SEPTEMBER 2023 RELEASES
September 2023 Releases
What is an AI Voice Agent for CX?
AI voice agents are revolutionizing how businesses handle customer interactions, reducing wait times, and personalizing conversations in ways human agents simply can't. But what exactly are AI voice agents, and how do they work? In this article, we’ll explore the technology behind AI voice agents, their benefits, real-world use cases, and how they are reshaping customer service across industries.
What is an AI Voice Agent?
An AI voice agent is an advanced conversational AI tool that uses Generative AI, Large Language Models (LLMs), and speech recognition to interact with customers via phone calls or other voice-enabled platforms (such as in-app voice). Unlike traditional Interactive Voice Response (IVR) systems that follow rigid scripts and option menus, AI voice agents powered by generative AI can understand intent, generate human-like responses, and provide dynamic, personalized conversations in real time. (Wait? You mean like Siri and Alexa? No, those are AI Voice Assistants that are more rule-based, have limited memory, and can’t take turns.)
How Do AI Voice Agents Work?
Modern AI voice agents rely on a combination of cutting-edge technologies to process, interpret, and respond to customer inquiries:
- Automatic Speech Recognition (ASR)
- Converts spoken language into text in real time (transcription).
- Generative AI & Large Language Models (LLMs)
- Uses deep learning models to generate conversational responses dynamically, making interactions more fluid and natural.
- Natural Language Processing (NLP) for Intent Recognition
- Analyzes customer queries, detects intent, and provides structured understanding before generating a response.
- Text-to-Speech (TTS) Technology
- Converts AI-generated text responses into human-like speech, making conversations feel natural.
- Integration with CRM & Backend Systems
- AI voice agents pull data from CRM platforms, databases, and APIs to provide relevant information during interactions.
New advanced “real-time LLMs” in beta from OpenAI and Gemini are fully “voice-to-voice” models, avoiding the need for ASR (step 1) and TTS (step 4). These models are lower latency and hold a promise to eventually incorporate emotion-detection. However, they are still currently nascent.
Benefits of AI Voice Agents for Businesses
The rise of AI voice agents is driven by cost savings, efficiency, and superior customer experience (CX). Here’s how businesses benefit:
✅ 24/7 Availability – AI voice agents handle inquiries around the clock, reducing wait times and improving customer satisfaction.
✅ Scalability – Unlike human agents, AI voice agents can manage thousands of simultaneous interactions without requiring additional resources.
✅ Reduced Operational Costs – Businesses cut customer support headcount, training and recruiting costs by automating repetitive queries and streamlining workflows.
✅ Consistent & Personalized Responses – AI voice agents provide responsive, accurate, and context-aware responses based on customer history.
✅ Multilingual Support – Advanced AI models can engage customers in multiple languages, expanding business reach globally.
AI Voice Agents vs. Human Call Center Agents: Key Differences
You can think of using AI Voice Agents as a replacement for your IVRs or IVAs where a better customer experience is warranted, or as a replacement for Human agents on calls that are relatively constrained (e.g., guided, formulaic, limited optionality) and short (e.g., <5 min).
Human agents remain necessary for highly complex interactions or those that require licensing. While IVR systems, though very limited, are still the most cost efficient and thereby valuable for efficiently handling very transactional inquiries like checking a bank balance.
We expect IVAs to be deprecated as companies adopt generative-AI Voice Agents.
Industries Using AI Voice Agents
AI voice agents are transforming customer service across many industries:
- E-commerce: Order tracking, refunds, personalized recommendations.
- Education: Applicant enrollment, scheduling interviews, student success.
- Banking & Finance: Balance inquiries, fraud detection, loan processing, collections.
- Healthcare: Appointment scheduling, prescription reminders, insurance validation, collections.
- Home Services: Lead qualification, appointment setting, inbound support.
- Insurance: Lead qualification, claims inquiries, payment reminders.
- Real Estate: Property inquiries, scheduling viewings, lead follow-ups.
- Telecom: Plan upgrades, troubleshooting, billing support.
Case Study: AI Voice Agent in Action
- Company: A leading Health Insurance Marketplace.
- Problem: Experiences a large spike in call volumes during AEP (Annual Enrollment Period) for Medicare eligible Americans. Normally the customer has to scale up agent headcount temporarily, and train those agents very quickly, leading to high operational costs and below average agent quality.
- Solution: Deployed Regal’s generative AI phone agent as a Medicare screener. Qualified leads were then transferred to a live licensed agent to complete the transaction.
- Results: Zero hold times, 40% Qualified Transfer Rate (on par with their best human agents), 94% Customer Sentiment.
Current Challenges with AI Voice Agents
- Ecosystem immaturity – the entire ecosystem collectively underpinning AI voice agents, from LLM providers (e.g., OpenAI) to transcription providers (e.g., Deepgram) to TTS providers (e.g., ElevenLabs), are all newer companies, the technology is still actively developing, and so uptime SLAs are not as robust, protocols to move to backup providers are not established, etc. Working with a partner like Regal that incorporates multiple providers in each of these areas is a key way to mitigate this risk.
- Regulatory uncertainty – there are developing state and federal regulations for generative AI voice agents that are in flux, and unclear if/when they will move forward. See more details in this article AI Ethics & Disclosure Timing in 2025.
These are natural challenges with any new technology category, and are sure to be resolved over time as more companies deploy AI voice agents. The promise of AI voice agents is so great for businesses and consumers alike, we don’t believe either of these will block the wave of AI voice agents coming to contact centers.
Conclusion
AI voice agents powered by Generative AI and LLMs are reshaping customer service by enhancing efficiency, reducing costs, and delivering personalized, real-time interactions. Businesses that adopt AI-powered voice agents will gain a competitive edge, improve customer experience, and scale operations effortlessly. And now any time someone asks you “what is an AI Voice Agent” you’ve got the answer!
💡 Want to integrate AI voice agents into your business? Contact Regal.ai today for a custom AI Agent demo.
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