Voice AI’s big year — the secret to more scalable CX in 2025

Voice AI is taking center stage in 2025. According to our research, nearly 80 percent of CX leaders believe voice AI is ushering in a new era of more seamless problem-solving, leaving robotic IVRs in the past. Thanks to its generative capabilities, voice AI understands and responds to spoken language in a natural, human-like way, assisting customers without the cost of 24/7 staffing. And customers are embracing the change—65 percent say voice AI improves phone interactions. One reason why? Many find it easier to explain and resolve complex issues.

This shift couldn’t come at a better time. McKinsey predicts call volumes will surge by up to 20 percent in just a few years, compounded by persistent talent shortages and tighter customer care budgets. But with voice AI at the ready, call center leaders can tackle these challenges head-on. Take Qualia, for example. By automating post-call transcription and summarization, the team cut after-call work in half.

Voice AI is a powerful, yet still emerging solution. That means many CX leaders are still figuring out their strategies or even where to begin. Based on our experience working with thousands of CX leaders, here are 5 tactics to effectively scale your voice AI and meet growing demands.

5 strategies to effectively scale voice AI in 2025

1. Let AI agents for voice handle common, high-volume queries

Missed calls and long wait times can cost you customers—Gartner found that nearly a third of callers abandon their service journeys if kept waiting too long. AI agents for voice can cut the queue, capable of handling over half of incoming calls.

With generative AI, these advanced voice bots can handle your most frequent customer needs with the care and efficiency of a human agent—making them essential for call centers during peak periods. Whether authenticating calls, answering questions, or booking reservations, AI agents for voice are upending traditional call center staffing methods by ensuring fast, accurate support around-the-clock. Plus, with their multilingual capabilities, they help call centers scale their CX globally while keeping costs under control.

Start simple by deploying AI agents to handle your most common, repetitive phone queries. Analyze call center data to identify high-volume FAQs like order tracking or password resets. Offloading these tasks frees human agents for more complex issues while giving you key insights into AI performance—paving the way for more advanced use cases over time.

2. Use AI to direct calls and prepare agents

For those higher-stakes interactions, AI can direct callers to the right agent and prepare them with critical insights into customers’ needs and emotions. With real-time context at their fingertips, agents can provide faster and more bespoke resolutions at scale.

Use AI to intelligently route calls based on intent, sentiment, and language, as well as conversation priority, agent skills, and availability. Define clear call routing rules to ensure customers reach the right agent the first time, eliminating frustrating transfers and speeding up resolutions.

Adopting an omnichannel routing strategy is also essential. It allows customers to switch channels more seamlessly, whether they request a receipt via email after a call or opt for a text instead of waiting on hold. A common mistake we see CX leaders make before coming to us is failing to integrate voice with other channels, creating conversation silos. A unified approach ensures continuity across interactions, making support smoother and more connected.

3. Speed up after-call work with AI call summaries and transcripts

With call volumes surging and teams shrinking, efficiency is everything. Equip your agents with an AI assistant that automatically summarizes and transcribes calls, streamlining call wrap-ups. It might seem like a small win, but this can save at least 20 percent of agents’ time, making a big impact on overall productivity.

Take it a step further by using call summaries and transcripts to automate workflows. For example, AI can detect keywords like “urgent” and instantly flag tickets for priority handling, ensuring faster, and more strategic support.

Beyond efficiency, AI-driven summaries and transcripts improve service quality by capturing every detail, eliminating the need for agents to take notes or rely on memory. Make sure summaries and transcripts are recorded in your CX platform—this allows agents to quickly reference past conversations, leading to more tailored and informed resolutions.

4. Leverage AI-driven insights to enhance call quality

Call transcripts do more than streamline after-call work—they power automated quality assurance (QA) across 100 percent of phone interactions, including outsourced call centers and AI agents for voice. And with 63 percent of customers willing to switch brands after just one bad experience, scaling QA is essential for maintaining service quality as call volumes rise.

AI-driven insights flag when customers are upset, detect dead air, and highlight calls that need attention—whether an agent missed a required disclosure or a compliance issue arises. These insights help you catch quality gaps, reduce churn, and provide targeted agent training to ensure every interaction exceeds customer expectations.

Take Conservice, for example. By using Zendesk QA to score every phone call, the company’s Internal Quality Score (IQS) improved to a whopping 97 percent.

5. Use AI-powered forecasting to optimize staffing

Call center leaders are also using AI to optimize and scale team management. AI-powered workforce management tools can predict staffing needs based on call volume and automatically schedule agents to meet demand.

Traditional forecasting and scheduling methods often result in costly overstaffing or slow response times due to understaffing. AI tools help call center leaders get ahead of these challenges, ensuring the right agents with the right skills are staffed on the right channels—optimizing resource allocation, reducing wait times, and eliminating overtime costs.

This is another area that highlights the urgent need to integrate voice with other support channels to create a more seamless and efficient customer experience. Conservice is a prime example—by using Zendesk WFM to forecast staffing across phone, email, and chat, CX leaders ensure agents are deployed where demand is highest. With these cross-channel insights, the team was able to operate with 40 percent less staff while boosting agent productivity by 67 percent.

Let your customers be heard at every touchpoint

By providing a more effortless CX, voice AI is enabling consumers to feel truly heard and raising the bar for support—creating a clear divide between brands that embrace it and those that lag behind. With more than half of consumers already engaging with advanced voice AI and 60 percent eager for wider adoption, voice AI is now an essential ingredient in any customer service strategy.

But Voice AI is just one part of the equation. Leading CX teams take an integrated approach, ensuring seamless, AI-powered support across every channel.

Elevate your customer service—on the phone and beyond—with our complete CX solution for the AI era.