a human.
  • Audit your tech stack. If cost is a concern, look for opportunities to consolidate multiple tools into one. An AI-powered CRM combines data, marketing, service, and analytics capabilities into a single source of truth, which not only is more cost-effective but also empowers your teams to understand your customers better and engage with them accordingly.
  • Invest in quality data. To address security concerns and preserve customer trust, use zero- and first-party data whose collection requires explicit consent from customers. Always be transparent about how you collect, store, and use consumer data, with easily accessible links to your privacy policy and terms and conditions.
  • Test AI use cases. Start small with high-volume, low-risk use cases. Test ROI before scaling and choose user-friendly tools that give your team time to learn.
  • Measure what matters. Measure AI-specific customer service metrics, like AI agent resolutions, reduction in human agent ticket volume, and escalations.

Elevate your customer experience with K:AI (Klaviyo AI)

A great customer service experience can turn quick resolutions into customer loyalty and new revenue opportunities. As the AI-first B2C CRM, Klaviyo brings service and marketing together into one platform where brands can:

  • Build a personalized, on-site destination for self-service with Klaviyo Customer Hub.
  • Answer questions, recommend products, and convert visitors into buyers with K:AI Customer Agent.
  • Resolve simple and complex issues across multiple channels with Klaviyo Helpdesk.

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