The Gist
Rapid evolution. Voice AI for customer service is advancing quickly, fueled by major technology improvements. Core components. Four key technologies are driving both agent enablement and call automation. Expanding market. Current adoption is strong, with studies projecting striking annual growth ahead.
Editor’s note: We’re kicking off a three-part series from new CMSWire contributor Andrew Neff on the state (and speed) of voice AI. Part 1, launching today, sets the baseline: how far voice AI has come in customer service and which technologies are compounding the surge. Next up, Part 2 breaks down the three market forces accelerating adoption and revenue impact. We’ll close with Part 3, a forward look at how voice AI extends beyond service into core business and sales over the next decade. If Part 1 captures the essence and engines of growth, Part 2 explains the acceleration—and Part 3 assembles where this all goes next, including a few startlingly logical use cases you might not see coming.
Let’s start with perspective on where we were vs. where we’re heading. Automated voice customer service started as IVR with numeric choices for the user, and those who have not adapted still use this.
Sector analyst Blair Pleasant from COMMfusion said, “AI advancements have entirely reinvented and revitalized the voice market.” Voice AI now injects human-like voices into customer interactions, the first version of which was AI IVR.
From my first-hand experience working on this, an early version of conversational AI, it leverages AI choices and automated journey mapping to build a basic verbal dialogue. As with any new technology, adding generative AI alone was first viewed as a “fix it all.” However, early versions received mixed reviews.
Those errors are mostly fixed. More learning combined with new tools and improved conversational AI/large language models (LLMs) have transformed voice AI. Now it’s growing in contact centers, a proven solution that users (50% have used, according to PwC) and companies say they are comfortable with. This trend is just one of the many reasons NiCE just acquired Cognigy, a recognized sector leader.
Said Alan Ranger, Cognigy VP of Marketing, “The growing prevalence of voice AI solutions is well-established, notably in customer service.”
Isn’t it ironic? Strategically, we are still early in the adoption and growth cycle. How can we have come so far so quickly? Multiple success variables now prove market acceptance. An important distinction is that “conversational AI” refers to both text and voice while voice AI refers to conversational AI in a “voice only” user experience.
Let’s start below with four specific reasons voice AI is now well-known in customer service and growing:
Table of Contents
Four Technology Strengths: Voice AI Advancements Help Both Your Agents and Call Automation
Agent Assist Tools: Real-time, On Screen Tools Powered by Voice AI Have Evolved on Multiple Levels
Picture customer service agents who can view multiple tools on their monitor while the call is in session. Voice AI transcribes calls in real-time that the agent can leverage to help them in multiple ways. Choose 1 or all.
In real-time, it can serve up optional answers in text on screen and coach the contact center agent on tone of voice or actions based on customer history. It can literally provide checklists for a human agent to monitor and thus cover all bases needed for the call. This elevates FCR.
Other tools solve the challenge of agents’ language limitations, experience level and vertical sector knowledge. Part of agentic AI, there is now a full range of tools for tasks. Reliable, consistent answers from voice AI shown to the agent in real-time tackles potential issues and elevates the average performance across all agents. It boosts CX, CSAT and session consistency for the customer. Early agents’ training time is now dramatically reduced, a key cost when there is notable agent turnover or vertical expertise is needed.
Related Article: Agentic AI and the Future of Customer Support: What CX Leaders Need to Know
Elevated Performance: Automated Calls Complete Simple Tasks and Reduce Mistakes on FAQs
Standard calls like booking appointments or checking balances are easier and more accurate in a truly conversational setting.
Journey mapping is built-in for each vertical, improving data accuracy and customer comfort levels. Handling a higher percentage of the straightforward calls is crucial. In the past, some customers would demand human agents for even simple calls as they did not trust the UX of AI IVR. That has changed, and boosts in session results show multiple key benefits driving it.
Now, regular tasks are resolved faster and with a lower error rate by automated VoiceAI. How? Better vertical LLMs are paired with the next generation NLP and boosted STT/TTS algorithms. Higher customer confidence levels result in agents focusing more on the truly challenging calls. It offers the option of reducing human agents if the company so chooses. It certainly reduces cost-per-call and overall costs. While this describes customer service use, it’s easy to see how similar tasks could be handled by VoiceAI in tangential markets like phoned-in restaurant orders or outbound calls.
Hyper-Personalization: Improved Speech Recognition and NLG Creation Quality Boost Call Results
Raise the bar across the board. “80% of businesses plan to use voice AI for CustServ by 2026” (Statistica). Multilingual pre- training, accent variation, conversation history, sector-specific keywords and abbreviations all elevate UX, CX and reduce cost per call as agents handle fewer calls. Hyper-personalization creates pleasant custom calls and more accurate answers. Customers know live agents are still just one step away, but are less likely to demand it early. Formulaic wording used every single time? Not any more!
Now VoiceAI understands both context and emotion, using the right tone of voice and subtle language cues to match the right mood needed to keep customers happy and thus reach FCR.
Calling out AI as ‘digital labor’ or ‘AI coworkers’ is becoming popular but easily goes too far as surveys show these are nicknames but not workers’ true feelings.
– Blair Pleasant, president and principal analyst, COMMfusion
Post-Call Assessment Tools: Review All Calls to Help Solve More Agent Needs and Fix Journey Issues
In the past, a random sample of a very small percentage of agents’ calls was reviewed by the supervisor personally followed by one-on-one meetings and extra agent training. All very time consuming where time is money. Voice AI post-call tools now automatically assess everything and provide agent-friendly.
Recommendations personalized for each agent’s improvement needs. All calls, all agents. Serious time and money are saved for agent managers, and CSAT jumps up for all. The same deep, all-inclusive data mining tools identify roadblocks in the customer journey where customers demand a live agent. They report the frequency and can automatically generate numerous options to fix the problem.
This asset has huge business value and can be presented as a free value-add, reducing engineering needs and elevating brand value as customers are happier.
Related Article: Why Voice May Be the Ultimate CX Interface for AI Adoption
What Is the State of the Voice AI Market?
It’s both early and well-proven, but what is the market now and how fast it growing annually? A simple question took serious review time, but I averaged out 5 official voice AI reports. Each includes customer service. Those revenue projections and other key changes that voice AI is driving will be the focus of part 2.
Learning OpportunitiesView all
The automation and industry acceptance have empowered voice AI solution providers to add the next layer of “performance boosters,” which we will cover as there are more than I expected.
FAQ About Voice AI in Customer Service
Editor’s note: Key questions surrounding voice AI’s role in customer service and its rapid market growth.
How has voice AI evolved in customer service?
Voice AI has moved far beyond basic IVR, now delivering real-time transcription, automated answers and contextual guidance that improve CX and reduce errors.
What is the market outlook for voice AI?
Multiple studies project striking annual growth, with adoption expanding across industries and use cases well beyond customer service.
Which technologies are driving voice AI adoption?
Advances in speech recognition, natural language generation, large language models and analytics are powering both agent assist tools and automation.
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