Voice AI agents are a rapidly evolving area in the business world, moving far beyond simple interactive voice response (IVR) systems. The trend is significantly impacting both customer loyalty and word-of-mouth (WOM) advertising.
Alex Levin, CEO of Regal, a customer-centric contact center software company, believes that voice AI agents will usher in a new era of brand loyalty.
Some customers now save the direct phone number for a brand’s AI voice agent — not the general support line — and pass it along to friends the same way they would for a trusted local electrician or plumber. But poorly implemented voice AI can muddy a company’s competitive advantage if it doesn’t deliver consistent, efficient, and emotionally intelligent customer experiences.
"This buys those brands' loyalty and word-of-mouth advertising. Historically, customers did everything to avoid having to call support, wait on hold, and suffer through yet another terrible AI chatbot interaction," Levin told CRM Buyer.
What gives well-trained AI agents a business edge? They nail the basics by immediately answering every call, having context about the customer without repeating themselves, and always coming with a positive attitude, he insisted.
How Voice AI Fixes the IVR Gap
Traditional IVR-based phone trees differ significantly from the conversational flow of a Regal voice AI agent. A major reason is cost.
According to Levin, IVR's purpose was to frustrate customers and deflect them from speaking with someone. It was too expensive for brands to take the call.
"AI Agents are so much less expensive that they allow brands to take every call and prioritize the customer's desired channel," he explained.
Regal ensures high-priority performance by measuring standard contact center metrics such as first-contact resolution and customer satisfaction (CSAT), as well as customer revenue generated and customer retention.
Levin warned that a poorly implemented AI agent can lead to frustration, misunderstandings, or repeated transfers, quickly generating negative word of mouth (detractors) that damage brand reputation and loyalty.
That risk emphasizes the need for natural language understanding (NLU) and effective handoffs to human agents. Regal's approach addresses the most significant hurdle — the psychological shift — in getting customers to embrace this new form of interaction and to actively share an AI agent's contact information.
AI-Powered Voice Agents at a Glance
AI voice agents are advanced software systems that interact with users using human-like voices, natural tone, and swift, intelligent responses. They are powered by sophisticated technologies such as automatic speech recognition (ASR), natural language processing (NLP), and large language models (LLMs), enabling them to understand human intent and generate contextually relevant answers.
For businesses, these agents deploy to automate customer interactions, serving as virtual receptionists or support staff capable of managing high-volume, around-the-clock communications. They can revolutionize operations for retailers and small- and medium-sized businesses (SMBs) by automating high-volume, repetitive tasks, enabling 24/7 service, and enhancing the overall customer experience (CX).
Modern voice agents can enhance customer service and support by automating high-volume, repetitive inquiries in multiple languages. They can process address changes, provide real-time package tracking updates, guide customers through scheduling or rescheduling deliveries, and even initiate returns or refunds, all through natural conversation.
AI voice agents drive sales and personalization through lead qualification and conversion, serve as virtual shopping assistants, and foster proactive engagement by making outbound calls to customers with updates. The technology can integrate with existing business systems (such as CRM, POS, or inventory management), ensuring that customer information is always up to date.
Improving Call Center Failure Rates
Most people are used to poor automation and are not ready to treat an AI agent like a regular conversation partner, Levin admitted. He sees that when callers use traditional one-word answers instead of complete sentences.
Regal's goal is to enhance the overall customer experience, not replace human agents. The integration of AI-powered voice agents frees up human counterparts to handle the most complex issues.
"Not all AI agents can handle complex tasks," he shared. "It is possible to build the infrastructure needed -- including RAG [retrieval-augmented generation], custom actions, and workflows -- to complete the most complex tasks."
Levin noted that Regal's technology better integrates with human agents. Contact centers experience 40% turnover each year because the job is thankless.
"We see AI agents as the solution to replace these difficult jobs. Instead, the people interested in careers in CX will end up having six-figure jobs handling escalated issues and building and improving AI agents," he said.
Building a Better AI Agent
Levin explained that Regal built a unified customer profile that integrates with companies' data sources. It works with each brand to give every AI agent its own defined personality that reflects the brand’s promise.
Regal's platform also ensures that security and privacy measures are in place to protect customer data and ensure these interactions are secure. The developer imposes several significant limitations.
"First, AI models never store or train on customer data. AI agents only have access to the specific fields of data needed on that specific customer for that specific call," he emphasized.
"Second, we have global guardrails that limit what AI agents can do, and what a nefarious customer could do with AI agents."
A Future Built Around Voice AI Agents
Over the next five years, Levin sees customers leveraging voice more often than other channels or self-serve once they realize it is always on and always easy. He also sees challenges for companies looking to implement a voice AI strategy.
"It’s easy for companies to see that in five years, the majority of CX interactions will be handled by AI. To be successful, they must be ready to change the goals and incentives of the CX team significantly," he concluded.
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