The 5 Customer Service AI Trends Shaping 2025 — Industry Leaders Weigh In

Customer service AI is transforming our understanding of what’s possible in customer experience. Beyond the buzz about efficiency gains lies a more profound revolution reshaping customer care from the ground up. Here’s an insider’s look at how leading brands leverage AI to reimagine service – insights directly from the innovators crafting the future of customer experience.

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Trend #1: Slow Your Roll — Why Strategic AI Is the Way

Forget the race to implement customer service AI at all costs. Industry leaders are taking a more strategic approach — and it’s paying off. The real trend? Taking time to get it right.

Lauren Inman-Semerau, Head of CX at Rothy’s, emphasizes this crucial pre-implementation phase: “I believe the pre-implementation phase is arguably the most important part of the entire journey. It’s your chance to think about why you want to do this and if the timing is right. We’re starting to move past the misconception that AI will replace humans. While cost efficiency is important, it’s not the most important factor.”

John Burke, VP of CX at Wine Enthusiast, reinforces this strategic approach: “The near future for customer experience is about finding strategic, purposeful places where AI makes the experience better. I’m focused on self-service because customers want control over their purchases and support. AI can make that process faster and more seamless, but we avoid just slapping AI into workflows where it doesn’t belong.”

CX expert Mara Castro, whose experience spans Warby Parker, Evolve, and now Ruggable, sees this shift clearly: “Right now, people are heavily focused on AI, but they’re viewing it in a limited way — primarily as a tool for cutting costs and continuing to treat CX as a cost center. What I see as the most transformative trend is how technology — especially AI — can truly augment the customer experience in a holistic way.”

But this transformation requires patience. Danny Cox, VP of Guest Experiences at Breeze Airways, says: “Initially, the biggest challenge was selecting the right AI because there’s quite a bit of bad AI out there. After choosing Gladly’s AI, the biggest challenge was remaining patient and not rushing to roll out something that wasn’t ready.”

What thoughtful AI implementation looks like:

• Starting with clear strategic goals beyond cost savings
• Taking time to map AI opportunities across the customer journey
• Building comprehensive testing protocols
• Creating meaningful success metrics before launch
• Focusing on customer experience enhancement over speed to market

Trend #2: “Spring Cleaning” Ahead of Your AI

Think you can just plug in customer service AI and watch the magic happen? Think again. The secret to AI success isn’t in the algorithm — it’s in the groundwork. Leading companies are discovering that AI amplifies everything — including your mistakes. That’s why the first step in any customer service AI implementation isn’t about the tech at all.

Mandi Geary, Director of CX at BSN Sports, learned this firsthand: “Implementing Answer Threads has been insightful for us because you think you have all the right answers, but when you start to piece it out and layer in that AI, some of it may not be as good as we thought it was. It’s been a good ‘spring cleaning’ for us to really deep dive into our content and make sure it’s clean, and we’re accountable for that content before we start relying on AI to transfer that information for us.”

Lauren puts it more bluntly: “Clean the cobwebs out of the house so that you are starting with a base to build on that is clean. It will save you so much time later.”

What winning companies are doing differently:

• Auditing and updating knowledge bases before AI implementation
• Creating clear content governance processes
• Building standardized response templates
• Documenting customer service processes
• Setting up regular content review cycles

Trend #3: Use AI and Humans for Perfect CX Harmony

The whole “AI vs. humans” debate? It’s so 2023. Today’s customer service AI isn’t about replacement — it’s about creating the perfect partnership. Leading companies are discovering that magic happens when AI and human agents each play to their strengths.

Mara shares this vision: “The key is providing customers with options, recognizing that no two customers are alike. What matters most is executing whatever approach you choose effectively. If you automate your service poorly, customers will be frustrated. The goal should be identifying friction points in the customer journey and using technology to reduce them. While self-service options are important, ensure customers can easily reach a human agent when needed.”

This understanding of customer individuality is exactly what drives Lauren’s approach to experience delivery: “At the end of the day, customers want to be heard, serviced, and delivered to. Our current largest customer base really wants experiences. As AI evolves, customer needs may not change, but how we deliver those experiences will.”

She’s even found ways to make AI feel like part of the Rothy’s team: “We do a lot to try to make the agent brand ambassador experience really good. And I thought a lot about that in the AI implementation too. Which was part of why we branded [Rothy’s chatbot] Sandi. Now my agents have a peer; they don’t have a bot.”

What this partnership looks like in practice:

• AI handling routine queries and data gathering
• Humans focusing on complex problem-solving
• Seamless handoffs between AI and agents
• Collaborative insight sharing
• Team-based performance metrics

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Trend #4: Layer Metrics to Keep Score in the AI Game

Traditional KPIs are evolving, and customer service AI is pushing us to redefine success. The metrics that mattered yesterday might not tell the full story today.

Lauren explains this shift: “Overall metrics are going to start shifting, and what we think about as industry standard is going to change because of AI. We don’t want to give up those base health metrics like SLA, average handle time, FCR, and CSAT. But now we have the opportunity to layer onto them things like resolution rate for your bot and transfer rate to your agents.”

One valuable addition to this layered metrics approach is Sidekick Conversation Handle Time (CHT). This metric provides a directional estimate of the time Gladly’s conversational and collaborative AI saves by handling routine inquiries that agents would otherwise manage. By analyzing message volume, CHT gives businesses a clearer picture of workload reduction, allowing teams to use agent time more strategically. It supports staffing decisions by showing where automation is freeing up agents to focus on high-value work, such as complex problem-solving, sales, and relationship building.

Lauren underscores the importance of context when evaluating these metrics, highlighting the need to consider individual agent handle times to ensure they remain reasonable based on the types of issues that brand ambassadors handle. Complex topics naturally take longer to resolve than simpler ones, so handle time data could be easily misinterpreted without this context.

The new metrics playbook includes:

• AI resolution rates
• Sentiment analysis scores
• Predictive accuracy measurements
• Human-AI collaboration effectiveness
• Customer effort reduction metrics

Trend #5: Turn AI Data into Customer Magic

While everyone’s focused on response times, leading companies are using customer service AI to crack the code on customer behavior. This isn’t just about collecting data – it’s about turning insights into action.

Mandi describes this evolution: “The biggest trend I see is leveraging AI in the customer experience space to extend our concept of personalization. We’re seeing AI that can extract real-time data and customer insights, helping agents provide more accurate, personalized information focused on customers’ product needs, desires, or wants…we’re compounding our Gladly customer data with AI technology to feed back quantifiable and qualitative information to the business to really help identify root causes.”

How leaders are leveraging AI insights:

• Predicting customer needs before they arise
• Identifying emerging product issues
• Personalizing service approaches
• Optimizing customer journeys
• Building proactive support strategies

The Real Future of Customer Service AI

As we look toward 2025, one thing is clear: customer service AI isn’t just about automating what we already do — it’s about reimagining what’s possible. The companies that win won’t be the ones with the fanciest chatbots. They’ll be the ones that use AI to transform how they understand and serve their customers.

Success in this new era requires:

• Starting with clean, organized data
• Looking beyond cost savings
• Building true human-AI partnerships
• Measuring what really matters
• Using insights to drive action

The future of customer service AI is here, and it’s a lot more exciting than your chatbot would have you believe. The question isn’t whether to embrace AI — it’s how to do it right.

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